Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm

ERIC Educational Resources Information Center

Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.

2008-01-01

This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and…

A seismic fault recognition method based on ant colony optimization

NASA Astrophysics Data System (ADS)

Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

2018-05-01

Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

DTIC Science & Technology

2015-01-01

programming formulation of traveling salesman problems , Journal of the ACM, 7(4), 326-329. Montemanni, R., Gambardella, L. M., Rizzoli, A.E., Donati. A.V... salesman problem . BioSystem, 43(1), 73-81. Dror, M., Trudeau, P., 1989. Savings by split delivery routing. Transportation Science, 23, 141- 145. Dror, M...An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to solve the Split Delivery Vehicle Routing Problem Authors: Gautham Rajappa

An improved self-adaptive ant colony algorithm based on genetic strategy for the traveling salesman problem

NASA Astrophysics Data System (ADS)

Wang, Pan; Zhang, Yi; Yan, Dong

2018-05-01

Ant Colony Algorithm (ACA) is a powerful and effective algorithm for solving the combination optimization problem. Moreover, it was successfully used in traveling salesman problem (TSP). But it is easy to prematurely converge to the non-global optimal solution and the calculation time is too long. To overcome those shortcomings, a new method is presented-An improved self-adaptive Ant Colony Algorithm based on genetic strategy. The proposed method adopts adaptive strategy to adjust the parameters dynamically. And new crossover operation and inversion operation in genetic strategy was used in this method. We also make an experiment using the well-known data in TSPLIB. The experiment results show that the performance of the proposed method is better than the basic Ant Colony Algorithm and some improved ACA in both the result and the convergence time. The numerical results obtained also show that the proposed optimization method can achieve results close to the theoretical best known solutions at present.

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

Multiple-hopping trajectories near a rotating asteroid

NASA Astrophysics Data System (ADS)

Shen, Hong-Xin; Zhang, Tian-Jiao; Li, Zhao; Li, Heng-Nian

2017-03-01

We present a study of the transfer orbits connecting landing points of irregular-shaped asteroids. The landing points do not touch the surface of the asteroids and are chosen several meters above the surface. The ant colony optimization technique is used to calculate the multiple-hopping trajectories near an arbitrary irregular asteroid. This new method has three steps which are as follows: (1) the search of the maximal clique of candidate target landing points; (2) leg optimization connecting all landing point pairs; and (3) the hopping sequence optimization. In particular this method is applied to asteroids 433 Eros and 216 Kleopatra. We impose a critical constraint on the target landing points to allow for extensive exploration of the asteroid: the relative distance between all the arrived target positions should be larger than a minimum allowed value. Ant colony optimization is applied to find the set and sequence of targets, and the differential evolution algorithm is used to solve for the hopping orbits. The minimum-velocity increment tours of hopping trajectories connecting all the landing positions are obtained by ant colony optimization. The results from different size asteroids indicate that the cost of the minimum velocity-increment tour depends on the size of the asteroids.

Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

NASA Astrophysics Data System (ADS)

Hou, Huirang; Zheng, Dandan; Nie, Laixiao

2015-04-01

For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

Image Edge Tracking via Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Li, Ruowei; Wu, Hongkun; Liu, Shilong; Rahman, M. A.; Liu, Sanchi; Kwok, Ngai Ming

2018-04-01

A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.

A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements

NASA Astrophysics Data System (ADS)

Pu, Xun; Lu, XianLiang

2011-10-01

Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.

Optic disc detection using ant colony optimization

NASA Astrophysics Data System (ADS)

Dias, Marcy A.; Monteiro, Fernando C.

2012-09-01

The retinal fundus images are used in the treatment and diagnosis of several eye diseases, such as diabetic retinopathy and glaucoma. This paper proposes a new method to detect the optic disc (OD) automatically, due to the fact that the knowledge of the OD location is essential to the automatic analysis of retinal images. Ant Colony Optimization (ACO) is an optimization algorithm inspired by the foraging behaviour of some ant species that has been applied in image processing for edge detection. Recently, the ACO was used in fundus images to detect edges, and therefore, to segment the OD and other anatomical retinal structures. We present an algorithm for the detection of OD in the retina which takes advantage of the Gabor wavelet transform, entropy and ACO algorithm. Forty images of the retina from DRIVE database were used to evaluate the performance of our method.

Predicting Flood in Perlis Using Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Nadia Sabri, Syaidatul; Saian, Rizauddin

2017-06-01

Flood forecasting is widely being studied in order to reduce the effect of flood such as loss of property, loss of life and contamination of water supply. Usually flood occurs due to continuous heavy rainfall. This study used a variant of Ant Colony Optimization (ACO) algorithm named the Ant-Miner to develop the classification prediction model to predict flood. However, since Ant-Miner only accept discrete data, while rainfall data is a time series data, a pre-processing steps is needed to discretize the rainfall data initially. This study used a technique called the Symbolic Aggregate Approximation (SAX) to convert the rainfall time series data into discrete data. As an addition, Simple K-Means algorithm was used to cluster the data produced by SAX. The findings show that the predictive accuracy of the classification prediction model is more than 80%.

An ant colony optimization based algorithm for identifying gene regulatory elements.

PubMed

Liu, Wei; Chen, Hanwu; Chen, Ling

2013-08-01

It is one of the most important tasks in bioinformatics to identify the regulatory elements in gene sequences. Most of the existing algorithms for identifying regulatory elements are inclined to converge into a local optimum, and have high time complexity. Ant Colony Optimization (ACO) is a meta-heuristic method based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of real ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper designs and implements an ACO based algorithm named ACRI (ant-colony-regulatory-identification) for identifying all possible binding sites of transcription factor from the upstream of co-expressed genes. To accelerate the ants' searching process, a strategy of local optimization is presented to adjust the ants' start positions on the searched sequences. By exploiting the powerful optimization ability of ACO, the algorithm ACRI can not only improve precision of the results, but also achieve a very high speed. Experimental results on real world datasets show that ACRI can outperform other traditional algorithms in the respects of speed and quality of solutions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

NASA Astrophysics Data System (ADS)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

Dynamic Network Formation Using Ant Colony Optimization

DTIC Science & Technology

2009-03-01

backhauls, VRP with pick-up and delivery, VRP with satellite facilities, and VRP with time windows (Murata & Itai , 2005). The general vehicle...given route is only visited once. The objective of the basic problem is to minimize a total cost as follows (Murata & Itai , 2005): M m mc 1 min...Problem based on Ant Colony System. Second Internation Workshop on Freight Transportation and Logistics. Palermo, Italy. Murata, T., & Itai , R. (2005

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

NASA Astrophysics Data System (ADS)

Deng, Guang-Feng; Lin, Woo-Tsong

This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.

Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization.

PubMed

Juang, Chia-Feng; Hsu, Chia-Hung

2009-12-01

This paper proposes a new reinforcement-learning method using online rule generation and Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy controller is based on an interval type-2 fuzzy system (IT2FS). The antecedent part in the designed IT2FS uses interval type-2 fuzzy sets to improve controller robustness to noise. There are initially no fuzzy rules in the IT2FS. The ORGQACO concurrently designs both the structure and parameters of an IT2FS. We propose an online interval type-2 rule generation method for the evolution of system structure and flexible partitioning of the input space. Consequent part parameters in an IT2FS are designed using Q -values and the reinforcement local-global ant colony optimization algorithm. This algorithm selects the consequent part from a set of candidate actions according to ant pheromone trails and Q-values, both of which are updated using reinforcement signals. The ORGQACO design method is applied to the following three control problems: 1) truck-backing control; 2) magnetic-levitation control; and 3) chaotic-system control. The ORGQACO is compared with other reinforcement-learning methods to verify its efficiency and effectiveness. Comparisons with type-1 fuzzy systems verify the noise robustness property of using an IT2FS.

Application of ant colony Algorithm and particle swarm optimization in architectural design

NASA Astrophysics Data System (ADS)

Song, Ziyi; Wu, Yunfa; Song, Jianhua

2018-02-01

By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments. PMID:22666056

Adapting an ant colony metaphor for multi-robot chemical plume tracing.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments.

A multilevel ant colony optimization algorithm for classical and isothermic DNA sequencing by hybridization with multiplicity information available.

PubMed

Kwarciak, Kamil; Radom, Marcin; Formanowicz, Piotr

2016-04-01

The classical sequencing by hybridization takes into account a binary information about sequence composition. A given element from an oligonucleotide library is or is not a part of the target sequence. However, the DNA chip technology has been developed and it enables to receive a partial information about multiplicity of each oligonucleotide the analyzed sequence consist of. Currently, it is not possible to assess the exact data of such type but even partial information should be very useful. Two realistic multiplicity information models are taken into consideration in this paper. The first one, called "one and many" assumes that it is possible to obtain information if a given oligonucleotide occurs in a reconstructed sequence once or more than once. According to the second model, called "one, two and many", one is able to receive from biochemical experiment information if a given oligonucleotide is present in an analyzed sequence once, twice or at least three times. An ant colony optimization algorithm has been implemented to verify the above models and to compare with existing algorithms for sequencing by hybridization which utilize the additional information. The proposed algorithm solves the problem with any kind of hybridization errors. Computational experiment results confirm that using even the partial information about multiplicity leads to increased quality of reconstructed sequences. Moreover, they also show that the more precise model enables to obtain better solutions and the ant colony optimization algorithm outperforms the existing ones. Test data sets and the proposed ant colony optimization algorithm are available on: http://bioserver.cs.put.poznan.pl/download/ACO4mSBH.zip. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

NASA Astrophysics Data System (ADS)

Davoodi, M.; Mesgari, M. S.

2015-12-01

Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

Ant colony system algorithm for the optimization of beer fermentation control.

PubMed

Xiao, Jie; Zhou, Ze-Kui; Zhang, Guang-Xin

2004-12-01

Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.

Solving NP-Hard Problems with Physarum-Based Ant Colony System.

PubMed

Liu, Yuxin; Gao, Chao; Zhang, Zili; Lu, Yuxiao; Chen, Shi; Liang, Mingxin; Tao, Li

2017-01-01

NP-hard problems exist in many real world applications. Ant colony optimization (ACO) algorithms can provide approximate solutions for those NP-hard problems, but the performance of ACO algorithms is significantly reduced due to premature convergence and weak robustness, etc. With these observations in mind, this paper proposes a Physarum-based pheromone matrix optimization strategy in ant colony system (ACS) for solving NP-hard problems such as traveling salesman problem (TSP) and 0/1 knapsack problem (0/1 KP). In the Physarum-inspired mathematical model, one of the unique characteristics is that critical tubes can be reserved in the process of network evolution. The optimized updating strategy employs the unique feature and accelerates the positive feedback process in ACS, which contributes to the quick convergence of the optimal solution. Some experiments were conducted using both benchmark and real datasets. The experimental results show that the optimized ACS outperforms other meta-heuristic algorithms in accuracy and robustness for solving TSPs. Meanwhile, the convergence rate and robustness for solving 0/1 KPs are better than those of classical ACS.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

Efficient distribution of toy products using ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Hidayat, S.; Nurpraja, C. A.

2017-12-01

CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.

A Stochastic Inversion Method for Potential Field Data: Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou

2014-07-01

Simulating natural ants' foraging behavior, the ant colony optimization (ACO) algorithm performs excellently in combinational optimization problems, for example the traveling salesman problem and the quadratic assignment problem. However, the ACO is seldom used to inverted for gravitational and magnetic data. On the basis of the continuous and multi-dimensional objective function for potential field data optimization inversion, we present the node partition strategy ACO (NP-ACO) algorithm for inversion of model variables of fixed shape and recovery of physical property distributions of complicated shape models. We divide the continuous variables into discrete nodes and ants directionally tour the nodes by use of transition probabilities. We update the pheromone trails by use of Gaussian mapping between the objective function value and the quantity of pheromone. It can analyze the search results in real time and promote the rate of convergence and precision of inversion. Traditional mapping, including the ant-cycle system, weaken the differences between ant individuals and lead to premature convergence. We tested our method by use of synthetic data and real data from scenarios involving gravity and magnetic anomalies. The inverted model variables and recovered physical property distributions were in good agreement with the true values. The ACO algorithm for binary representation imaging and full imaging can recover sharper physical property distributions than traditional linear inversion methods. The ACO has good optimization capability and some excellent characteristics, for example robustness, parallel implementation, and portability, compared with other stochastic metaheuristics.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Attractors in Sequence Space: Agent-Based Exploration of MHC I Binding Peptides.

PubMed

Jäger, Natalie; Wisniewska, Joanna M; Hiss, Jan A; Freier, Anja; Losch, Florian O; Walden, Peter; Wrede, Paul; Schneider, Gisbert

2010-01-12

Ant Colony Optimization (ACO) is a meta-heuristic that utilizes a computational analogue of ant trail pheromones to solve combinatorial optimization problems. The size of the ant colony and the representation of the ants' pheromone trails is unique referring to the given optimization problem. In the present study, we employed ACO to generate novel peptides that stabilize MHC I protein on the plasma membrane of a murine lymphoma cell line. A jury of feedforward neural network classifiers served as fitness function for peptide design by ACO. Bioactive murine MHC I H-2K(b) stabilizing as well as nonstabilizing octapeptides were designed, synthesized and tested. These peptides reveal residue motifs that are relevant for MHC I receptor binding. We demonstrate how the performance of the implemented ACO algorithm depends on the colony size and the size of the search space. The actual peptide design process by ACO constitutes a search path in sequence space that can be visualized as trajectories on a self-organizing map (SOM). By projecting the sequence space on a SOM we visualize the convergence of the different solutions that emerge during the optimization process in sequence space. The SOM representation reveals attractors in sequence space for MHC I binding peptides. The combination of ACO and SOM enables systematic peptide optimization. This technique allows for the rational design of various types of bioactive peptides with minimal experimental effort. Here, we demonstrate its successful application to the design of MHC-I binding and nonbinding peptides which exhibit substantial bioactivity in a cell-based assay. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

PubMed

Mohsen, Abdulqader M

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

PubMed

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

NASA Astrophysics Data System (ADS)

Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

2014-05-01

Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

PubMed Central

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

Ant- and Ant-Colony-Inspired ALife Visual Art.

PubMed

Greenfield, Gary; Machado, Penousal

2015-01-01

Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior.

All-Optical Implementation of the Ant Colony Optimization Algorithm

PubMed Central

Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare

2016-01-01

We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems. PMID:27222098

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems

PubMed Central

Idris, Hajara; Junaidu, Sahalu B.; Adewumi, Aderemi O.

2017-01-01

The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time. PMID:28545075

Improved understanding of the searching behavior of ant colony optimization algorithms applied to the water distribution design problem

NASA Astrophysics Data System (ADS)

Zecchin, A. C.; Simpson, A. R.; Maier, H. R.; Marchi, A.; Nixon, J. B.

2012-09-01

Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP

PubMed Central

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality. PMID:27999590

Integrating geological uncertainty in long-term open pit mine production planning by ant colony optimization

NASA Astrophysics Data System (ADS)

Gilani, Seyed-Omid; Sattarvand, Javad

2016-02-01

Meeting production targets in terms of ore quantity and quality is critical for a successful mining operation. In-situ grade uncertainty causes both deviations from production targets and general financial deficits. A new stochastic optimization algorithm based on ant colony optimization (ACO) approach is developed herein to integrate geological uncertainty described through a series of the simulated ore bodies. Two different strategies were developed based on a single predefined probability value (Prob) and multiple probability values (Pro bnt) , respectively in order to improve the initial solutions that created by deterministic ACO procedure. Application at the Sungun copper mine in the northwest of Iran demonstrate the abilities of the stochastic approach to create a single schedule and control the risk of deviating from production targets over time and also increase the project value. A comparison between two strategies and traditional approach illustrates that the multiple probability strategy is able to produce better schedules, however, the single predefined probability is more practical in projects requiring of high flexibility degree.

Refraction law and Fermat principle: a project using the ant colony optimization algorithm for undergraduate students in physics

NASA Astrophysics Data System (ADS)

Vuong, Q. L.; Rigaut, C.; Gossuin, Y.

2018-07-01

A programming project for undergraduate students in physics is proposed in this work. Its goal is to check the Snell–Descartes law of refraction using the Fermat principle and the ant colony optimization algorithm. The project involves basic mathematics and physics and is adapted to students with basic programming skills. More advanced tools can be used (but are not mandatory) as parallelization or object-oriented programming, which makes the project also suitable for more experienced students. We propose two tests to validate the program. Our algorithm is able to find solutions which are close to the theoretical predictions. Two quantities are defined to study its convergence and the quality of the solutions. It is also shown that the choice of the values of the simulation parameters is important to efficiently obtain precise results.

Improved Ant Colony Clustering Algorithm and Its Performance Study

PubMed Central

Gao, Wei

2016-01-01

Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

Power plant maintenance scheduling using ant colony optimization: an improved formulation

NASA Astrophysics Data System (ADS)

Foong, Wai Kuan; Maier, Holger; Simpson, Angus

2008-04-01

It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm.

An ant colony optimization heuristic for an integrated production and distribution scheduling problem

NASA Astrophysics Data System (ADS)

Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju

2014-04-01

Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.

Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems.

PubMed

Mavrovouniotis, Michalis; Muller, Felipe M; Yang, Shengxiang

2016-06-13

For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms.

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

PubMed

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

Using Ant Colony Optimization for Routing in VLSI Chips

NASA Astrophysics Data System (ADS)

Arora, Tamanna; Moses, Melanie

2009-04-01

Rapid advances in VLSI technology have increased the number of transistors that fit on a single chip to about two billion. A frequent problem in the design of such high performance and high density VLSI layouts is that of routing wires that connect such large numbers of components. Most wire-routing problems are computationally hard. The quality of any routing algorithm is judged by the extent to which it satisfies routing constraints and design objectives. Some of the broader design objectives include minimizing total routed wire length, and minimizing total capacitance induced in the chip, both of which serve to minimize power consumed by the chip. Ant Colony Optimization algorithms (ACO) provide a multi-agent framework for combinatorial optimization by combining memory, stochastic decision and strategies of collective and distributed learning by ant-like agents. This paper applies ACO to the NP-hard problem of finding optimal routes for interconnect routing on VLSI chips. The constraints on interconnect routing are used by ants as heuristics which guide their search process. We found that ACO algorithms were able to successfully incorporate multiple constraints and route interconnects on suite of benchmark chips. On an average, the algorithm routed with total wire length 5.5% less than other established routing algorithms.

Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

DOT National Transportation Integrated Search

2010-05-01

Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

Swarm intelligence in bioinformatics: methods and implementations for discovering patterns of multiple sequences.

PubMed

Cui, Zhihua; Zhang, Yi

2014-02-01

As a promising and innovative research field, bioinformatics has attracted increasing attention recently. Beneath the enormous number of open problems in this field, one fundamental issue is about the accurate and efficient computational methodology that can deal with tremendous amounts of data. In this paper, we survey some applications of swarm intelligence to discover patterns of multiple sequences. To provide a deep insight, ant colony optimization, particle swarm optimization, artificial bee colony and artificial fish swarm algorithm are selected, and their applications to multiple sequence alignment and motif detecting problem are discussed.

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

Ant system: optimization by a colony of cooperating agents.

PubMed

Dorigo, M; Maniezzo, V; Colorni, A

1996-01-01

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

Skull removal in MR images using a modified artificial bee colony optimization algorithm.

PubMed

Taherdangkoo, Mohammad

2014-01-01

Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.

Parallelizing Ant Colony Optimization via Area of Expertise Learning

DTIC Science & Technology

2007-09-13

reminding me that when you don’t have anything else to say, a cat on the keyboard can at least get you a few more pages. Adrian A. de Freitas v Table of...Determination of Others’ Expertise (Q-Learning) . . . . . . . . 69 viii Figure Page 4.8. Pheromone Concentrations of Colonies 1, 2, and 3... Pheromone Concentrations of a Single ACS-GRIDWORLD Colony 75 4.14. Comparison of Policies Formed through AOE Learning . . . . . 75 4.15. Combined Pheromone

Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems

PubMed Central

Yin, Zhendong; Zhuang, Shufeng; Wu, Zhilu; Ma, Bo

2015-01-01

Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems. PMID:26426016

Population-Based Ant Colony Optimization for Multivariate Microaggregation

ERIC Educational Resources Information Center

Aksut, Ann Ahu

2013-01-01

Numerous organizations collect and distribute non-aggregate personal data for a variety of different purposes, including demographic and public health research. In these situations, the data distributor is responsible with the protection of the anonymity and personal information of individuals. Microaggregation is one of the most commonly used…

Optimal angle of polycrystalline silicon solar panels placed in a building using the ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Saouane, I.; Chaker, A.; Zaidi, B.; Shekhar, C.

2017-03-01

This paper describes the mathematical model used to determine the amount of solar radiation received on an inclined solar photovoltaic panel. The optimum slope angles for each month, season, and year have also been calculated for a solar photovoltaic panel. The optimization of the procedure to maximize the solar energy collected by the solar panel by varying the tilt angle is also presented. As a first step, the global solar radiation on the horizontal surface of a thermal photovoltaic panel during clear sky is estimated. Thereafter, the Muneer model, which provides the most accurate estimation of the total solar radiation at a given geographical point has been used to determine the optimum collector slope. Also, the Ant Colony Optimization (ACO) algorithm was applied to obtain the optimum tilt angle settings for PV collector to improve the PV collector efficiency. The results show good agreement between calculated and predicted results. Additionally, this paper presents studies carried out on the polycrystalline silicon solar panels for electrical energy generation in the city of Ghardaia. The electrical energy generation has been studied as a function of amount of irradiation received and the angle of optimum orientation of the solar panels.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Ant Colony Optimization Based Feature Selection for Web Page Classification

PubMed Central

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods. PMID:25136678

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

Adaptable Learning Pathway Generation with Ant Colony Optimization

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2009-01-01

One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

The modification of hybrid method of ant colony optimization, particle swarm optimization and 3-OPT algorithm in traveling salesman problem

NASA Astrophysics Data System (ADS)

Hertono, G. F.; Ubadah; Handari, B. D.

2018-03-01

The traveling salesman problem (TSP) is a famous problem in finding the shortest tour to visit every vertex exactly once, except the first vertex, given a set of vertices. This paper discusses three modification methods to solve TSP by combining Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and 3-Opt Algorithm. The ACO is used to find the solution of TSP, in which the PSO is implemented to find the best value of parameters α and β that are used in ACO.In order to reduce the total of tour length from the feasible solution obtained by ACO, then the 3-Opt will be used. In the first modification, the 3-Opt is used to reduce the total tour length from the feasible solutions obtained at each iteration, meanwhile, as the second modification, 3-Opt is used to reduce the total tour length from the entire solution obtained at every iteration. In the third modification, 3-Opt is used to reduce the total tour length from different solutions obtained at each iteration. Results are tested using 6 benchmark problems taken from TSPLIB by calculating the relative error to the best known solution as well as the running time. Among those modifications, only the second and third modification give satisfactory results except the second one needs more execution time compare to the third modifications.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

PubMed

Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

2016-01-01

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm

PubMed Central

Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

2016-01-01

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function. PMID:27893845

An ant colony optimization based feature selection for web page classification.

PubMed

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Khajeh, M.; Pourkarami, A.; Arefnejad, E.; Bohlooli, M.; Khatibi, A.; Ghaffari-Moghaddam, M.; Zareian-Jahromi, S.

2017-09-01

Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 μg/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.

Enhanced ant colony optimization for inventory routing problem

NASA Astrophysics Data System (ADS)

Wong, Lily; Moin, Noor Hasnah

2015-10-01

The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

A multipath routing protocol based on clustering and ant colony optimization for wireless sensor networks.

PubMed

Yang, Jing; Xu, Mai; Zhao, Wei; Xu, Baoguo

2010-01-01

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Applying ant colony optimization metaheuristic to solve forest transportation planning problems with side constraints

Treesearch

Marco A. Contreras; Woodam Chung; Greg Jones

2008-01-01

Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimization of Straight Cylindrical Turning Using Artificial Bee Colony (ABC) Algorithm

NASA Astrophysics Data System (ADS)

Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

2017-04-01

Artificial bee colony (ABC) algorithm, that mimics the intelligent foraging behavior of honey bees, is increasingly gaining acceptance in the field of process optimization, as it is capable of handling nonlinearity, complexity and uncertainty. Straight cylindrical turning is a complex and nonlinear machining process which involves the selection of appropriate cutting parameters that affect the quality of the workpiece. This paper presents the estimation of optimal cutting parameters of the straight cylindrical turning process using the ABC algorithm. The ABC algorithm is first tested on four benchmark problems of numerical optimization and its performance is compared with genetic algorithm (GA) and ant colony optimization (ACO) algorithm. Results indicate that, the rate of convergence of ABC algorithm is better than GA and ACO. Then, the ABC algorithm is used to predict optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool nose radius to achieve good surface finish. Results indicate that, the ABC algorithm estimated a comparable surface finish when compared with real coded genetic algorithm and differential evolution algorithm.

Application of ant colony optimization in development of models for prediction of anti-HIV-1 activity of HEPT derivatives.

PubMed

Zare-Shahabadi, Vali; Abbasitabar, Fatemeh

2010-09-01

Quantitative structure-activity relationship models were derived for 107 analogs of 1-[(2-hydroxyethoxy) methyl]-6-(phenylthio)thymine, a potent inhibitor of the HIV-1 reverse transcriptase. The activities of these compounds were investigated by means of multiple linear regression (MLR) technique. An ant colony optimization algorithm, called Memorized_ACS, was applied for selecting relevant descriptors and detecting outliers. This algorithm uses an external memory based upon knowledge incorporation from previous iterations. At first, the memory is empty, and then it is filled by running several ACS algorithms. In this respect, after each ACS run, the elite ant is stored in the memory and the process is continued to fill the memory. Here, pheromone updating is performed by all elite ants collected in the memory; this results in improvements in both exploration and exploitation behaviors of the ACS algorithm. The memory is then made empty and is filled again by performing several ACS algorithms using updated pheromone trails. This process is repeated for several iterations. At the end, the memory contains several top solutions for the problem. Number of appearance of each descriptor in the external memory is a good criterion for its importance. Finally, prediction is performed by the elitist ant, and interpretation is carried out by considering the importance of each descriptor. The best MLR model has a training error of 0.47 log (1/EC(50)) units (R(2) = 0.90) and a prediction error of 0.76 log (1/EC(50)) units (R(2) = 0.88). Copyright 2010 Wiley Periodicals, Inc.

Use of a Colony of Cooperating Agents and MAPLE To Solve the Traveling Salesman Problem.

ERIC Educational Resources Information Center

Guerrieri, Bruno

This paper reviews an approach for finding optimal solutions to the traveling salesman problem, a well-known problem in combinational optimization, and describes implementing the approach using the MAPLE computer algebra system. The method employed in this approach to the problem is similar to the way ant colonies manage to establish shortest…

An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

NASA Astrophysics Data System (ADS)

Ramadhani, T.; Hertono, G. F.; Handari, B. D.

2017-07-01

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

Termites: a Retinex implementation based on a colony of agents

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Audino, Giuseppe; Farup, Ivar; Rizzi, Alessandro

2012-01-01

This paper describes a novel implementation of the Retinex algorithm with the exploration of the image done by an ant swarm. In this case the purpose of the ant colony is not the optimization of some constraints but is an alternative way to explore the image content as diffused as possible, with the possibility of tuning the exploration parameters to the image content trying to better approach the Human Visual System behavior. For this reason, we used "termites", instead of ants, to underline the idea of the eager exploration of the image. The paper presents the spatial characteristics of locality and discusses differences in path exploration with other Retinex implementations. Furthermore a psychophysical experiment has been carried out on eight images with 20 observers and results indicate that a termite swarm should investigate a particular region of an image to find the local reference white.

antaRNA: ant colony-based RNA sequence design.

PubMed

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

PubMed Central

Zhu, Xiaoning

2014-01-01

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. PMID:25538768

Optimal management of substrates in anaerobic co-digestion: An ant colony algorithm approach.

PubMed

Verdaguer, Marta; Molinos-Senante, María; Poch, Manel

2016-04-01

Sewage sludge (SWS) is inevitably produced in urban wastewater treatment plants (WWTPs). The treatment of SWS on site at small WWTPs is not economical; therefore, the SWS is typically transported to an alternative SWS treatment center. There is increased interest in the use of anaerobic digestion (AnD) with co-digestion as an SWS treatment alternative. Although the availability of different co-substrates has been ignored in most of the previous studies, it is an essential issue for the optimization of AnD co-digestion. In a pioneering approach, this paper applies an Ant-Colony-Optimization (ACO) algorithm that maximizes the generation of biogas through AnD co-digestion in order to optimize the discharge of organic waste from different waste sources in real-time. An empirical application is developed based on a virtual case study that involves organic waste from urban WWTPs and agrifood activities. The results illustrate the dominate role of toxicity levels in selecting contributions to the AnD input. The methodology and case study proposed in this paper demonstrate the usefulness of the ACO approach in supporting a decision process that contributes to improving the sustainability of organic waste and SWS management. Copyright © 2016 Elsevier Ltd. All rights reserved.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2012-01-01

In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

The approach for shortest paths in fire succor based on component GIS technology

NASA Astrophysics Data System (ADS)

Han, Jie; Zhao, Yong; Dai, K. W.

2007-06-01

Fire safety is an important issue for the national economy and people's living. Efficiency and exactness of fire department succor directly relate to safety of peoples' lives and property. Many disadvantages of the traditional fire system have been emerged in practical applications. The preparation of pumpers is guided by wireless communication or wire communication, so its real-time and accurate performances are much poorer. The information about the reported fire, such as the position, disaster and map, et al., for alarm and command was processed by persons, which slows the reaction speed and delays the combat opportunity. In order to solve these disadvantages, it has an important role to construct a modern fire command center based on high technology. The construction of modern fire command center can realize the modernization and automation of fire command and management. It will play a great role in protecting safety of peoples' lives and property. The center can enhance battle ability and can reduce the direct and indirect loss of fire damage at most. With the development of science technology, Geographic Information System (GIS) has becoming a new information industry for hardware production, software development, data collection, space analysis and counseling. With the popularization of computers and the development of GIS, GIS has gained increasing broad applications for its strong functionality. Network analysis is one of the most important functions of GIS, and the most elementary and pivotal issue of network analysis is the calculation of shortest paths. The shortest paths are mostly applied to some emergent systems such as 119 fire alarms. These systems mainly require that the computation time of the optimal path should be 1-3 seconds. And during traveling, the next running path of the vehicles should be calculated in time. So the implement of the shortest paths must have a high efficiency. In this paper, the component GIS technology was applied to collect and record the data information (such as, the situation of this disaster, map and road status et al) of the reported fire firstly. The ant colony optimization was used to calculate the shortest path of fire succor secondly. The optimization results were sent to the pumpers, which can let pumpers choose the shortest paths intelligently and come to fire position with least time. The programming method for shortest paths is proposed in section 3. There are three parts in this section. The elementary framework of the proposed programming method is presented in part one. The systematic framework of GIS component is described in part two. The ant colony optimization employed is presented in part three. In section 4, a simple application instance was presented to demonstrate the proposed programming method. There are three parts in this section. The distributed Web application based on component GIS was described in part one. The optimization results without traffic constraint were presented in part two. The optimization results with traffic constraint were presented in part three. The contributions of this paper can be summarized as follows. (1) It proposed an effective approach for shortest paths in fire succor based on component GIS technology. This proposed approach can achieve the real-time decisions of shortest paths for fire succor. (2) It applied the ant colony optimization to implement the shortest path decision. The traffic information was considered in the shortest path decision using ant colony optimization. The final application instance suggests that the proposed approach is feasible, correct and valid.

Intelligent Method for Diagnosing Structural Faults of Rotating Machinery Using Ant Colony Optimization

PubMed Central

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called “relative ratio symptom parameters” are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

PubMed

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

NASA Astrophysics Data System (ADS)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

NASA Astrophysics Data System (ADS)

Szemis, J. M.; Maier, H. R.; Dandy, G. C.

2012-08-01

Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.

Plant defense, herbivory, and the growth of Cordia alliodora trees and their symbiotic Azteca ant colonies.

PubMed

Pringle, Elizabeth G; Dirzo, Rodolfo; Gordon, Deborah M

2012-11-01

The effects of herbivory on plant fitness are integrated over a plant's lifetime, mediated by ontogenetic changes in plant defense, tolerance, and herbivore pressure. In symbiotic ant-plant mutualisms, plants provide nesting space and food for ants, and ants defend plants against herbivores. The benefit to the plant of sustaining the growth of symbiotic ant colonies depends on whether defense by the growing ant colony outpaces the plant's growth in defendable area and associated herbivore pressure. These relationships were investigated in the symbiotic mutualism between Cordia alliodora trees and Azteca pittieri ants in a Mexican tropical dry forest. As ant colonies grew, worker production remained constant relative to ant-colony size. As trees grew, leaf production increased relative to tree size. Moreover, larger trees hosted lower densities of ants, suggesting that ant-colony growth did not keep pace with tree growth. On leaves with ants experimentally excluded, herbivory per unit leaf area increased exponentially with tree size, indicating that larger trees experienced higher herbivore pressure per leaf area than smaller trees. Even with ant defense, herbivory increased with tree size. Therefore, although larger trees had larger ant colonies, ant density was lower in larger trees, and the ant colonies did not provide sufficient defense to compensate for the higher herbivore pressure in larger trees. These results suggest that in this system the tree can decrease herbivory by promoting ant-colony growth, i.e., sustaining space and food investment in ants, as long as the tree continues to grow.

Concepts and applications of "natural computing" techniques in de novo drug and peptide design.

PubMed

Hiss, Jan A; Hartenfeller, Markus; Schneider, Gisbert

2010-05-01

Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.

Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks

NASA Astrophysics Data System (ADS)

Ji, Junzhong; Song, Xiangjing; Liu, Chunnian; Zhang, Xiuzhen

2013-08-01

Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2018-03-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

A pheromone-rate-based analysis on the convergence time of ACO algorithm.

PubMed

Huang, Han; Wu, Chun-Guo; Hao, Zhi-Feng

2009-08-01

Ant colony optimization (ACO) has widely been applied to solve combinatorial optimization problems in recent years. There are few studies, however, on its convergence time, which reflects how many iteration times ACO algorithms spend in converging to the optimal solution. Based on the absorbing Markov chain model, we analyze the ACO convergence time in this paper. First, we present a general result for the estimation of convergence time to reveal the relationship between convergence time and pheromone rate. This general result is then extended to a two-step analysis of the convergence time, which includes the following: 1) the iteration time that the pheromone rate spends on reaching the objective value and 2) the convergence time that is calculated with the objective pheromone rate in expectation. Furthermore, four brief ACO algorithms are investigated by using the proposed theoretical results as case studies. Finally, the conclusions of the case studies that the pheromone rate and its deviation determine the expected convergence time are numerically verified with the experiment results of four one-ant ACO algorithms and four ten-ant ACO algorithms.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2017-12-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

NASA Astrophysics Data System (ADS)

Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

2016-10-01

Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique

NASA Astrophysics Data System (ADS)

Pal, Siddharth; Basak, Aniruddha; Das, Swagatam

In many manufacturing areas the detection of surface defects is one of the most important processes in quality control. Currently in order to detect small scratches on solid surfaces most of the industries working on material manufacturing rely on visual inspection primarily. In this article we propose a hybrid computational intelligence technique to automatically detect a linear scratch from a solid surface and estimate its length (in pixel unit) simultaneously. The approach is based on a swarm intelligence algorithm called Ant Colony Optimization (ACO) and image preprocessing with Wiener and Sobel filters as well as the Canny edge detector. The ACO algorithm is mostly used to compensate for the broken parts of the scratch. Our experimental results confirm that the proposed technique can be used for detecting scratches from noisy and degraded images, even when it is very difficult for conventional image processing to distinguish the scratch area from its background.

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

PubMed

Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Inverse estimation of the spheroidal particle size distribution using Ant Colony Optimization algorithms in multispectral extinction technique

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Wang, Yuqing; Ruan, Liming

2014-10-01

Four improved Ant Colony Optimization (ACO) algorithms, i.e. the probability density function based ACO (PDF-ACO) algorithm, the Region ACO (RACO) algorithm, Stochastic ACO (SACO) algorithm and Homogeneous ACO (HACO) algorithm, are employed to estimate the particle size distribution (PSD) of the spheroidal particles. The direct problems are solved by the extended Anomalous Diffraction Approximation (ADA) and the Lambert-Beer law. Three commonly used monomodal distribution functions i.e. the Rosin-Rammer (R-R) distribution function, the normal (N-N) distribution function, and the logarithmic normal (L-N) distribution function are estimated under dependent model. The influence of random measurement errors on the inverse results is also investigated. All the results reveal that the PDF-ACO algorithm is more accurate than the other three ACO algorithms and can be used as an effective technique to investigate the PSD of the spheroidal particles. Furthermore, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution functions to retrieve the PSD of spheroidal particles using PDF-ACO algorithm. The investigation shows a reasonable agreement between the original distribution function and the general distribution function when only considering the variety of the length of the rotational semi-axis.

Ant Colony Optimization for Mapping, Scheduling and Placing in Reconfigurable Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferrandi, Fabrizio; Lanzi, Pier Luca; Pilato, Christian

Modern heterogeneous embedded platforms, com- posed of several digital signal, application specific and general purpose processors, also include reconfigurable devices support- ing partial dynamic reconfiguration. These devices can change the behavior of some of their parts during execution, allowing hardware acceleration of more sections of the applications. Never- theless, partial dynamic reconfiguration imposes severe overheads in terms of latency. For such systems, a critical part of the design phase is deciding on which processing elements (mapping) and when (scheduling) executing a task, but also how to place them on the reconfigurable device to guarantee the most efficient reuse of themore » programmable logic. In this paper we propose an algorithm based on Ant Colony Optimization (ACO) that simultaneously executes the scheduling, the mapping and the linear placing of tasks, hiding reconfiguration overheads through prefetching. Our heuristic gradually constructs solutions and then searches around the best ones, cutting out non-promising areas of the design space. We show how to consider the partial dynamic reconfiguration constraints in the scheduling, placing and mapping problems and compare our formulation to other heuristics that address the same problems. We demonstrate that our proposal is more general and robust, and finds better solutions (16.5% in average) with respect to competing solutions.« less

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

NASA Astrophysics Data System (ADS)

Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

2010-10-01

To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Usefulness of fire ant genetics in insecticide efficacy trials

USDA-ARS?s Scientific Manuscript database

Mature fire ant colonies contain an average of 80,000 worker ants. For this study, eight fire ant workers were randomly sampled from each colony. DNA fingerprints for each individual ant were generated using 21 simple sequence repeats (SSR) markers that were developed from fire ant DNA by other lab...

Software Piracy Detection Model Using Ant Colony Optimization Algorithm

NASA Astrophysics Data System (ADS)

Astiqah Omar, Nor; Zakuan, Zeti Zuryani Mohd; Saian, Rizauddin

2017-06-01

Internet enables information to be accessible anytime and anywhere. This scenario creates an environment whereby information can be easily copied. Easy access to the internet is one of the factors which contribute towards piracy in Malaysia as well as the rest of the world. According to a survey conducted by Compliance Gap BSA Global Software Survey in 2013 on software piracy, found out that 43 percent of the software installed on PCs around the world was not properly licensed, the commercial value of the unlicensed installations worldwide was reported to be 62.7 billion. Piracy can happen anywhere including universities. Malaysia as well as other countries in the world is faced with issues of piracy committed by the students in universities. Piracy in universities concern about acts of stealing intellectual property. It can be in the form of software piracy, music piracy, movies piracy and piracy of intellectual materials such as books, articles and journals. This scenario affected the owner of intellectual property as their property is in jeopardy. This study has developed a classification model for detecting software piracy. The model was developed using a swarm intelligence algorithm called the Ant Colony Optimization algorithm. The data for training was collected by a study conducted in Universiti Teknologi MARA (Perlis). Experimental results show that the model detection accuracy rate is better as compared to J48 algorithm.

The interplay between scent trails and group-mass recruitment systems in ants.

PubMed

Planqué, Robert; van den Berg, Jan Bouwe; Franks, Nigel R

2013-10-01

Large ant colonies invariably use effective scent trails to guide copious ant numbers to food sources. The success of mass recruitment hinges on the involvement of many colony members to lay powerful trails. However, many ant colonies start off as single queens. How do these same colonies forage efficiently when small, thereby overcoming the hurdles to grow large? In this paper, we study the case of combined group and mass recruitment displayed by some ant species. Using mathematical models, we explore to what extent early group recruitment may aid deployment of scent trails, making such trails available at much smaller colony sizes. We show that a competition between group and mass recruitment may cause oscillatory behaviour mediated by scent trails. This results in a further reduction of colony size to establish trails successfully.

Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization.

PubMed

Odili, Julius Beneoluchi; Mohmad Kahar, Mohd Nizam; Noraziah, A

2017-01-01

In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

An ants-eye view of an ant-plant protection mutualism

PubMed Central

Lanan, M. C.; Bronstein, J. L.

2013-01-01

Ant protection of extrafloral nectar-secreting plants (EFN plants) is a common form of mutualism found in most habitats around the world. However, very few studies have considered these mutualisms from the ant, rather than the plant, perspective. In particular, a whole-colony perspective that takes into account the spatial structure and nest arrangement of the ant colonies that visit these plants has been lacking, obscuring when and how colony-level foraging decisions might affect tending rates on individual plants. Here, we experimentally demonstrate that recruitment of Crematogaster opuntiae (Buren) ant workers to the extrafloral nectar-secreting cactus Ferocactus wislizeni (Englem) is not independent between plants up to 5m apart. Colony territories of C. opuntiae are large, covering areas of up to 5000m2, and workers visit between five and thirty-four extrafloral nectar-secreting barrel cacti within the territories. These ants are highly polydomous, with up to twenty nest entrances dispersed throughout the territory and interconnected by trail networks. Our study demonstrates that worker recruitment is not independent within large polydomous ant colonies, highlighting the importance of considering colonies rather than individual workers as the relevant study unit within ant/plant protection mutualisms PMID:23515612

A new method for distinguishing colony social forms of the fire ant Solenopsis invicta

USDA-ARS?s Scientific Manuscript database

Two distinct forms of colony social organization occur in the fire ant Solenopsis invicta: Colonies of the monogyne social form are headed by a single egg-laying queen, whereas those of the polygyne social form contain multiple egg-laying queens. This major difference in social organization is ass...

Product Mix Selection Using AN Evolutionary Technique

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Vasant, Pandian

2009-08-01

This paper proposes an evolutionary technique for the solution of a real—life industrial problem and particular for the product mix selection problem. The evolutionary technique is a combination of a genetic algorithm that preserves the feasibility of the trial solutions with penalties and some local optimization method. The goal of this paper has been achieved in finding the best near optimal solution for the profit fitness function respect to vagueness factor and level of satisfaction. The findings of the profit values will be very useful for the decision makers in the industrial engineering sector for the implementation purpose. It's possible to improve the solutions obtained in this study by employing other meta-heuristic methods such as simulated annealing, tabu Search, ant colony optimization, particle swarm optimization and artificial immune systems.

Sociogenomics of cooperation and conflict during colony foundation in the fire ant Solenopsis invicta

USDA-ARS?s Scientific Manuscript database

The genomic state of an individual results from the interplay between its internal condition and the external environment, which may include the social environment. The link between genes and social environment is clearly visible during the process of colony founding in the fire ant Solenopsis invic...

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

PubMed

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

Optimization on Paddy Crops in Central Java (with Solver, SVD on Least Square and ACO (Ant Colony Algorithm))

NASA Astrophysics Data System (ADS)

Parhusip, H. A.; Trihandaru, S.; Susanto, B.; Prasetyo, S. Y. J.; Agus, Y. H.; Simanjuntak, B. H.

2017-03-01

Several algorithms and objective functions on paddy crops have been studied to get optimal paddy crops in Central Java based on the data given from Surakarta and Boyolali. The algorithms are linear solver, least square and Ant Colony Algorithms (ACO) to develop optimization procedures on paddy crops modelled with Modified GSTAR (Generalized Space-Time Autoregressive) and nonlinear models where the nonlinear models are quadratic and power functions. The studied data contain paddy crops from Surakarta and Boyolali determining the best period of planting in the year 1992-2012 for Surakarta where 3 periods for planting are known and the optimal amount of paddy crops in Boyolali in the year 2008-2013. Having these analyses may guide the local agriculture government to give a decision on rice sustainability in its region. The best period for planting in Surakarta is observed, i.e. the best period is in September-December based on the data 1992-2012 by considering the planting area, the cropping area, and the paddy crops are the most important factors to be taken into account. As a result, we can refer the paddy crops in this best period (about 60.4 thousand tons per year) as the optimal results in 1992-2012 where the used objective function is quadratic. According to the research, the optimal paddy crops in Boyolali about 280 thousand tons per year where the studied factors are the amount of rainfalls, the harvested area and the paddy crops in 2008-2013. In this case, linear and power functions are studied to be the objective functions. Compared to all studied algorithms, the linear solver is still recommended to be an optimization tool for a local agriculture government to predict paddy crops in future.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

External immunity in ant societies: sociality and colony size do not predict investment in antimicrobials

PubMed Central

Halawani, Omar; Pearson, Bria; Mathews, Stephanie; López-Uribe, Margarita M.; Dunn, Robert R.; Smith, Adrian A.

2018-01-01

Social insects live in dense groups with a high probability of disease transmission and have therefore faced strong pressures to develop defences against pathogens. For this reason, social insects have been hypothesized to invest in antimicrobial secretions as a mechanism of external immunity to prevent the spread of disease. However, empirical studies linking the evolution of sociality with increased investment in antimicrobials have been relatively few. Here we quantify the strength of antimicrobial secretions among 20 ant species that cover a broad spectrum of ant diversity and colony sizes. We extracted external compounds from ant workers to test whether they inhibited the growth of the bacterium Staphylococcus epidermidis. Because all ant species are highly social, we predicted that all species would exhibit some antimicrobial activity and that species that form the largest colonies would exhibit the strongest antimicrobial response. Our comparative approach revealed that strong surface antimicrobials are common to particular ant clades, but 40% of species exhibited no antimicrobial activity at all. We also found no correlation between antimicrobial activity and colony size. Rather than relying on antimicrobial secretions as external immunity to control pathogen spread, many ant species have probably developed alternative strategies to defend against disease pressure. PMID:29515850

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

NASA Astrophysics Data System (ADS)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

An element search ant colony technique for solving virtual machine placement problem

NASA Astrophysics Data System (ADS)

Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

2017-09-01

The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Janich, Karl W.

2005-01-01

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results.

PubMed

Otero, Fernando E B; Freitas, Alex A

2016-01-01

Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rules instead of an individual rule. In this paper we propose an extension of the cAnt-Miner[Formula: see text] algorithm to discover a set of rules (unordered rules). The main motivations for this work are to improve the interpretation of individual rules by discovering a set of rules and to evaluate the impact on the predictive accuracy of the algorithm. We also propose a new measure to evaluate the interpretability of the discovered rules to mitigate the fact that the commonly used model size measure ignores how the rules are used to make a class prediction. Comparisons with state-of-the-art rule induction algorithms, support vector machines, and the cAnt-Miner[Formula: see text] producing ordered rules are also presented.

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Distributed nestmate recognition in ants.

PubMed

Esponda, Fernando; Gordon, Deborah M

2015-05-07

We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response.

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

PubMed Central

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

Groups have a larger cognitive capacity than individuals.

PubMed

Sasaki, Takao; Pratt, Stephen C

2012-10-09

Increasing the number of options can paradoxically lead to worse decisions, a phenomenon known as cognitive overload [1]. This happens when an individual decision-maker attempts to digest information exceeding its processing capacity. Highly integrated groups, such as social insect colonies, make consensus decisions that combine the efforts of many members, suggesting that these groups can overcome individual limitations [2-4]. Here we report that an ant colony choosing a new nest site is less vulnerable to cognitive overload than an isolated ant making this decision on her own. We traced this improvement to differences in individual behavior. In whole colonies, each ant assesses only a small subset of available sites, and the colony combines their efforts to thoroughly explore all options. An isolated ant, on the other hand, must personally assess a larger number of sites to approach the same level of option coverage. By sharing the burden of assessment, the colony avoids overtaxing the abilities of its members. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique

PubMed Central

Kumarasabapathy, N.; Manoharan, P. S.

2015-01-01

This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion. PMID:26504895

A preliminary study to metaheuristic approach in multilayer radiation shielding optimization

NASA Astrophysics Data System (ADS)

Arif Sazali, Muhammad; Rashid, Nahrul Khair Alang Md; Hamzah, Khaidzir

2018-01-01

Metaheuristics are high-level algorithmic concepts that can be used to develop heuristic optimization algorithms. One of their applications is to find optimal or near optimal solutions to combinatorial optimization problems (COPs) such as scheduling, vehicle routing, and timetabling. Combinatorial optimization deals with finding optimal combinations or permutations in a given set of problem components when exhaustive search is not feasible. A radiation shield made of several layers of different materials can be regarded as a COP. The time taken to optimize the shield may be too high when several parameters are involved such as the number of materials, the thickness of layers, and the arrangement of materials. Metaheuristics can be applied to reduce the optimization time, trading guaranteed optimal solutions for near-optimal solutions in comparably short amount of time. The application of metaheuristics for radiation shield optimization is lacking. In this paper, we present a review on the suitability of using metaheuristics in multilayer shielding design, specifically the genetic algorithm and ant colony optimization algorithm (ACO). We would also like to propose an optimization model based on the ACO method.

No effect of Zn-pollution on the energy content in the black garden ant.

PubMed

Grześ, Irena M; Okrutniak, Mateusz

2016-05-01

Social insects may display a response to environmental pollution at the colony level. The key trait of an ant colony is to share energy between castes in order to maintain the existing adult population and to feed the brood. In the present study we calorimetrically measured the energy content per body mass (J/mg) of adults and pupae of workers, males and females of the black garden ant Lasius niger. The ants were sampled from 37 wild colonies originating from 19 sites located along the metal pollution gradient established in a post-mining area in Poland. The cost of metal detoxification seen as a possible reduction in energy content with increasing pollution was found neither for pupae nor adults. However, a considerable part of variance in energy content is explained by belonging to the same colony. These findings stress the importance of colony-specific factors and/or the interaction of these factors with specific site in shaping the response of ants to metal-pollution stress. Colony-related factors may constrain possible selfish decisions of workers over energy allocation in workers and sexual castes.

Colony size and brood investment of Myrmica rubra ant colonies in habitats invaded by goldenrods.

PubMed

Grześ, I M; Ślipiński, P; Babik, H; Moroń, D; Walter, B; Trigos Peral, G; Maak, I; Witek, M

2018-01-01

Ant richness and abundance are negatively affected by the invasion of alien goldenrods ( Solidago sp.). However, little is known about the mechanisms standing behind the impact of the invaders on ant life history, such as colony investments in growth and reproduction. We examined this problem of the investments of Myrmica rubra ant colonies living in different grasslands invaded and non-invaded by goldenrods. Altogether, 47 colonies were analysed; and for each colony, we calculated the number of queens, workers and the production of young workers, gynes, and males. We found that colonies from invaded meadows are smaller in size, but have a similar number of adult queens compared to colonies from non-invaded sites. We also found different brood investments among colonies from invaded and non-invaded meadows-colonies from non-invaded meadows produce more young workers and invest more in growth, whereas colonies from invaded meadows invest more in reproduction through higher gyne production. Male production was at a similar level in colonies from both habitat types. The observed patterns may be explained by the effect of various environmental factors occurring in both grassland types, such as stress in changed habitats, higher competition among gynes in non-invaded grasslands, or finally, by the adaptive colony-level response of ants to stress. The higher production of gynes observed in the invaded grasslands may support dispersal and enhance the probability of establishing a colony in a more favourable location.

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

Toxicity Profiles and Colony Effects of Liquid Baits on Tawny Crazy Ants (plus an update on their U.S. distribution)

USDA-ARS?s Scientific Manuscript database

Tawny crazy ants, Nylanderia fulva, is an invasive ant that are known to readily forage on the liquid, carbohydrate rich honeydew produced by hemipterans such as aphids and scales. There is interest in developing liquid ant baits that can eliminate tawny crazy ant colonies. Preliminary and anecdot...

Effect of density on traffic and velocity on trunk trails of Formica pratensis.

PubMed

Hönicke, C; Bliss, P; Moritz, R F A

2015-04-01

The allocation of large numbers of workers facilitates the swift intake of locally available resources which is essential for ant colony survival. To organise the traffic between nest and food source, the black-meadow ant Formica pratensis establishes permanent trunk trails, which are maintained by the ants. To unravel the ant organisation and potential traffic rules on these trails, we analysed velocity and lane segregation under various densities by experimentally changing feeding regimes. Even under the highest ant densities achieved, we never observed any traffic jams. On the contrary, velocity increased after supplementary feeding despite an enhanced density. Furthermore, inbound ants returning to the nest had a higher velocity than those leaving the colony. Whilst at low and medium density the ants used the centre of the trail, they used the full width of the trail at high density. Outbound ants also showed some degree of lane segregation which contributes to traffic organisation.

Ant colony optimization algorithm for interpretable Bayesian classifiers combination: application to medical predictions.

PubMed

Bouktif, Salah; Hanna, Eileen Marie; Zaki, Nazar; Abu Khousa, Eman

2014-01-01

Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models' interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm.

Internest food sharing within wood ant colonies: resource redistribution behavior in a complex system

PubMed Central

Robinson, Elva J.H.

2016-01-01

Resource sharing is an important cooperative behavior in many animals. Sharing resources is particularly important in social insect societies, as division of labor often results in most individuals including, importantly, the reproductives, relying on other members of the colony to provide resources. Sharing resources between individuals is therefore fundamental to the success of social insects. Resource sharing is complicated if a colony inhabits several spatially separated nests, a nesting strategy common in many ant species. Resources must be shared not only between individuals in a single nest but also between nests. We investigated the behaviors facilitating resource redistribution between nests in a dispersed-nesting population of wood ant Formica lugubris. We marked ants, in the field, as they transported resources along the trails between nests of a colony, to investigate how the behavior of individual workers relates to colony-level resource exchange. We found that workers from a particular nest “forage” to other nests in the colony, treating them as food sources. Workers treating other nests as food sources means that simple, pre-existing foraging behaviors are used to move resources through a distributed system. It may be that this simple behavioral mechanism facilitates the evolution of this complex life-history strategy. PMID:27004016

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

Sampling efficacy for the red imported fire ant Solenopsis invicta (Hymenoptera: Formicidae).

PubMed

Stringer, Lloyd D; Suckling, David Maxwell; Baird, David; Vander Meer, Robert K; Christian, Sheree J; Lester, Philip J

2011-10-01

Cost-effective detection of invasive ant colonies before establishment in new ranges is imperative for the protection of national borders and reducing their global impact. We examined the sampling efficiency of food-baits and pitfall traps (baited and nonbaited) in detecting isolated red imported fire ant (Solenopsis invicta Buren) nests in multiple environments in Gainesville, FL. Fire ants demonstrated a significantly higher preference for a mixed protein food type (hotdog or ground meat combined with sweet peanut butter) than for the sugar or water baits offered. Foraging distance success was a function of colony size, detection trap used, and surveillance duration. Colony gyne number did not influence detection success. Workers from small nests (0- to 15-cm mound diameter) traveled no >3 m to a food source, whereas large colonies (>30-cm mound diameter) traveled up to 17 m. Baited pitfall traps performed best at detecting incipient ant colonies followed by nonbaited pitfall traps then food baits, whereas food baits performed well when trying to detect large colonies. These results were used to create an interactive model in Microsoft Excel, whereby surveillance managers can alter trap type, density, and duration parameters to estimate the probability of detecting specified or unknown S. invicta colony sizes. This model will support decision makers who need to balance the sampling cost and risk of failure to detect fire ant colonies.

Microbial community structure of leaf-cutter ant fungus gardens and refuse dumps.

PubMed

Scott, Jarrod J; Budsberg, Kevin J; Suen, Garret; Wixon, Devin L; Balser, Teri C; Currie, Cameron R

2010-03-29

Leaf-cutter ants use fresh plant material to grow a mutualistic fungus that serves as the ants' primary food source. Within fungus gardens, various plant compounds are metabolized and transformed into nutrients suitable for ant consumption. This symbiotic association produces a large amount of refuse consisting primarily of partly degraded plant material. A leaf-cutter ant colony is thus divided into two spatially and chemically distinct environments that together represent a plant biomass degradation gradient. Little is known about the microbial community structure in gardens and dumps or variation between lab and field colonies. Using microbial membrane lipid analysis and a variety of community metrics, we assessed and compared the microbiota of fungus gardens and refuse dumps from both laboratory-maintained and field-collected colonies. We found that gardens contained a diverse and consistent community of microbes, dominated by Gram-negative bacteria, particularly gamma-Proteobacteria and Bacteroidetes. These findings were consistent across lab and field gardens, as well as host ant taxa. In contrast, dumps were enriched for Gram-positive and anaerobic bacteria. Broad-scale clustering analyses revealed that community relatedness between samples reflected system component (gardens/dumps) rather than colony source (lab/field). At finer scales samples clustered according to colony source. Here we report the first comparative analysis of the microbiota from leaf-cutter ant colonies. Our work reveals the presence of two distinct communities: one in the fungus garden and the other in the refuse dump. Though we find some effect of colony source on community structure, our data indicate the presence of consistently associated microbes within gardens and dumps. Substrate composition and system component appear to be the most important factor in structuring the microbial communities. These results thus suggest that resident communities are shaped by the plant degradation gradient created by ant behavior, specifically their fungiculture and waste management.

Ecological consequences of colony structure in dynamic ant nest networks.

PubMed

Ellis, Samuel; Franks, Daniel W; Robinson, Elva J H

2017-02-01

Access to resources depends on an individual's position within the environment. This is particularly important to animals that invest heavily in nest construction, such as social insects. Many ant species have a polydomous nesting strategy: a single colony inhabits several spatially separated nests, often exchanging resources between the nests. Different nests in a polydomous colony potentially have differential access to resources, but the ecological consequences of this are unclear. In this study, we investigate how nest survival and budding in polydomous wood ant ( Formica lugubris ) colonies are affected by being part of a multi-nest system. Using field data and novel analytical approaches combining survival models with dynamic network analysis, we show that the survival and budding of nests within a polydomous colony are affected by their position in the nest network structure. Specifically, we find that the flow of resources through a nest, which is based on its position within the wider nest network, determines a nest's likelihood of surviving and of founding new nests. Our results highlight how apparently disparate entities in a biological system can be integrated into a functional ecological unit. We also demonstrate how position within a dynamic network structure can have important ecological consequences.

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

Colony size as a buffer against seasonality: Bergmann's rule in social insects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaspari, M.; Vargo, E.

1994-06-01

In eusocial species, the size of the superorganism is the summed sizes of its component individuals. Bergmann's rule, the cline of decreasing size with decreasing latitude, applies to colony size in ants. Using data from the literature and our own collections, we show that colony sizes of tropical ant species are on average 1/10th the size of temperate species. The patterns holds for 5 of 6 subfamilies and 15 of 16 genera tested. What causes this trend Larger colonies of the fire ant, Solenopsis invicta, are better able to protect the queen (the colony's reproductive tissue) against food shortage, likelymore » by sacrificing workers (it's somatic tissue). Days of queen survival follows the allometry M[sup 0.25]. We propose that the shorter growing seasons in temperate latitudes cull small-colony species through over-wintering starvation.« less

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

PubMed

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

Long-Term Disease Dynamics for a Specialized Parasite of Ant Societies: A Field Study

PubMed Central

Loreto, Raquel G.; Elliot, Simon L.; Freitas, Mayara L. R.; Pereira, Thairine M.; Hughes, David P.

2014-01-01

Many studies have investigated how social insects behave when a parasite is introduced into their colonies. These studies have been conducted in the laboratory, and we still have a limited understanding of the dynamics of ant-parasite interactions under natural conditions. Here we consider a specialized parasite of ant societies (Ophiocordyceps camponoti-rufipedis infecting Camponotus rufipes) within a rainforest. We first established that the parasite is unable to develop to transmission stage when introduced within the host nest. Secondly, we surveyed all colonies in the studied area and recorded 100% prevalence at the colony level (all colonies were infected). Finally, we conducted a long-term detailed census of parasite pressure, by mapping the position of infected dead ants and foraging trails (future hosts) in the immediate vicinity of the colonies over 20 months. We report new dead infected ants for all the months we conducted the census – at an average of 14.5 cadavers/month/colony. Based on the low infection rate, the absence of colony collapse or complete recovery of the colonies, we suggest that this parasite represents a chronic infection in the ant societies. We also proposed a “terminal host model of transmission” that links the age-related polyethism to the persistence of a parasitic infection. PMID:25133749

A solution quality assessment method for swarm intelligence optimization algorithms.

PubMed

Zhang, Zhaojun; Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua

2014-01-01

Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of "value performance," the "ordinal performance" is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and "good enough" set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

PubMed Central

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts. PMID:26357510

Opportunistic brood theft in the context of colony relocation in an Indian queenless ant

PubMed Central

Paul, Bishwarup; Paul, Manabi; Annagiri, Sumana

2016-01-01

Brood is a very valuable part of an ant colony and behaviours increasing its number with minimum investment is expected to be favoured by natural selection. Brood theft has been well documented in ants belonging to the subfamilies Myrmicinae and Formicinae. In this study we report opportunistic brood theft in the context of nest relocation in Diacamma indicum, belonging to the primitively eusocial subfamily Ponerinae. Pupae was the preferred stolen item both in laboratory conditions and in natural habitat and a small percentage of the members of a colony acting as thieves stole about 12% of the brood of the victim colony. Stolen brood were not consumed but became slaves. We propose a new dimension to the risks of relocation in the form of brood theft by conspecific neighbours and speculate that examination of this phenomenon in other primitively eusocial species will help understand the origin of brood theft in ants. PMID:27796350

Ant colony optimisation inversion of surface and borehole magnetic data under lithological constraints

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou; Xi, Yufei; Cai, Jianchao; Zhang, Henglei

2015-01-01

The ant colony optimisation algorithm has successfully been used to invert for surface magnetic data. However, the resolution of the distributions of the recovered physical property for deeply buried magnetic sources is not generally very high because of geophysical ambiguities. We use three approaches to deal with this problem. First, the observed surface magnetic data are taken together with the three-component borehole magnetic anomalies to recover the distributions of the physical properties. This cooperative inversion strategy improves the resolution of the inversion results in the vertical direction. Additionally, as the ant colony tours the discrete nodes, we force it to visit the nodes with physical properties that agree with the drilled lithologies. These lithological constraints reduce the non-uniqueness of the inversion problem. Finally, we also implement a K-means cluster analysis for the distributions of the magnetic cells after each iteration, in order to separate the distributions of magnetisation intensity instead of concentrating the distribution in a single area. We tested our method using synthetic data and found that all tests returned favourable results. In the case study of the Mengku iron-ore deposit in northwest China, the recovered distributions of magnetisation are in good agreement with the locations and shapes of the magnetite orebodies as inferred by drillholes. Uncertainty analysis shows that the ant colony algorithm is robust in the presence of noise and that the proposed approaches significantly improve the quality of the inversion results.

Trail pheromone disruption of red imported fire ant.

PubMed

Suckling, David M; Stringer, Lloyd D; Bunn, Barry; El-Sayed, Ashraf M; Vander Meer, Robert K

2010-07-01

The fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is considered one of the most aggressive and invasive species in the world. Toxic bait systems are used widely for control, but they also affect non-target ant species and cannot be used in sensitive ecosystems such as organic farms and national parks. The fire ant uses recruitment pheromones to organize the retrieval of large food resources back to the colony, with Z,E-alpha-farnesene responsible for the orientation of workers along trails. We prepared Z,E-alpha-farnesene, (91% purity) from extracted E,E-alpha-farnesene and demonstrated disruption of worker trail orientation after presentation of an oversupply of this compound from filter paper point sources (30 microg). Trails were established between queen-right colony cells and food sources in plastic tubs. Trail-following behavior was recorded by overhead webcam, and ants were digitized before and after presentation of the treatment, using two software approaches. The linear regression statistic, r(2) was calculated. Ants initially showed high linear trail integrity (r(2) = 0.75). Within seconds of presentation of the Z,E-alpha-farnesene treatment, the trailing ants showed little or no further evidence of trail following behavior in the vicinity of the pheromone source. These results show that trailing fire ants become disorientated in the presence of large amounts of Z,E-alpha-farnesene. Disrupting fire ant recruitment to resources may have a negative effect on colony size or other effects yet to be determined. This phenomenon was demonstrated recently for the Argentine ant, where trails were disrupted for two weeks by using their formulated trail pheromone, Z-9-hexadecenal. Further research is needed to establish the long term effects and control potential for trail disruption in S. invicta.

Arboreal ant colonies as 'hot-points' of cryptic diversity for myrmecophiles: the weaver ant Camponotus sp. aff. textor and its interaction network with its associates.

PubMed

Pérez-Lachaud, Gabriela; Lachaud, Jean-Paul

2014-01-01

Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biodiversity. We investigated the invertebrate diversity associated with an undescribed, but already threatened, Neotropical Camponotus weaver ant. As most of the common sampling methods used in studies of ant diversity are not suited for evaluating myrmecophile diversity within ant nests, we evaluated the macrofauna within ant nests through exhaustive colony sampling of three nests and examination of more than 80,000 individuals. We identified invertebrates from three classes belonging to 18 taxa, some of which were new to science, and recorded the first instance of the co-occurrence of two brood parasitoid wasp families attacking the same ant host colony. This diversity of ant associates corresponded to a highly complex interaction network. Agonistic interactions prevailed, but the prevalence of myrmecophiles was remarkably low. Our data support the hypothesis of the evolution of low virulence in a variety of symbionts associated with large insect societies. Because most myrmecophiles found in this work are rare, strictly specific, and exhibit highly specialized biology, the risk of extinction for these hitherto unknown invertebrates and their natural enemies is high. The cryptic, far unappreciated diversity within arboreal ant nests in areas at high risk of habitat loss qualifies these nests as 'hot-points' of biodiversity that urgently require special attention as a component of conservation and management programs.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Chemically armed mercenary ants protect fungus-farming societies.

PubMed

Adams, Rachelle M M; Liberti, Joanito; Illum, Anders A; Jones, Tappey H; Nash, David R; Boomsma, Jacobus J

2013-09-24

The ants are extraordinary in having evolved many lineages that exploit closely related ant societies as social parasites, but social parasitism by distantly related ants is rare. Here we document the interaction dynamics among a Sericomyrmex fungus-growing ant host, a permanently associated parasitic guest ant of the genus Megalomyrmex, and a raiding agro-predator of the genus Gnamptogenys. We show experimentally that the guest ants protect their host colonies against agro-predator raids using alkaloid venom that is much more potent than the biting defenses of the host ants. Relatively few guest ants are sufficient to kill raiders that invariably exterminate host nests without a cohabiting guest ant colony. We also show that the odor of guest ants discourages raider scouts from recruiting nestmates to host colonies. Our results imply that Sericomyrmex fungus-growers obtain a net benefit from their costly guest ants behaving as a functional soldier caste to meet lethal threats from agro-predator raiders. The fundamentally different life histories of the agro-predators and guest ants appear to facilitate their coexistence in a negative frequency-dependent manner. Because a guest ant colony is committed for life to a single host colony, the guests would harm their own interests by not defending the host that they continue to exploit. This conditional mutualism is analogous to chronic sickle cell anemia enhancing the resistance to malaria and to episodes in human history when mercenary city defenders offered either net benefits or imposed net costs, depending on the level of threat from invading armies.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

Colony Fusion in a Parthenogenetic Ant, Pristomyrmex punctatus

PubMed Central

Satow, Show; Satoh, Toshiyuki; Hirota, Tadao

2013-01-01

In the ant Pristomyrmex punctatus Smith (Hymenoptera: Formicidae), all young workers lay a small number of eggs parthenogenetically. Some colonies consist of monoclonal individuals that provide high inclusive fitness, according to the kin selection theory. However, in some populations, a majority of the colonies contain multiple lineages. Intracolonial genetic variation of parthenogenetic ants cannot be explained by the multiple mating of single founderesses or by the foundation of a colony by multiple foundresses, which are the usual causes of genetically diverse colonies in social insects. Here, we hypothesized that the fusion of established colonies might facilitate the formation of multiclonal colonies. Colony fusion decreases indirect benefits because of the reduction in intracolonial relatedness. However, when suitable nesting places for overwintering are scarce, colony fusion provides a strategy for the survival of colonies. Here, ants derived from different colonies were allowed to encounter one another in a container with just one nesting place. Initially, high aggression was observed; however, after several days, no aggression was observed and the ants shared the nest. When the fused colonies were allowed to transfer to two alternative nests, ants from different colonies occupied the same nest. This study highlights the importance of limiting the number of nesting places in order to understand the genetic diversity of parthenogenetic ant colonies. PMID:23895053

TACD: a transportable ant colony discrimination model for corporate bankruptcy prediction

NASA Astrophysics Data System (ADS)

Lalbakhsh, Pooia; Chen, Yi-Ping Phoebe

2017-05-01

This paper presents a transportable ant colony discrimination strategy (TACD) to predict corporate bankruptcy, a topic of vital importance that is attracting increasing interest in the field of economics. The proposed algorithm uses financial ratios to build a binary prediction model for companies with the two statuses of bankrupt and non-bankrupt. The algorithm takes advantage of an improved version of continuous ant colony optimisation (CACO) at the core, which is used to create an accurate, simple and understandable linear model for discrimination. This also enables the algorithm to work with continuous values, leading to more efficient learning and adaption by avoiding data discretisation. We conduct a comprehensive performance evaluation on three real-world data sets under a stratified cross-validation strategy. In three different scenarios, TACD is compared with 11 other bankruptcy prediction strategies. We also discuss the efficiency of the attribute selection methods used in the experiments. In addition to its simplicity and understandability, statistical significance tests prove the efficiency of TACD against the other prediction algorithms in both measures of AUC and accuracy.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

Opportunistic brood theft in the context of colony relocation in an Indian queenless ant.

PubMed

Paul, Bishwarup; Paul, Manabi; Annagiri, Sumana

2016-10-31

Brood is a very valuable part of an ant colony and behaviours increasing its number with minimum investment is expected to be favoured by natural selection. Brood theft has been well documented in ants belonging to the subfamilies Myrmicinae and Formicinae. In this study we report opportunistic brood theft in the context of nest relocation in Diacamma indicum, belonging to the primitively eusocial subfamily Ponerinae. Pupae was the preferred stolen item both in laboratory conditions and in natural habitat and a small percentage of the members of a colony acting as thieves stole about 12% of the brood of the victim colony. Stolen brood were not consumed but became slaves. We propose a new dimension to the risks of relocation in the form of brood theft by conspecific neighbours and speculate that examination of this phenomenon in other primitively eusocial species will help understand the origin of brood theft in ants.

Noise and the statistical mechanics of distributed transport in a colony of interacting agents

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Graewer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.

Inspired by the process of liquid food distribution between individuals in an ant colony, in this work we consider the statistical mechanics of resource dissemination between interacting agents with finite carrying capacity. The agents move inside a confined space (nest), pick up the food at the entrance of the nest and share it with other agents that they encounter. We calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess which strategies can lead to efficient food distribution within the nest and also to what level the observed food uptake rates and efficiency in food distribution are due to stochastic fluctuations or specific food exchange strategies by an actual ant colony.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Chemically armed mercenary ants protect fungus-farming societies

PubMed Central

Adams, Rachelle M. M.; Liberti, Joanito; Illum, Anders A.; Jones, Tappey H.; Nash, David R.; Boomsma, Jacobus J.

2013-01-01

The ants are extraordinary in having evolved many lineages that exploit closely related ant societies as social parasites, but social parasitism by distantly related ants is rare. Here we document the interaction dynamics among a Sericomyrmex fungus-growing ant host, a permanently associated parasitic guest ant of the genus Megalomyrmex, and a raiding agro-predator of the genus Gnamptogenys. We show experimentally that the guest ants protect their host colonies against agro-predator raids using alkaloid venom that is much more potent than the biting defenses of the host ants. Relatively few guest ants are sufficient to kill raiders that invariably exterminate host nests without a cohabiting guest ant colony. We also show that the odor of guest ants discourages raider scouts from recruiting nestmates to host colonies. Our results imply that Sericomyrmex fungus-growers obtain a net benefit from their costly guest ants behaving as a functional soldier caste to meet lethal threats from agro-predator raiders. The fundamentally different life histories of the agro-predators and guest ants appear to facilitate their coexistence in a negative frequency-dependent manner. Because a guest ant colony is committed for life to a single host colony, the guests would harm their own interests by not defending the host that they continue to exploit. This conditional mutualism is analogous to chronic sickle cell anemia enhancing the resistance to malaria and to episodes in human history when mercenary city defenders offered either net benefits or imposed net costs, depending on the level of threat from invading armies. PMID:24019482

Intraspecific Variation among Social Insect Colonies: Persistent Regional and Colony-Level Differences in Fire Ant Foraging Behavior

PubMed Central

Bockoven, Alison A.; Wilder, Shawn M.; Eubanks, Micky D.

2015-01-01

Individuals vary within a species in many ecologically important ways, but the causes and consequences of such variation are often poorly understood. Foraging behavior is among the most profitable and risky activities in which organisms engage and is expected to be under strong selection. Among social insects there is evidence that within-colony variation in traits such as foraging behavior can increase colony fitness, but variation between colonies and the potential consequences of such variation are poorly documented. In this study, we tested natural populations of the red imported fire ant, Solenopsis invicta, for the existence of colony and regional variation in foraging behavior and tested the persistence of this variation over time and across foraging habitats. We also reared single-lineage colonies in standardized environments to explore the contribution of colony lineage. Fire ants from natural populations exhibited significant and persistent colony and regional-level variation in foraging behaviors such as extra-nest activity, exploration, and discovery of and recruitment to resources. Moreover, colony-level variation in extra-nest activity was significantly correlated with colony growth, suggesting that this variation has fitness consequences. Lineage of the colony had a significant effect on extra-nest activity and exploratory activity and explained approximately half of the variation observed in foraging behaviors, suggesting a heritable component to colony-level variation in behavior. PMID:26197456

One-dimensional swarm algorithm packaging

NASA Astrophysics Data System (ADS)

Lebedev, Boris K.; Lebedev, Oleg B.; Lebedeva, Ekaterina O.

2018-05-01

The paper considers an algorithm for solving the problem of onedimensional packaging based on the adaptive behavior model of an ant colony. The key role in the development of the ant algorithm is the choice of representation (interpretation) of the solution. The structure of the solution search graph, the procedure for finding solutions on the graph, the methods of deposition and evaporation of pheromone are described. Unlike the canonical paradigm of an ant algorithm, an ant on the solution search graph generates sets of elements distributed across blocks. Experimental studies were conducted on IBM PC. Compared with the existing algorithms, the results are improved.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

PubMed

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

Interspecific competition between Solenopsis invicta and two native ant species, Pheidole fervens and Monomorium chinense.

PubMed

Chen, Yin-Cheng; Kafle, Lekhnath; Shih, Cheng-Jen

2011-04-01

This study was designed to understand the effects of the interspecific competition between red imported fire ant, Solenopsis invicta Buren and two native ant species, Pheidole fervens Smith and Monomorium chinense Santschi, by conducting colony interference and individual confrontation tests under laboratory conditions. The colony interference test showed that both native ant species, owing to their numerical advantage, killed the Solenopsis invicta virus-1 (SINV-1)-infected or healthy queens of S. invicta. Significantly less time was required for M. chinense to kill all SINV-1-infected S. invicta compared with the time required to kill the healthy S. invicta. Compared with healthy S. invicta, SINV-1-infected S. invicta spent a longer time eliminating the P. fervens colonies. In confrontation tests, M. chinense killed a significantly higher number of infected S. invicta minors than they did healthy minors, but the number of S. invicta majors (either infected or healthy) killed was substantially less. This study found that the viral infection weakened the competitive ability of S. invicta and made them prone to be eliminated by M. chinense but not by P. fervens.

PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm.

PubMed

Zaidman, Daniel; Wolfson, Haim J

2016-08-01

Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ([Formula: see text]) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. danielza@post.tau.ac.il; wolfson@tau.ac.il. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Ant-plant mutualism: a dietary by-product of a tropical ant's macronutrient requirements.

PubMed

Arcila Hernández, Lina M; Sanders, Jon G; Miller, Gabriel A; Ravenscraft, Alison; Frederickson, Megan E

2017-12-01

Many arboreal ants depend on myrmecophytic plants for both food and shelter; in return, these ants defend their host plants against herbivores, which are often insects. Ant-plant and other mutualisms do not necessarily involve the exchange of costly rewards or services; they may instead result from by-product benefits, or positive outcomes that do not entail a cost for one or both partners. Here, we examined whether the plant-ant Allomerus octoarticulatus pays a short-term cost to defend their host plants against herbivores, or whether plant defense is a by-product benefit of ant foraging for insect prey. Because the food offered by ant-plants is usually nitrogen-poor, arboreal ants may balance their diets by consuming insect prey or associating with microbial symbionts to acquire nitrogen, potentially shifting the costs and benefits of plant defense for the ant partner. To determine the effect of ant diet on an ant-plant mutualism, we compared the behavior, morphology, fitness, stable isotope signatures, and gaster microbiomes of A. octoarticulatus ants nesting in Cordia nodosa trees maintained for nearly a year with or without insect herbivores. At the end of the experiment, ants from herbivore exclosures preferred protein-rich baits more than ants in the control (i.e., herbivores present) treatment. Furthermore, workers in the control treatment were heavier than in the herbivore-exclusion treatment, and worker mass predicted reproductive output, suggesting that foraging for insect prey directly increased ant colony fitness. The gaster microbiome of ants was not significantly affected by the herbivore exclusion treatment. We conclude that the defensive behavior of some phytoecious ants is a by-product of their need for external protein sources; thus, the consumption of insect herbivores by ants benefits both the ant colony and the host plant. © 2017 by the Ecological Society of America.

Arboreal Ant Colonies as ‘Hot-Points’ of Cryptic Diversity for Myrmecophiles: The Weaver Ant Camponotus sp. aff. textor and Its Interaction Network with Its Associates

PubMed Central

Pérez-Lachaud, Gabriela; Lachaud, Jean-Paul

2014-01-01

Introduction Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biodiversity. Materials and Methods We investigated the invertebrate diversity associated with an undescribed, but already threatened, Neotropical Camponotus weaver ant. As most of the common sampling methods used in studies of ant diversity are not suited for evaluating myrmecophile diversity within ant nests, we evaluated the macrofauna within ant nests through exhaustive colony sampling of three nests and examination of more than 80,000 individuals. Results We identified invertebrates from three classes belonging to 18 taxa, some of which were new to science, and recorded the first instance of the co-occurrence of two brood parasitoid wasp families attacking the same ant host colony. This diversity of ant associates corresponded to a highly complex interaction network. Agonistic interactions prevailed, but the prevalence of myrmecophiles was remarkably low. Conclusions Our data support the hypothesis of the evolution of low virulence in a variety of symbionts associated with large insect societies. Because most myrmecophiles found in this work are rare, strictly specific, and exhibit highly specialized biology, the risk of extinction for these hitherto unknown invertebrates and their natural enemies is high. The cryptic, far unappreciated diversity within arboreal ant nests in areas at high risk of habitat loss qualifies these nests as ‘hot-points’ of biodiversity that urgently require special attention as a component of conservation and management programs. PMID:24941047

Application of multi-agent coordination methods to the design of space debris mitigation tours

NASA Astrophysics Data System (ADS)

Stuart, Jeffrey; Howell, Kathleen; Wilson, Roby

2016-04-01

The growth in the number of defunct and fragmented objects near to the Earth poses a growing hazard to launch operations as well as existing on-orbit assets. Numerous studies have demonstrated the positive impact of active debris mitigation campaigns upon the growth of debris populations, but comparatively fewer investigations incorporate specific mission scenarios. Furthermore, while many active mitigation methods have been proposed, certain classes of debris objects are amenable to mitigation campaigns employing chaser spacecraft with existing chemical and low-thrust propulsive technologies. This investigation incorporates an ant colony optimization routing algorithm and multi-agent coordination via auctions into a debris mitigation tour scheme suitable for preliminary mission design and analysis as well as spacecraft flight operations.

Optimal time--energy allocation and the evolution of colony demography among eusocial insects. [Polistes fuscatus, Vespa orientalis, ants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Macevicz, S.C.

1979-05-09

This thesis attempts to explain the evolution of certain features of social insect colony population structure by the use of optimization models. Two areas are examined in detail. First, the optimal reproductive strategies of annual eusocial insects are considered. A model is constructed for the growth of workers and reproductives as a function of the resources allocated to each. Next the allocation schedule is computed which yields the maximum number of reproductives by season's end. The results indicate that if there is constant return to scale for allocated resources the optimal strategy is to invest in colony growth until approximatelymore » one generation before season's end, whereupon worker production ceases and reproductive effort is switched entirely to producing queens and males. Furthermore, the results indicate that if there is decreasing return to scale for allocated resources then simultaneous production of workers and reproductives is possible. The model is used to explain the colony demography of two species of wasp, Polistes fuscatus and Vespa orientalis. Colonies of these insects undergo a sudden switch from the production of workers to the production of reproductives. The second area examined concerns optimal forager size distributions for monomorphic ant colonies. A model is constructed that describes the colony's energetic profit as a function which depends on the size distribution of food resources as well as forager efficiency, metabolic costs, and manufacturing costs.« less

Successful transmission of Solenopsis invicta virus 3 to Solenopsis invicta fire ant colonies in oil, sugar, and cricket bait formulations

USDA-ARS?s Scientific Manuscript database

Tests were conducted to evaluate whether Solenopsis invicta virus 3 (SINV-3) could be delivered in various bait formulations to fire ant colonies and measure the corresponding colony health changes associated with virus infection in Solenopsis invicta. Three bait formulations (10% sugar solution, c...

Aspectos ecologicos, toxicologicos y agricolas de la hormiga brasileña Solenopsis invicta

Treesearch

J. A. Torres

1990-01-01

The fire ant Solenopsis invicta recently invaded in Puerto Rico. Its presence has created great alarm among farmers and the public. This work reviews the ecology of this ant in the United States, Brazil and Puerto Rico in order to clarify some misconceptions. Information is provided to separate Solenopsis invicta from S. geminata. Colony foundation, caste...

PSO/ACO algorithm-based risk assessment of human neural tube defects in Heshun County, China.

PubMed

Liao, Yi Lan; Wang, Jin Feng; Wu, Ji Lei; Wang, Jiao Jiao; Zheng, Xiao Ying

2012-10-01

To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world. The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects (NTDs). A hybrid particle swarm optimization/ant colony optimization (PSO/ACO) algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes. The algorithm was easy to apply, with the accuracy of the results being 69.5%±7.02% at the 95% confidence level. The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

A survey about methods dedicated to epistasis detection.

PubMed

Niel, Clément; Sinoquet, Christine; Dina, Christian; Rocheleau, Ghislain

2015-01-01

During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated with diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks) or combinatorial optimization approaches (ant colony optimization, computational evolution system).

Ant Lion Optimization algorithm for kidney exchanges.

PubMed

Hamouda, Eslam; El-Metwally, Sara; Tarek, Mayada

2018-01-01

The kidney exchange programs bring new insights in the field of organ transplantation. They make the previously not allowed surgery of incompatible patient-donor pairs easier to be performed on a large scale. Mathematically, the kidney exchange is an optimization problem for the number of possible exchanges among the incompatible pairs in a given pool. Also, the optimization modeling should consider the expected quality-adjusted life of transplant candidates and the shortage of computational and operational hospital resources. In this article, we introduce a bio-inspired stochastic-based Ant Lion Optimization, ALO, algorithm to the kidney exchange space to maximize the number of feasible cycles and chains among the pool pairs. Ant Lion Optimizer-based program achieves comparable kidney exchange results to the deterministic-based approaches like integer programming. Also, ALO outperforms other stochastic-based methods such as Genetic Algorithm in terms of the efficient usage of computational resources and the quantity of resulting exchanges. Ant Lion Optimization algorithm can be adopted easily for on-line exchanges and the integration of weights for hard-to-match patients, which will improve the future decisions of kidney exchange programs. A reference implementation for ALO algorithm for kidney exchanges is written in MATLAB and is GPL licensed. It is available as free open-source software from: https://github.com/SaraEl-Metwally/ALO_algorithm_for_Kidney_Exchanges.

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making

PubMed Central

Hoover, Kevin M.; Bubak, Andrew N.; Law, Isaac J.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.

2016-01-01

Abstract Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant’s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions. PMID:29491915

Lazy workers are necessary for long-term sustainability in insect societies

PubMed Central

Hasegawa, Eisuke; Ishii, Yasunori; Tada, Koichiro; Kobayashi, Kazuya; Yoshimura, Jin

2016-01-01

Optimality theory predicts the maximization of productivity in social insect colonies, but many inactive workers are found in ant colonies. Indeed, the low short-term productivity of ant colonies is often the consequence of high variation among workers in the threshold to respond to task-related stimuli. Why is such an inefficient strategy among colonies maintained by natural selection? Here, we show that inactive workers are necessary for the long-term sustainability of a colony. Our simulation shows that colonies with variable thresholds persist longer than those with invariable thresholds because inactive workers perform the critical function of replacing active workers when they become fatigued. Evidence of the replacement of active workers by inactive workers has been found in ant colonies. Thus, the presence of inactive workers increases the long-term persistence of the colony at the expense of decreasing short-term productivity. Inactive workers may represent a bet-hedging strategy in response to environmental stochasticity. PMID:26880339

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas

PubMed Central

Shao, Jing; Yang, Lina; Peng, Ling; Chi, Tianhe; Wang, Xiaomeng

2015-01-01

China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC)-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining “replace” and “alter” operations, and the third is a “swap” strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China), and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing) was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures. PMID:26394148

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making.

PubMed

Hoover, Kevin M; Bubak, Andrew N; Law, Isaac J; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

2016-06-01

Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant's brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.

Ants impact the composition of the aquatic macroinvertebrate communities of a myrmecophytic tank bromeliad.

PubMed

Dejean, Alain; Compin, Arthur; Leponce, Maurice; Azémar, Frédéric; Bonhomme, Camille; Talaga, Stanislas; Pelozuelo, Laurent; Hénaut, Yann; Corbara, Bruno

2018-03-01

In an inundated Mexican forest, 89 out of 92 myrmecophytic tank bromeliads (Aechmea bracteata) housed an associated ant colony: 13 sheltered Azteca serica, 43 Dolichoderus bispinosus, and 33 Neoponera villosa. Ant presence has a positive impact on the diversity of the aquatic macroinvertebrate communities (n=30 bromeliads studied). A Principal Component Analysis (PCA) showed that the presence and the species of ant are not correlated to bromeliad size, quantity of water, number of wells, filtered organic matter or incident radiation. The PCA and a generalized linear model showed that the presence of Azteca serica differed from the presence of the other two ant species or no ants in its effects on the aquatic invertebrate community (more predators). Therefore, both ant presence and species of ant affect the composition of the aquatic macroinvertebrate communities in the tanks of A. bracteata, likely due to ant deposition of feces and other waste in these tanks. Copyright © 2018. Published by Elsevier Masson SAS.

Colony-level behavioural variation correlates with differences in expression of the foraging gene in red imported fire ants.

PubMed

Bockoven, Alison A; Coates, Craig J; Eubanks, Micky D

2017-11-01

Among social insects, colony-level variation is likely to be widespread and has significant ecological consequences. Very few studies, however, have documented how genetic factors relate to behaviour at the colony level. Differences in expression of the foraging gene have been associated with differences in foraging and activity of a wide variety of organisms. We quantified expression of the red imported fire ant foraging gene (sifor) in workers from 21 colonies collected across the natural range of Texas fire ant populations, but maintained under standardized, environmentally controlled conditions. Colonies varied significantly in their behaviour. The most active colonies had up to 10 times more active foragers than the least active colony and more than 16 times as many workers outside the nest. Expression differences among colonies correlated with this colony-level behavioural variation. Colonies with higher sifor expression in foragers had, on average, significantly higher foraging activity, exploratory activity and recruitment to nectar than colonies with lower expression. Expression of sifor was also strongly correlated with worker task (foraging vs. working in the interior of the nest). These results provide insight into the genetic and physiological processes underlying collective differences in social behaviour. Quantifying variation in expression of the foraging gene may provide an important tool for understanding and predicting the ecological consequences of colony-level behavioural variation. © 2017 John Wiley & Sons Ltd.

Mission planning optimization of video satellite for ground multi-object staring imaging

NASA Astrophysics Data System (ADS)

Cui, Kaikai; Xiang, Junhua; Zhang, Yulin

2018-03-01

This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

A new strategy for array optimization applied to Brazilian Decimetric Array

NASA Astrophysics Data System (ADS)

Faria, C.; Stephany, S.; Sawant, H. S.

Radio interferometric arrays measure the Fourier transform of the sky brightness distribution in a finite set of points that are determined by the cross-correlation of different pairs of antennas of the array The sky brightness distribution is reconstructed by the inverse Fourier transform of the sampled visibilities The quality of the reconstructed images strongly depends on the array configuration since it determines the sampling function and therefore the points in the Fourier Plane This work proposes a new optimization strategy for the array configuration that is based on the entropy of the distribution of the samples points in the Fourier plane A stochastic optimizer the Ant Colony Optimization employs entropy of the point distribution in the Fourier plane to iteratively refine the candidate solutions The proposed strategy was developed for the Brazilian Decimetric Array BDA a radio interferometric array that is currently being developed for solar observations at the Brazilian Institute for Space Research Configurations results corresponding to the Fourier plane coverage synthesized beam and side lobes levels are shown for an optimized BDA configuration obtained with the proposed strategy and compared to the results for a standard T array configuration that was originally proposed

Ants regulate colony spatial organization using multiple chemical road-signs

PubMed Central

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-01-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical ‘road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony. PMID:28569746

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

PubMed

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

An ant-plant mutualism through the lens of cGMP-dependent kinase genes.

PubMed

Malé, Pierre-Jean G; Turner, Kyle M; Doha, Manjima; Anreiter, Ina; Allen, Aaron M; Sokolowski, Marla B; Frederickson, Megan E

2017-09-13

In plant-animal mutualisms, how an animal forages often determines how much benefit its plant partner receives. In many animals, foraging behaviour changes in response to foraging gene expression or activation of the cGMP-dependent protein kinase (PKG) that foraging encodes. Here, we show that this highly conserved molecular mechanism affects the outcome of a plant-animal mutualism. We studied the two PKG genes of Allomerus octoarticulatus, an Amazonian ant that defends the ant-plant Cordia nodosa against herbivores. Some ant colonies are better 'bodyguards' than others. Working in the field in Peru, we found that colonies fed with a PKG activator recruited more workers to attack herbivores than control colonies. This resulted in less herbivore damage. PKG gene expression in ant workers correlated with whether an ant colony discovered an herbivore and how much damage herbivores inflicted on leaves in a complex way; natural variation in expression levels of the two genes had significant interaction effects on ant behaviour and herbivory. Our results suggest a molecular basis for ant protection of plants in this mutualism. © 2017 The Author(s).

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Chen, Tingyang; Zeng, Chunnian; Guo, Xueping; Lian, Huijuan; Zheng, You; Wei, Xiaoxu

2016-12-01

This paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). Owing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

The cost of being queen: investment across Pogonomyrmex harvester ant gynes that differ in degree of claustrality.

PubMed

Enzmann, Brittany L; Gibbs, Allen G; Nonacs, Peter

2014-11-01

The role of the ant colony largely consists of non-reproductive tasks, such as foraging, tending brood, and defense. However, workers are vitally linked to reproduction through their provisioning of sexual offspring, which are produced annually to mate and initiate new colonies. Gynes (future queens) have size-associated variation in colony founding strategy (claustrality), with each strategy requiring different energetic investments from their natal colony. We compared the per capita production cost required for semi-claustral, facultative, and claustral gynes across four species of Pogonomyrmex harvester ants. We found that the claustral founding strategy is markedly expensive, costing approximately 70% more energy than that of the semi-claustral strategy. Relative to males, claustral gynes also had the largest differential investment and smallest size variation. We applied these investment costs to a model by Brown and Bonhoeffer (2003) that predicts founding strategy based on investment cost and foraging survivorship. The model predicts that non-claustral foundresses must survive the foraging period with a probability of 30-36% in order for a foraging strategy to be selectively favored. These results highlight the importance of incorporating resource investment at the colony level when investigating the evolution of colony founding strategies in ants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ants regulate colony spatial organization using multiple chemical road-signs.

PubMed

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-06-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical 'road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony.

Task partitioning in a ponerine ant.

PubMed

Theraulaz, Guy; Bonabeau, Eric; Sole, Ricard V; Schatz, Bertrand; Deneubourg, Jean-Louis

2002-04-21

This paper reports a study of the task partitioning observed in the ponerine ant Ectatomma ruidum, where prey-foraging behaviour can be subdivided into two categories: stinging and transporting. Stingers kill live prey and transporters carry prey corpses back to the nest. Stinging and transporting behaviours are released by certain stimuli through response thresholds; the respective stimuli for stinging and transporting appear to be the number of live prey and the number of prey corpses. A response threshold model, the parameters of which are all measured empirically, reproduces a set of non-trivial colony-level dynamical patterns observed in the experiments. This combination of modelling and empirical work connects explicitly the level of individual behaviour with colony-level patterns of work organization. Copyright 2002 Elsevier Science Ltd. All rights reserved.

Using ant colony optimization on the quadratic assignment problem to achieve low energy cost in geo-distributed data centers

NASA Astrophysics Data System (ADS)

Osei, Richard

There are many problems associated with operating a data center. Some of these problems include data security, system performance, increasing infrastructure complexity, increasing storage utilization, keeping up with data growth, and increasing energy costs. Energy cost differs by location, and at most locations fluctuates over time. The rising cost of energy makes it harder for data centers to function properly and provide a good quality of service. With reduced energy cost, data centers will have longer lasting servers/equipment, higher availability of resources, better quality of service, a greener environment, and reduced service and software costs for consumers. Some of the ways that data centers have tried to using to reduce energy costs include dynamically switching on and off servers based on the number of users and some predefined conditions, the use of environmental monitoring sensors, and the use of dynamic voltage and frequency scaling (DVFS), which enables processors to run at different combinations of frequencies with voltages to reduce energy cost. This thesis presents another method by which energy cost at data centers could be reduced. This method involves the use of Ant Colony Optimization (ACO) on a Quadratic Assignment Problem (QAP) in assigning user request to servers in geo-distributed data centers. In this paper, an effort to reduce data center energy cost involves the use of front portals, which handle users' requests, were used as ants to find cost effective ways to assign users requests to a server in heterogeneous geo-distributed data centers. The simulation results indicate that the ACO for Optimal Server Activation and Task Placement algorithm reduces energy cost on a small and large number of users' requests in a geo-distributed data center and its performance increases as the input data grows. In a simulation with 3 geo-distributed data centers, and user's resource request ranging from 25,000 to 25,000,000, the ACO algorithm was able to reduce energy cost on an average of $.70 per second. The ACO for Optimal Server Activation and Task Placement algorithm has proven to work as an alternative or improvement in reducing energy cost in geo-distributed data centers.

Textural defect detect using a revised ant colony clustering algorithm

NASA Astrophysics Data System (ADS)

Zou, Chao; Xiao, Li; Wang, Bingwen

2007-11-01

We propose a totally novel method based on a revised ant colony clustering algorithm (ACCA) to explore the topic of textural defect detection. In this algorithm, our efforts are mainly made on the definition of local irregularity measurement and the implementation of the revised ACCA. The local irregular measurement defined evaluates the local textural inconsistency of each pixel against their mini-environment. In our revised ACCA, the behaviors of each ant are divided into two steps: release pheromone and act. The quantity of pheromone released is proportional to the irregularity measurement; the actions of the ants to act next are chosen independently of each other in a stochastic way according to some evaluated heuristic knowledge. The independency of ants implies the inherent parallel computation architecture of this algorithm. We apply the proposed method in some typical textural images with defects. From the series of pheromone distribution map (PDM), it can be clearly seen that the pheromone distribution approaches the textual defects gradually. By some post-processing, the final distribution of pheromone can demonstrate the shape and area of the defects well.

Ant colony optimisation-direct cover: a hybrid ant colony direct cover technique for multi-level synthesis of multiple-valued logic functions

NASA Astrophysics Data System (ADS)

Abd-El-Barr, Mostafa

2010-12-01

The use of non-binary (multiple-valued) logic in the synthesis of digital systems can lead to savings in chip area. Advances in very large scale integration (VLSI) technology have enabled the successful implementation of multiple-valued logic (MVL) circuits. A number of heuristic algorithms for the synthesis of (near) minimal sum-of products (two-level) realisation of MVL functions have been reported in the literature. The direct cover (DC) technique is one such algorithm. The ant colony optimisation (ACO) algorithm is a meta-heuristic that uses constructive greediness to explore a large solution space in finding (near) optimal solutions. The ACO algorithm mimics the ant's behaviour in the real world in using the shortest path to reach food sources. We have previously introduced an ACO-based heuristic for the synthesis of two-level MVL functions. In this article, we introduce the ACO-DC hybrid technique for the synthesis of multi-level MVL functions. The basic idea is to use an ant to decompose a given MVL function into a number of levels and then synthesise each sub-function using a DC-based technique. The results obtained using the proposed approach are compared to those obtained using existing techniques reported in the literature. A benchmark set consisting of 50,000 randomly generated 2-variable 4-valued functions is used in the comparison. The results obtained using the proposed ACO-DC technique are shown to produce efficient realisation in terms of the average number of gates (as a measure of chip area) needed for the synthesis of a given MVL function.

Solving the vehicle routing problem by a hybrid meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Yousefikhoshbakht, Majid; Khorram, Esmaile

2012-08-01

The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.

Why are there few seedlings beneath the myrmecophyte Triplaris americana?

NASA Astrophysics Data System (ADS)

Larrea-Alcázar, Daniel M.; Simonetti, Javier A.

2007-07-01

We compared the relative importance of chemical alellopathy, pruning behaviour of resident ants and other non-related agents to ant-plant mutualism for seedling establishment beneath Triplaris americana L. (Polygonaceae), a myrmecophyte plant. We also included a preliminary analysis of effects of fragmentation on these ecological processes. Seeds and seedlings of Theobroma cacao L. (Sterculiaceae) were used as the target species in all experiments. Leaf-tissue extracts of the myrmecophyte plant did not inhibit germination of cacao seeds. Resident Pseudomyrmex triplarinus Weddell (Pseudomyrmecinae) ants did not remove seeds under the canopy of their host plants. The main seed consumer was the leaf-cutting ant Atta sexdens L. (Myrmicinae). Leaves of cacao seedlings were partially or totally pruned by Pseudomyrmex ants mainly in forest fragments studied. We offer evidence pointing to the possibility that the absence of seedlings beneath Triplaris may result from effects of both ant species. We discuss the benefits of pruning behaviour for the resident ant colony and the effects of ant-ant interactions on seedling establishment beneath this ant-plant system.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Fairness in optimizing bus-crew scheduling process.

PubMed

Ma, Jihui; Song, Cuiying; Ceder, Avishai Avi; Liu, Tao; Guan, Wei

2017-01-01

This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group) Co., Ltd., one of the largest bus transit companies in the world. It shows that unfair cost is indirectly related to common cost, fixed cost and extra cost and also the unfair cost approaches to common and fixed cost when its coefficient is twice of common cost coefficient. Furthermore, the longest time for the tested bus line with 1108 pieces, 74 blocks is less than 30 minutes. The results indicate that the HACO-based algorithm can be a feasible and efficient optimization technique for CSP-BD, especially with large scale problems.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

Prudent Protomognathus and despotic Leptothorax duloticus: Differential costs of ant slavery

PubMed Central

Hare, James F.; Alloway, Thomas M.

2001-01-01

The concept of ant slavery rests on the untested assumption that slave-making ants impose fitness costs on colonies of the species they raid. We tested that assumption by comparing the summertime seasonal productivity of Leptothorax spp. colonies in field exclosures without slavemakers, with a colony of the obligatory slave-making ant Protomognathus americanus, or with a colony of the obligatory slavemaker Leptothorax duloticus. Leptothorax longispinosus colonies placed in exclosures with P. americanus colonies did not differ significantly in any demographic attribute from colonies in exclosures without slavemakers. By contrast, Leptothorax curvispinosus colonies exposed to L. duloticus experienced significant reductions in dealate queens, workers, and larvae relative to control colonies exclosed without slavemakers. The pronounced difference in the impact of these slavemakers on their host-species populations correlates with differences in the behavior of the slavemakers observed in the laboratory and likely explains why P. americanus is more abundant than L. duloticus in nature. It seems that more advanced social parasites, like anatomical parasites, evolve to minimize their impact on their hosts, and thus can be regarded as “prudent social parasites.” PMID:11572933

Pericarpial nectary-visiting ants do not provide fruit protection against pre-dispersal seed predators regardless of ant species composition and resource availability

PubMed Central

Ré Jorge, Leonardo; Benitez-Vieyra, Santiago; Amorim, Felipe W.

2017-01-01

Extrafloral nectaries can occur in both vegetative and reproductive plant structures. In many Rubiaceae species in the Brazilian Cerrado, after corolla abscission, the floral nectary continues to secret nectar throughout fruit development originating post-floral pericarpial nectaries which commonly attract many ant species. The occurrence of such nectar secreting structures might be strategic for fruit protection against seed predators, as plants are expected to invest higher on more valuable and vulnerable parts. Here, we performed ant exclusion experiments to investigate whether the interaction with ants mediated by the pericarpial nectaries of Tocoyena formosa affects plant reproductive success by reducing the number of pre-dispersal seed predators. We also assessed whether ant protection was dependent on ant species composition and resource availability. Although most of the plants were visited by large and aggressive ant species, such as Ectatomma tuberculatum and species of the genus Camponotus, ants did not protect fruits against seed predators. Furthermore, the result of the interaction was neither related to ant species composition nor to the availability of resources. We suggest that these results may be related to the nature and behavior of the most important seed predators, like Hemicolpus abdominalis weevil which the exoskeleton toughness prevent it from being predated by most ant species. On the other hand, not explored factors, such as reward quality, local ant abundance, ant colony characteristics and/or the presence of alternative energetic sources could also account for variations in ant frequency, composition, and finally ant protective effects, highlighting the conditionality of facultative plant-ant mutualisms. PMID:29211790

Specialization Does Not Predict Individual Efficiency in an Ant

PubMed Central

Dornhaus, Anna

2008-01-01

The ecological success of social insects is often attributed to an increase in efficiency achieved through division of labor between workers in a colony. Much research has therefore focused on the mechanism by which a division of labor is implemented, i.e., on how tasks are allocated to workers. However, the important assumption that specialists are indeed more efficient at their work than generalist individuals—the “Jack-of-all-trades is master of none” hypothesis—has rarely been tested. Here, I quantify worker efficiency, measured as work completed per time, in four different tasks in the ant Temnothorax albipennis: honey and protein foraging, collection of nest-building material, and brood transports in a colony emigration. I show that individual efficiency is not predicted by how specialized workers were on the respective task. Worker efficiency is also not consistently predicted by that worker's overall activity or delay to begin the task. Even when only the worker's rank relative to nestmates in the same colony was used, specialization did not predict efficiency in three out of the four tasks, and more specialized workers actually performed worse than others in the fourth task (collection of sand grains). I also show that the above relationships, as well as median individual efficiency, do not change with colony size. My results demonstrate that in an ant species without morphologically differentiated worker castes, workers may nevertheless differ in their ability to perform different tasks. Surprisingly, this variation is not utilized by the colony—worker allocation to tasks is unrelated to their ability to perform them. What, then, are the adaptive benefits of behavioral specialization, and why do workers choose tasks without regard for whether they can perform them well? We are still far from an understanding of the adaptive benefits of division of labor in social insects. PMID:19018663

Co-founding ant queens prevent disease by performing prophylactic undertaking behaviour.

PubMed

Pull, Christopher D; Cremer, Sylvia

2017-10-13

Social insects form densely crowded societies in environments with high pathogen loads, but have evolved collective defences that mitigate the impact of disease. However, colony-founding queens lack this protection and suffer high rates of mortality. The impact of pathogens may be exacerbated in species where queens found colonies together, as healthy individuals may contract pathogens from infectious co-founders. Therefore, we tested whether ant queens avoid founding colonies with pathogen-exposed conspecifics and how they might limit disease transmission from infectious individuals. Using Lasius niger queens and a naturally infecting fungal pathogen Metarhizium brunneum, we observed that queens were equally likely to found colonies with another pathogen-exposed or sham-treated queen. However, when one queen died, the surviving individual performed biting, burial and removal of the corpse. These undertaking behaviours were performed prophylactically, i.e. targeted equally towards non-infected and infected corpses, as well as carried out before infected corpses became infectious. Biting and burial reduced the risk of the queens contracting and dying from disease from an infectious corpse of a dead co-foundress. We show that co-founding ant queens express undertaking behaviours that, in mature colonies, are performed exclusively by workers. Such infection avoidance behaviours act before the queens can contract the disease and will therefore improve the overall chance of colony founding success in ant queens.

Surgery scheduling optimization considering real life constraints and comprehensive operation cost of operating room.

PubMed

Xiang, Wei; Li, Chong

2015-01-01

Operating Room (OR) is the core sector in hospital expenditure, the operation management of which involves a complete three-stage surgery flow, multiple resources, prioritization of the various surgeries, and several real-life OR constraints. As such reasonable surgery scheduling is crucial to OR management. To optimize OR management and reduce operation cost, a short-term surgery scheduling problem is proposed and defined based on the survey of the OR operation in a typical hospital in China. The comprehensive operation cost is clearly defined considering both under-utilization and overutilization. A nested Ant Colony Optimization (nested-ACO) incorporated with several real-life OR constraints is proposed to solve such a combinatorial optimization problem. The 10-day manual surgery schedules from a hospital in China are compared with the optimized schedules solved by the nested-ACO. Comparison results show the advantage using the nested-ACO in several measurements: OR-related time, nurse-related time, variation in resources' working time, and the end time. The nested-ACO considering real-life operation constraints such as the difference between first and following case, surgeries priority, and fixed nurses in pre/post-operative stage is proposed to solve the surgery scheduling optimization problem. The results clearly show the benefit of using the nested-ACO in enhancing the OR management efficiency and minimizing the comprehensive overall operation cost.

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments.

PubMed

Juang, Chia-Feng; Lai, Min-Ge; Zeng, Wan-Ting

2015-09-01

This paper presents a method that allows two wheeled, mobile robots to navigate unknown environments while cooperatively carrying an object. In the navigation method, a leader robot and a follower robot cooperatively perform either obstacle boundary following (OBF) or target seeking (TS) to reach a destination. The two robots are controlled by fuzzy controllers (FC) whose rules are learned through an adaptive fusion of continuous ant colony optimization and particle swarm optimization (AF-CACPSO), which avoids the time-consuming task of manually designing the controllers. The AF-CACPSO-based evolutionary fuzzy control approach is first applied to the control of a single robot to perform OBF. The learning approach is then applied to achieve cooperative OBF with two robots, where an auxiliary FC designed with the AF-CACPSO is used to control the follower robot. For cooperative TS, a rule for coordination of the two robots is developed. To navigate cooperatively, a cooperative behavior supervisor is introduced to select between cooperative OBF and cooperative TS. The performance of the AF-CACPSO is verified through comparisons with various population-based optimization algorithms for the OBF learning problem. Simulations and experiments verify the effectiveness of the approach for cooperative navigation of two robots.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

PubMed Central

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

Tricks of the trade: Mechanism of brood theft in an ant.

PubMed

Paul, Bishwarup; Annagiri, Sumana

2018-01-01

Thievery is ubiquitous in the animal kingdom, social insects not being an exception. Brood is invaluable for the survival of social insect colonies and brood theft is well documented in ants. In many species the stolen brood act as slaves in the thief colony as they take up tasks related to foraging, defence and colony maintenance. Slave-making (dulotic) ants are at an advantage as they gain workforce without investing in rearing immature young, and several slave-making species have been recorded in temperate regions. In the current study we investigate brood theft in a primitively eusocial ponerine ant Diacamma indicum that inhabits the tropics. In the context of colony relocation we asked how thieves steal brood and what victim colonies do to prevent theft. While exposed nests increased colonies' vulnerability, the relocation process itself did not enhance the chances of theft. Various aggressive interactions, in particular immobilization of intruders helped in preventing theft. Thieves that acted quickly, stayed furtive and stole unguarded brood were found to be successful. This comprehensive study of behavioural mechanism of theft reveals that these are the 'tricks' adopted by thieves.

Genetic evidence for landscape effects on dispersal in the army ant Eciton burchellii.

PubMed

Soare, Thomas W; Kumar, Anjali; Naish, Kerry A; O'Donnell, Sean

2014-01-01

Inhibited dispersal, leading to reduced gene flow, threatens populations with inbreeding depression and local extinction. Fragmentation may be especially detrimental to social insects because inhibited gene flow has important consequences for cooperation and competition within and among colonies. Army ants have winged males and permanently wingless queens; these traits imply male-biased dispersal. However, army ant colonies are obligately nomadic and have the potential to traverse landscapes. Eciton burchellii, the most regularly nomadic army ant, is a forest interior species: colony raiding activities are limited in the absence of forest cover. To examine whether nomadism and landscape (forest clearing and elevation) affect population genetic structure in a montane E. burchellii population, we reconstructed queen and male genotypes from 25 colonies at seven polymorphic microsatellite loci. Pairwise genetic distances among individuals were compared to pairwise geographical and resistance distances using regressions with permutations, partial Mantel tests and random forests analyses. Although there was no significant spatial genetic structure in queens or males in montane forest, dispersal may be male-biased. We found significant isolation by landscape resistance for queens based on land cover (forest clearing), but not on elevation. Summed colony emigrations over the lifetime of the queen may contribute to gene flow in this species and forest clearing impedes these movements and subsequent gene dispersal. Further forest cover removal may increasingly inhibit Eciton burchellii colony dispersal. We recommend maintaining habitat connectivity in tropical forests to promote population persistence for this keystone species. © 2013 John Wiley & Sons Ltd.

Hybrid real-code ant colony optimisation for constrained mechanical design

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Using Swarming Agents for Scalable Security in Large Network Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

Identification of the heat transfer coefficient in the two-dimensional model of binary alloy solidification

NASA Astrophysics Data System (ADS)

Hetmaniok, Edyta; Hristov, Jordan; Słota, Damian; Zielonka, Adam

2017-05-01

The paper presents the procedure for solving the inverse problem for the binary alloy solidification in a two-dimensional space. This is a continuation of some previous works of the authors investigating a similar problem but in the one-dimensional domain. Goal of the problem consists in identification of the heat transfer coefficient on boundary of the region and in reconstruction of the temperature distribution inside the considered region in case when the temperature measurements in selected points of the alloy are known. Mathematical model of the problem is based on the heat conduction equation with the substitute thermal capacity and with the liquidus and solidus temperatures varying in dependance on the concentration of the alloy component. For describing this concentration the Scheil model is used. Investigated procedure involves also the parallelized Ant Colony Optimization algorithm applied for minimizing a functional expressing the error of approximate solution.

Daughters inherit colonies from mothers in the 'living-fossil' ant Nothomyrmecia macrops

NASA Astrophysics Data System (ADS)

Sanetra, Matthias; Crozier, Ross H.

2002-02-01

Newly mated queens of monogynous (single queen) ants usually found their colonies independently, without the assistance of workers. In polygynous (multiple queen) species queens are often adopted back into their natal nest and new colonies are established by budding. We report that the Australian 'living-fossil' ant, Nothomyrmecia macrops, is exceptional in that its single queen can be replaced by one of the colony's daughters. This type of colony founding is an interesting alternative reproductive strategy in monogynous ants, which maximizes fitness under kin selection. Successive queen replacement results in a series of reproductives over time (serial polygyny), making these colonies potentially immortal. Workers raise nieces and nephews (relatedness ≤ 0.375) the year after queen replacement. Although N. macrops is 'primitive' in many other respects, colony inheritance is likely to be a derived specialization resulting from ecological constraints on solitary founding.

Destructive disinfection of infected brood prevents systemic disease spread in ant colonies

PubMed Central

Ugelvig, Line V; Wiesenhofer, Florian; Grasse, Anna V; Tragust, Simon; Schmitt, Thomas; Brown, Mark JF

2018-01-01

In social groups, infections have the potential to spread rapidly and cause disease outbreaks. Here, we show that in a social insect, the ant Lasius neglectus, the negative consequences of fungal infections (Metarhizium brunneum) can be mitigated by employing an efficient multicomponent behaviour, termed destructive disinfection, which prevents further spread of the disease through the colony. Ants specifically target infected pupae during the pathogen’s non-contagious incubation period, utilising chemical ‘sickness cues’ emitted by pupae. They then remove the pupal cocoon, perforate its cuticle and administer antimicrobial poison, which enters the body and prevents pathogen replication from the inside out. Like the immune system of a metazoan body that specifically targets and eliminates infected cells, ants destroy infected brood to stop the pathogen completing its lifecycle, thus protecting the rest of the colony. Hence, in an analogous fashion, the same principles of disease defence apply at different levels of biological organisation. PMID:29310753

Influence of toxic bait type and starvation on worker and queen mortality in laboratory colonies of Argentine ant (Hymenoptera: Formicidae).

PubMed

Mathieson, Melissa; Toft, Richard; Lester, Philip J

2012-08-01

The efficacy of toxic baits should be judged by their ability to kill entire ant colonies, including the colony queen or queens. We studied the efficacy of four toxic baits to the Argentine ant, Linepithema humile (Mayr) (Hymenoptera: Formicidae). These baits were Xstinguish that has the toxicant fipronil, Exterm-an-Ant that contains both boric acid and sodium borate, and Advion ant gel and Advion ant bait arena that both have indoxacarb. Experimental nests contained 300 workers and 10 queen ants that were starved for either 24 or 48 h before toxic bait exposure. The efficacy of the toxic baits was strongly influenced by starvation. In no treatment with 24-h starvation did we observe 100% worker death. After 24-h starvation three of the baits did not result in any queen deaths, with only Exterm-an-Ant producing an average of 25% mortality. In contrast, 100% queen and worker mortality was observed in colonies starved for 48 h and given Xstinguish or Exterm-an-Ant. The baits Advion ant gel and Advion ant bait arena were not effective against Argentine ants in these trials, resulting in <60% mortality in all treatments. Because of the strong influence of starvation on bait uptake, control efficacy may be maximized by applying bait when ants are likely to be starved. Our results suggest queen mortality must be assessed in tests for toxic bait efficacy. Our data indicate that of these four baits, Xstinguish and Exterm-an-Ant are the best options for control of Argentine ants in New Zealand.

Evolutionary algorithms for the optimal management of coastal groundwater: A comparative study toward future challenges

NASA Astrophysics Data System (ADS)

Ketabchi, Hamed; Ataie-Ashtiani, Behzad

2015-01-01

This paper surveys the literature associated with the application of evolutionary algorithms (EAs) in coastal groundwater management problems (CGMPs). This review demonstrates that previous studies were mostly relied on the application of limited and particular EAs, mainly genetic algorithm (GA) and its variants, to a number of specific problems. The exclusive investigation of these problems is often not the representation of the variety of feasible processes may be occurred in coastal aquifers. In this study, eight EAs are evaluated for CGMPs. The considered EAs are: GA, continuous ant colony optimization (CACO), particle swarm optimization (PSO), differential evolution (DE), artificial bee colony optimization (ABC), harmony search (HS), shuffled complex evolution (SCE), and simplex simulated annealing (SIMPSA). The first application of PSO, ABC, HS, and SCE in CGMPs is reported here. Moreover, the four benchmark problems with different degree of difficulty and variety are considered to address the important issues of groundwater resources in coastal regions. Hence, the wide ranges of popular objective functions and constraints with the number of decision variables ranging from 4 to 15 are included. These benchmark problems are applied in the combined simulation-optimization model to examine the optimization scenarios. Some preliminary experiments are performed to select the most efficient parameters values for EAs to set a fair comparison. The specific capabilities of each EA toward CGMPs in terms of results quality and required computational time are compared. The evaluation of the results highlights EA's applicability in CGMPs, besides the remarkable strengths and weaknesses of them. The comparisons show that SCE, CACO, and PSO yield superior solutions among the EAs according to the quality of solutions whereas ABC presents the poor performance. CACO provides the better solutions (up to 17%) than the worst EA (ABC) for the problem with the highest decision variables and more complexity. In terms of computational time, PSO and SIMPSA are the fastest. SCE needs the highest computational time, even up to four times in comparison to the fastest EAs. CACO and PSO can be recommended for application in CGMPs, in terms of both abovementioned criteria.

Profiling and Metabolism of Sterols in the Weaver Ant Genus Oecophylla.

PubMed

Vidkjær, Nanna H; Jensen, Karl-Martin V; Gislum, René; Fomsgaard, Inge S

2016-01-01

Sterols are essential to insects because they are vital for many biochemical processes, nevertheless insects cannot synthesize sterols but have to acquire them through their diet. Studies of sterols in ants are sparse and here the sterols of the weaver ant genus Oecophylla are identified for the first time. The sterol profile and the dietary sterols provided to a laboratory Oecophylla longinoda colony were analyzed. Most sterols originated from the diet, except one, which was probably formed via dealkylation in the ants and two sterols of fungal origin, which likely originate from hitherto unidentified endosymbionts responsible for supplying these two compounds. The sterol profile of a wild Oecophylla smaragdina colony was also investigated. Remarkable qualitative similarities were established between the two species despite the differences in diet, species, and origin. This may reflect a common sterol need/aversion in the weaver ants. Additionally, each individual caste of both species displayed unique sterol profiles.

Variance-based selection may explain general mating patterns in social insects.

PubMed

Rueppell, Olav; Johnson, Nels; Rychtár, Jan

2008-06-23

Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.

Self-Adaptive Stepsize Search Applied to Optimal Structural Design

NASA Astrophysics Data System (ADS)

Nolle, L.; Bland, J. A.

Structural engineering often involves the design of space frames that are required to resist predefined external forces without exhibiting plastic deformation. The weight of the structure and hence the weight of its constituent members has to be as low as possible for economical reasons without violating any of the load constraints. Design spaces are usually vast and the computational costs for analyzing a single design are usually high. Therefore, not every possible design can be evaluated for real-world problems. In this work, a standard structural design problem, the 25-bar problem, has been solved using self-adaptive stepsize search (SASS), a relatively new search heuristic. This algorithm has only one control parameter and therefore overcomes the drawback of modern search heuristics, i.e. the need to first find a set of optimum control parameter settings for the problem at hand. In this work, SASS outperforms simulated-annealing, genetic algorithms, tabu search and ant colony optimization.

Tricks of the trade: Mechanism of brood theft in an ant

PubMed Central

Paul, Bishwarup

2018-01-01

Thievery is ubiquitous in the animal kingdom, social insects not being an exception. Brood is invaluable for the survival of social insect colonies and brood theft is well documented in ants. In many species the stolen brood act as slaves in the thief colony as they take up tasks related to foraging, defence and colony maintenance. Slave-making (dulotic) ants are at an advantage as they gain workforce without investing in rearing immature young, and several slave-making species have been recorded in temperate regions. In the current study we investigate brood theft in a primitively eusocial ponerine ant Diacamma indicum that inhabits the tropics. In the context of colony relocation we asked how thieves steal brood and what victim colonies do to prevent theft. While exposed nests increased colonies’ vulnerability, the relocation process itself did not enhance the chances of theft. Various aggressive interactions, in particular immobilization of intruders helped in preventing theft. Thieves that acted quickly, stayed furtive and stole unguarded brood were found to be successful. This comprehensive study of behavioural mechanism of theft reveals that these are the ‘tricks’ adopted by thieves. PMID:29489858

Destructive disinfection of infected brood prevents systemic disease spread in ant colonies.

PubMed

Pull, Christopher D; Ugelvig, Line V; Wiesenhofer, Florian; Grasse, Anna V; Tragust, Simon; Schmitt, Thomas; Brown, Mark Jf; Cremer, Sylvia

2018-01-09

In social groups, infections have the potential to spread rapidly and cause disease outbreaks. Here, we show that in a social insect, the ant Lasius neglectus , the negative consequences of fungal infections ( Metarhizium brunneum ) can be mitigated by employing an efficient multicomponent behaviour, termed destructive disinfection, which prevents further spread of the disease through the colony. Ants specifically target infected pupae during the pathogen's non-contagious incubation period, utilising chemical 'sickness cues' emitted by pupae. They then remove the pupal cocoon, perforate its cuticle and administer antimicrobial poison, which enters the body and prevents pathogen replication from the inside out. Like the immune system of a metazoan body that specifically targets and eliminates infected cells, ants destroy infected brood to stop the pathogen completing its lifecycle, thus protecting the rest of the colony. Hence, in an analogous fashion, the same principles of disease defence apply at different levels of biological organisation.

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

The adaptive significance of phasic colony cycles in army ants.

PubMed

Garnier, Simon; Kronauer, Daniel J C

2017-09-07

Army ants are top arthropod predators in tropical forests around the world. The colonies of many army ant species undergo stereotypical behavioral and reproductive cycles, alternating between brood care and reproductive phases. In the brood care phase, colonies contain a cohort of larvae that are synchronized in their development and have to be fed. In the reproductive phase larvae are absent and oviposition takes place. Despite these colony cycles being a striking feature of army ant biology, their adaptive significance is unclear. Here we use a modeling approach to show that cyclic reproduction is favored under conditions where per capita foraging costs decrease with the number of larvae in a colony ("High Cost of Entry" scenario), while continuous reproduction is favored under conditions where per capita foraging costs increase with the number of larvae ("Resource Exhaustion" scenario). We argue that the former scenario specifically applies to army ants, because large raiding parties are required to overpower prey colonies. However, once raiding is successful it provides abundant food for a large cohort of larvae. The latter scenario, on the other hand, will apply to non-army ants, because in those species local resource depletion will force workers to forage over larger distances to feed large larval cohorts. Our model provides a quantitative framework for understanding the adaptive value of phasic colony cycles in ants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization for routing vehicles of seafood product transportation

NASA Astrophysics Data System (ADS)

Soenandi, I. A.; Juan, Y.; Budi, M.

2017-12-01

Recently, increasing usage of marine products is creating new challenges for businesses of marine products in terms of transportation that used to carry the marine products like seafood to the main warehouse. This can be a problem if the carrier fleet is limited, and there are time constraints in terms of the freshness of the marine product. There are many ways to solve this problem, including the optimization of routing vehicles. In this study, this strategy is to implement in the marine product business in Indonesia with such an expected arrangement of the company to optimize routing problem in transportation with time and capacity windows. Until now, the company has not used the scientific method to manage the routing of their vehicle from warehouse to the location of marine products source. This study will solve a stochastic Vehicle Routing Problems (VRP) with time and capacity windows by using the comparison of six methods and looking the best results for the optimization, in this situation the company could choose the best method, in accordance with the existing condition. In this research, we compared the optimization with another method such as branch and bound, dynamic programming and Ant Colony Optimization (ACO). Finally, we get the best result after running ACO algorithm with existing travel time data. With ACO algorithm was able to reduce vehicle travel time by 3189.65 minutes, which is about 23% less than existing and based on consideration of the constraints of time within 2 days (including rest time for the driver) using 28 tons capacity of truck and the companies need two units of vehicles for transportation.

Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling

NASA Astrophysics Data System (ADS)

Basu, M.

2014-12-01

Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.

Harnessing ant defence at fruits reduces bruchid seed predation in a symbiotic ant-plant mutualism.

PubMed

Pringle, Elizabeth G

2014-06-22

In horizontally transmitted mutualisms, mutualists disperse separately and reassemble in each generation with partners genetically unrelated to those in the previous generation. Because of this, there should be no selection on either partner to enhance the other's reproductive output directly. In symbiotic ant-plant mutualisms, myrmecophytic plants host defensive ant colonies, and ants defend the plants from herbivores. Plants and ants disperse separately, and, although ant defence can indirectly increase plant reproduction by reducing folivory, it is unclear whether ants can also directly increase plant reproduction by defending seeds. The neotropical tree Cordia alliodora hosts colonies of Azteca pittieri ants. The trees produce domatia where ants nest at stem nodes and also at the node between the peduncle and the rachides of the infloresence. Unlike the stem domatia, these reproductive domatia senesce after the tree fruits each year. In this study, I show that the tree's resident ant colony moves into these ephemeral reproductive domatia, where they tend honeydew-producing scale insects and patrol the nearby developing fruits. The presence of ants significantly reduced pre-dispersal seed predation by Amblycerus bruchid beetles, thereby directly increasing plant reproductive output.

Resource redistribution in polydomous ant nest networks: local or global?

PubMed Central

Franks, Daniel W.; Robinson, Elva J.H.

2014-01-01

An important problem facing organisms in a heterogeneous environment is how to redistribute resources to where they are required. This is particularly complex in social insect societies as resources have to be moved both from the environment into the nest and between individuals within the nest. Polydomous ant colonies are split between multiple spatially separated, but socially connected, nests. Whether, and how, resources are redistributed between nests in polydomous colonies is unknown. We analyzed the nest networks of the facultatively polydomous wood ant Formica lugubris. Our results indicate that resource redistribution in polydomous F. lugubris colonies is organized at the local level between neighboring nests and not at the colony level. We found that internest trails connecting nests that differed more in their amount of foraging were stronger than trails between nests with more equal foraging activity. This indicates that resources are being exchanged directly from nests with a foraging excess to nests that require resources. In contrast, we found no significant relationships between nest properties, such as size and amount of foraging, and network measures such as centrality and connectedness. This indicates an absence of a colony-level resource exchange. This is a clear example of a complex behavior emerging as a result of local interactions between parts of a system. PMID:25214755

Alate susceptibility in ants

PubMed Central

Ho, Eddie K H; Frederickson, Megan E

2014-01-01

Pathogens are predicted to pose a particular threat to eusocial insects because infections can spread rapidly in colonies with high densities of closely related individuals. In ants, there are two major castes: workers and reproductives. Sterile workers receive no direct benefit from investing in immunity, but can gain indirect fitness benefits if their immunity aids the survival of their fertile siblings. Virgin reproductives (alates), on the other hand, may be able to increase their investment in reproduction, rather than in immunity, because of the protection they receive from workers. Thus, we expect colonies to have highly immune workers, but relatively more susceptible alates. We examined the survival of workers, gynes, and males of nine ant species collected in Peru and Canada when exposed to the entomopathogenic fungus Beauveria bassiana. For the seven species in which treatment with B. bassiana increased ant mortality relative to controls, we found workers were significantly less susceptible compared with both alate sexes. Female and male alates did not differ significantly in their immunocompetence. Our results suggest that, as with other nonreproductive tasks in ant colonies like foraging and nest maintenance, workers have primary responsibility for colony immunity, allowing alates to specialize on reproduction. We highlight the importance of colony-level selection on individual immunity in ants and other eusocial organisms. PMID:25540683

Multi-Objective Mission Route Planning Using Particle Swarm Optimization

DTIC Science & Technology

2002-03-01

solutions to complex problems using particles that interact with each other. Both Particle Swarm Optimization (PSO) and the Ant System (AS) have been...EXPERIMENTAL DESING PROCESS..............................................................55 5.1. Introduction...46 18. Phenotype level particle interaction

Circadian consequences of social organization in the ant species Camponotus compressus

NASA Astrophysics Data System (ADS)

Sharma, Vijay Kumar; Lone, Shahnaz Rahman; Goel, Anubhuthi; Chandrashekaran, M. K.

The locomotor activity rhythm of different castes of the ant species Camponotus compressus was monitored individually under laboratory light/dark (LD) cycles, and under continuous darkness (DD). The colony of this ant species comprises two sexual castes, the queens and the males, and three worker castes, namely the major, media, and minor workers. The virgin males and virgin queens display rhythmic activity patterns, but the mated queens were arrhythmic while laying eggs, with the rhythmicity resuming soon after egg-laying. Under the LD regime, major workers showed nocturnal patterns, while about 75% of the media workers displayed nocturnal patterns and about 25% showed diurnal patterns. Under the DD regime, most major workers exhibited circadian rhythm of activity with a single steady state, whereas media workers displayed two types of activity patterns, with activity patterns changing after 6-9 days in DD (turn-arounds). The pre-turn-around τ of the ants that showed nocturnal activity patterns during LD entrainment was <24 h after release into DD, which then became >24 h, after 6-9 days. On the other hand, the pre-turn-around τ of those ants that exhibited diurnal patterns during LD entrainment was first >24 h after release into DD, and then became <24 h, after 6-9 days. The activity of the minor workers neither entrained to LD cycles nor showed any sign of free-run in DD. It appears that the circadian clocks of the ant species C. compressus are flexible, and may perhaps depend upon the tasks assigned to them in the colony.

DEVELOPING AND FIELD IMPLEMENTING A DYNAMIC ECO-ROUTING SYSTEM.

DOT National Transportation Integrated Search

2017-04-01

The study develops two different eco-routing systems and uses them to investigate and quantify the system-wide impacts of implementing an eco-routing system. The first one is basically a Nash Equilibrium feedback system, which uses the Ant Colony opt...

Role of early experience in ant enslavement: a comparative analysis of a host and a non-host species

PubMed Central

Blatrix, Rumsaïs; Sermage, Claire

2005-01-01

Background Ants use the odour of the colony to discriminate nestmates. In some species, this odour is learned during the first days following emergence, and thus early experience has a strong influence on nestmate discrimination. Slave-making ants are social parasites that capture brood of other ant species to increase the worker force of their colony. After emerging in the slave-maker nest, slave workers work as if they were in their own colony. We tested the hypothesis that early experience allows the deception of commonly enslaved species, while non-host species use a different mechanism, which does not involve learning. Results Pupae of a host species, Temnothorax unifasciatus, and a non-host species, T. parvulus, were allowed to emerge in the presence of workers of one of two slave-maker species, Chalepoxenus muellerianus or Myrmoxenus ravouxi. When T. unifasciatus was exposed to slave-makers for 10 days following emergence, they were more aggressive towards their own sisters and groomed the slave-maker more. T. parvulus gave a less clear result: while workers behaved more aggressively towards their sisters when exposed early to C. muellerianus workers, this was not the case when exposed early to M. ravouxi workers. Moreover, T. parvulus workers allogroomed conspecific nestmates less than T. unifasciatus. Allogrooming activity might be very important for the slave-makers because they are tended by their slaves. Conclusion Our findings show that early experience influences nestmate discrimination in the ant T. unifasciatus and can account for the successful enslavement of this species. However, the non-host species T. parvulus is less influenced by the early environment. This might help to explain why this species is never used by social parasites. PMID:16076389

A novel global Harmony Search method based on Ant Colony Optimisation algorithm

NASA Astrophysics Data System (ADS)

Fouad, Allouani; Boukhetala, Djamel; Boudjema, Fares; Zenger, Kai; Gao, Xiao-Zhi

2016-03-01

The Global-best Harmony Search (GHS) is a stochastic optimisation algorithm recently developed, which hybridises the Harmony Search (HS) method with the concept of swarm intelligence in the particle swarm optimisation (PSO) to enhance its performance. In this article, a new optimisation algorithm called GHSACO is developed by incorporating the GHS with the Ant Colony Optimisation algorithm (ACO). Our method introduces a novel improvisation process, which is different from that of the GHS in the following aspects. (i) A modified harmony memory (HM) representation and conception. (ii) The use of a global random switching mechanism to monitor the choice between the ACO and GHS. (iii) An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The proposed GHSACO algorithm has been applied to various benchmark functions and constrained optimisation problems. Simulation results demonstrate that it can find significantly better solutions when compared with the original HS and some of its variants.

Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hooper-Bui, L. M.; Kwok, E S.C.; Buchholz, B. A.

Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14C-sucrose, 14C-hydramethylnon, and 14C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), butmore » dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). Moreover, the distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. The bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.« less

A specialist herbivore uses chemical camouflage to overcome the defenses of an ant-plant mutualism.

PubMed

Whitehead, Susan R; Reid, Ellen; Sapp, Joseph; Poveda, Katja; Royer, Anne M; Posto, Amanda L; Kessler, André

2014-01-01

Many plants and ants engage in mutualisms where plants provide food and shelter to the ants in exchange for protection against herbivores and competitors. Although several species of herbivores thwart ant defenses and extract resources from the plants, the mechanisms that allow these herbivores to avoid attack are poorly understood. The specialist insect herbivore, Piezogaster reclusus (Hemiptera: Coreidae), feeds on Neotropical bull-horn acacias (Vachellia collinsii) despite the presence of Pseudomyrmex spinicola ants that nest in and aggressively defend the trees. We tested three hypotheses for how P. reclusus feeds on V. collinsii while avoiding ant attack: (1) chemical camouflage via cuticular surface compounds, (2) chemical deterrence via metathoracic defense glands, and (3) behavioral traits that reduce ant detection or attack. Our results showed that compounds from both P. reclusus cuticles and metathoracic glands reduce the number of ant attacks, but only cuticular compounds appear to be essential in allowing P. reclusus to feed on bull-horn acacia trees undisturbed. In addition, we found that ant attack rates to P. reclusus increased significantly when individuals were transferred between P. spinicola ant colonies. These results are consistent with the hypothesis that chemical mimicry of colony-specific ant or host plant odors plays a key role in allowing P. reclusus to circumvent ant defenses and gain access to important resources, including food and possibly enemy-free space. This interaction between ants, acacias, and their herbivores provides an excellent example of the ability of herbivores to adapt to ant defenses of plants and suggests that herbivores may play an important role in the evolution and maintenance of mutualisms.

Mathematical modeling on obligate mutualism: Interactions between leaf-cutter ants and their fungus garden.

PubMed

Kang, Yun; Clark, Rebecca; Makiyama, Michael; Fewell, Jennifer

2011-11-21

We propose a simple mathematical model by applying Michaelis-Menton equations of enzyme kinetics to study the mutualistic interaction between the leaf cutter ant and its fungus garden at the early stage of colony expansion. We derive sufficient conditions on the extinction and coexistence of these two species. In addition, we give a region of initial condition that leads to the extinction of two species when the model has an interior attractor. Our global analysis indicates that the division of labor by worker ants and initial conditions are two important factors that determine whether leaf cutter ants' colonies and their fungus garden can survive and grow or not. We validate the model by comparing model simulations and data on fungal and ant colony growth rates under laboratory conditions. We perform sensitive analysis of the model based on the experimental data to gain more biological insights on ecological interactions between leaf-cutter ants and their fungus garden. Finally, we give conclusions and discuss potential future work. Published by Elsevier Ltd.

Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

DOE PAGES

Hooper-Bui, L. M.; Kwok, E S.C.; Buchholz, B. A.; ...

2015-07-03

Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14C-sucrose, 14C-hydramethylnon, and 14C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), butmore » dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). Moreover, the distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. The bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.« less

Foraging activity and dietary spectrum of the Argentine ant (Hymenoptera: Formicidae) in invaded natural areas of the northeast Iberian Peninsula.

PubMed

Abril, S; Oliveras, J; Gómez, C

2007-10-01

We analyzed the foraging activity and the dietary spectrum of the Argentine ant (Linepithema humile Mayr) and select native ants on cork oaks from Mediterranean open cork oak (Quercus suber) secondary forests. The study areas included invaded and noninvaded zones in close proximity. The Argentine ant's daily foraging activity was correlated to the abiotic factors studied, whereas the seasonal foraging activity was related not only to the variations in the average air temperature, but also to the trophic needs of the colony. Argentine ant workers focused their attention on protein foods during the queens' oviposition periods and during the larvae development phase, and on carbohydrate foods, such as honeydew, when males and workers were hatching. There were no significant differences over the entire year in the quantity of liquid food collected by the Argentine ant workers in comparison with the native ants studied. The solid diet of the Argentine ant on cork oaks is composed of insects, most of which are aphids. Our results have clear applications for control methods based on toxic baits in the invaded natural ecosystems of the Iberian Peninsula.

Application of Metaheuristic and Deterministic Algorithms for Aircraft Reference Trajectory Optimization =

NASA Astrophysics Data System (ADS)

Murrieta Mendoza, Alejandro

Aircraft reference trajectory is an alternative method to reduce fuel consumption, thus the pollution released to the atmosphere. Fuel consumption reduction is of special importance for two reasons: first, because the aeronautical industry is responsible of 2% of the CO2 released to the atmosphere, and second, because it will reduce the flight cost. The aircraft fuel model was obtained from a numerical performance database which was created and validated by our industrial partner from flight experimental test data. A new methodology using the numerical database was proposed in this thesis to compute the fuel burn for a given trajectory. Weather parameters such as wind and temperature were taken into account as they have an important effect in fuel burn. The open source model used to obtain the weather forecast was provided by Weather Canada. A combination of linear and bi-linear interpolations allowed finding the required weather data. The search space was modelled using different graphs: one graph was used for mapping the different flight phases such as climb, cruise and descent, and another graph was used for mapping the physical space in which the aircraft would perform its flight. The trajectory was optimized in its vertical reference trajectory using the Beam Search algorithm, and a combination of the Beam Search algorithm with a search space reduction technique. The trajectory was optimized simultaneously for the vertical and lateral reference navigation plans while fulfilling a Required Time of Arrival constraint using three different metaheuristic algorithms: the artificial bee's colony, and the ant colony optimization. Results were validated using the software FlightSIMRTM, a commercial Flight Management System, an exhaustive search algorithm, and as flown flights obtained from flightawareRTM. All algorithms were able to reduce the fuel burn, and the flight costs. None None None None None None None

Blending in with the crowd: social parasites integrate into their host colonies using a flexible chemical signature.

PubMed Central

D'Ettorre, P; Mondy, N; Lenoir, A; Errard, C

2002-01-01

Social parasites are able to exploit their host's communication code and achieve social integration. For colony foundation, a newly mated slave-making ant queen must usurp a host colony. The parasite's brood is cared for by the hosts and newly eclosed slave-making workers integrate to form a mixed ant colony. To elucidate the social integration strategy of the slave-making workers, Polyergus rufescens, behavioural and chemical analyses were carried out. Cocoons of P. rufescens were introduced into subcolonies of four potential host species: Formica subgenus Serviformica (Formica cunicularia and F. rufibarbis, usual host species; F. gagates, rare host; F. selysi, non-natural host). Slave-making broods were cared for and newly emerged workers showed several social interactions with adult Formica. We recorded the occurrence of abdominal trophallaxis, in which P. rufescens, the parasite, was the donor. Social integration of P. rufescens workers into host colonies appears to rely on the ability of the parasite to modify its cuticular hydrocarbon profile to match that of the rearing species. To study the specific P. rufescens chemical profile, newly emerged callows were reared in isolation from the mother colony (without any contact with adult ants). The isolated P. rufescens workers exhibited a chemical profile closely matching that of the primary host species, indicating the occurrence of local host adaptation in the slave-maker population. However, the high flexibility in the ontogeny of the parasite's chemical signature could allow for host switching. PMID:12350253

Gaseous templates in ant nests.

PubMed

Cox, M D; Blanchard, G B

2000-05-21

We apply a diffusion model to the atmosphere of ant nests. With particular reference to carbon dioxide (CO2), we explore analytically and numerically the spatial and temporal patterns of brood- or worker-produced gases in nests. The maximum concentration within a typical one-chamber ant nest with approximately 200 ants can reach 12.5 times atmospheric concentration, reaching 95% of equilibrium concentrations within 15 min. Maximum concentration increases with increasing number of ants in the nest (or production rate of the gas), distance between the centre of the nest ants and the nest entrance, entrance length, wall thickness, and with decreasing entrance width, wall permeability and diffusion coefficient. The nest can be divided into three qualitatively distinct regions according to the shape of the gradient: a plateau of high concentration in the back half of the nest; an intermediate region of increasingly steep gradient towards the entrance; and a steep linear gradient in the entrance tunnel. These regions are robust to changes in gas concentrations, but vary with changes in nest architecture. The pattern of diffusing gases contains information about position and orientation relative to gas sources and sinks, and about colony state, including colony size, activity state and aspects of nest architecture. We discuss how this diffusion pattern may act as a "dynamic template", providing local cues which trigger behavioural acts appropriate to colony needs, which in turn may feed back to changes in the gas template. In particular, wall building occurs along lines of similar concentration for a variety of nest geometries; there is surprising convergence between the period of cycles of synchronously active ants and the time taken for CO2 levels to equilibrate; and the qualitatively distinct regions of the "dynamic template" correspond to regions occupied by different groups of ants.

Variation in butterfly larval acoustics as a strategy to infiltrate and exploit host ant colony resources.

PubMed

Sala, Marco; Casacci, Luca Pietro; Balletto, Emilio; Bonelli, Simona; Barbero, Francesca

2014-01-01

About 10,000 arthropods live as ants' social parasites and have evolved a number of mechanisms allowing them to penetrate and survive inside the ant nests. Many of them can intercept and manipulate their host communication systems. This is particularly important for butterflies of the genus Maculinea, which spend the majority of their lifecycle inside Myrmica ant nests. Once in the colony, caterpillars of Maculinea "predatory species" directly feed on the ant larvae, while those of "cuckoo species" are fed primarily by attendance workers, by trophallaxis. It has been shown that Maculinea cuckoo larvae are able to reach a higher social status within the colony's hierarchy by mimicking the acoustic signals of their host queen ants. In this research we tested if, when and how myrmecophilous butterflies may change sound emissions depending on their integration level and on stages of their life cycle. We studied how a Maculinea predatory species (M. teleius) can acoustically interact with their host ants and highlighted differences with respect to a cuckoo species (M. alcon). We recorded sounds emitted by Maculinea larvae as well as by their Myrmica hosts, and performed playback experiments to assess the parasites' capacity to interfere with the host acoustic communication system. We found that, although varying between and within butterfly species, the larval acoustic emissions are more similar to queens' than to workers' stridulations. Nevertheless playback experiments showed that ant workers responded most strongly to the sounds emitted by the integrated (i.e. post-adoption) larvae of the cuckoo species, as well as by those of predatory species recorded before any contact with the host ants (i.e. in pre-adoption), thereby revealing the role of acoustic signals both in parasite integration and in adoption rituals. We discuss our findings in the broader context of parasite adaptations, comparing effects of acoustical and chemical mimicry.

Variation in Butterfly Larval Acoustics as a Strategy to Infiltrate and Exploit Host Ant Colony Resources

PubMed Central

Sala, Marco; Casacci, Luca Pietro; Balletto, Emilio; Bonelli, Simona; Barbero, Francesca

2014-01-01

About 10,000 arthropods live as ants' social parasites and have evolved a number of mechanisms allowing them to penetrate and survive inside the ant nests. Many of them can intercept and manipulate their host communication systems. This is particularly important for butterflies of the genus Maculinea, which spend the majority of their lifecycle inside Myrmica ant nests. Once in the colony, caterpillars of Maculinea “predatory species” directly feed on the ant larvae, while those of “cuckoo species” are fed primarily by attendance workers, by trophallaxis. It has been shown that Maculinea cuckoo larvae are able to reach a higher social status within the colony's hierarchy by mimicking the acoustic signals of their host queen ants. In this research we tested if, when and how myrmecophilous butterflies may change sound emissions depending on their integration level and on stages of their life cycle. We studied how a Maculinea predatory species (M. teleius) can acoustically interact with their host ants and highlighted differences with respect to a cuckoo species (M. alcon). We recorded sounds emitted by Maculinea larvae as well as by their Myrmica hosts, and performed playback experiments to assess the parasites' capacity to interfere with the host acoustic communication system. We found that, although varying between and within butterfly species, the larval acoustic emissions are more similar to queens' than to workers' stridulations. Nevertheless playback experiments showed that ant workers responded most strongly to the sounds emitted by the integrated (i.e. post-adoption) larvae of the cuckoo species, as well as by those of predatory species recorded before any contact with the host ants (i.e. in pre-adoption), thereby revealing the role of acoustic signals both in parasite integration and in adoption rituals. We discuss our findings in the broader context of parasite adaptations, comparing effects of acoustical and chemical mimicry. PMID:24718496

Social and Population Structure in the Ant Cataglyphis emmae

PubMed Central

Jowers, Michael J.; Leniaud, Laurianne; Cerdá, Xim; Alasaad, Samer; Caut, Stephane; Amor, Fernando; Aron, Serge; Boulay, Raphaël R.

2013-01-01

Dispersal has consequences not only for individual fitness, but also for population dynamics, population genetics and species distribution. Social Hymenoptera show two contrasting colony reproductive strategies, dependent and independent colony foundation modes, and these are often associated to the population structures derived from inter and intra-population gene flow processes conditioned by alternative dispersal strategies. Here we employ microsatellite and mitochondrial markers to investigate the population and social genetic structure and dispersal patterns in the ant Cataglyphis emmae at both, local and regional scales. We find that C. emmae is monogynous and polyandrous. Lack of detection of any population viscosity and population structure with nuclear markers at the local scale suggests efficient dispersal, in agreement with a lack of inbreeding. Contrasting demographic differences before and during the mating seasons suggest that C. emmae workers raise sexuals in peripheric nest chambers to reduce intracolonial conflicts. The high genetic differentiation recovered from the mtDNA haplotypes, together with the significant correlation of such to geographic distance, and presence of new nuclear alleles between areas (valleys) suggest long-term historical isolation between these regions, indicative of limited dispersal at the regional scale. Our findings on the ecological, social and population structure of this species increases our understanding of the patterns and processes involved under independent colony foundation. PMID:24039827

A Specialist Herbivore Uses Chemical Camouflage to Overcome the Defenses of an Ant-Plant Mutualism

PubMed Central

Whitehead, Susan R.; Reid, Ellen; Sapp, Joseph; Poveda, Katja; Royer, Anne M.; Posto, Amanda L.; Kessler, André

2014-01-01

Many plants and ants engage in mutualisms where plants provide food and shelter to the ants in exchange for protection against herbivores and competitors. Although several species of herbivores thwart ant defenses and extract resources from the plants, the mechanisms that allow these herbivores to avoid attack are poorly understood. The specialist insect herbivore, Piezogaster reclusus (Hemiptera: Coreidae), feeds on Neotropical bull-horn acacias (Vachellia collinsii) despite the presence of Pseudomyrmex spinicola ants that nest in and aggressively defend the trees. We tested three hypotheses for how P. reclusus feeds on V. collinsii while avoiding ant attack: (1) chemical camouflage via cuticular surface compounds, (2) chemical deterrence via metathoracic defense glands, and (3) behavioral traits that reduce ant detection or attack. Our results showed that compounds from both P. reclusus cuticles and metathoracic glands reduce the number of ant attacks, but only cuticular compounds appear to be essential in allowing P. reclusus to feed on bull-horn acacia trees undisturbed. In addition, we found that ant attack rates to P. reclusus increased significantly when individuals were transferred between P. spinicola ant colonies. These results are consistent with the hypothesis that chemical mimicry of colony-specific ant or host plant odors plays a key role in allowing P. reclusus to circumvent ant defenses and gain access to important resources, including food and possibly enemy-free space. This interaction between ants, acacias, and their herbivores provides an excellent example of the ability of herbivores to adapt to ant defenses of plants and suggests that herbivores may play an important role in the evolution and maintenance of mutualisms. PMID:25047551

Estimation of postmortem interval based on colony development time for Anoplolepsis longipes (Hymenoptera: Formicidae).

PubMed

Goff, M L; Win, B H

1997-11-01

The postmortem interval for a set of human remains discovered inside a metal tool box was estimated using the development time required for a stratiomyid fly (Diptera: Stratiomyidae), Hermetia illucens, in combination with the time required to establish a colony of the ant Anoplolepsis longipes (Hymenoptera: Formicidae) capable of producing alate (winged) reproductives. This analysis resulted in a postmortem interval estimate of 14 + months, with a period of 14-18 months being the most probable time interval. The victim had been missing for approximately 18 months.

Spatiotemporal resource distribution and foraging strategies of ants (Hymenoptera: Formicidae)

PubMed Central

Lanan, Michele

2014-01-01

The distribution of food resources in space and time is likely to be an important factor governing the type of foraging strategy used by ants. However, no previous systematic attempt has been made to determine whether spatiotemporal resource distribution is in fact correlated with foraging strategy across the ants. In this analysis, I present data compiled from the literature on the foraging strategy and food resource use of 402 species of ants from across the phylogenetic tree. By categorizing the distribution of resources reported in these studies in terms of size relative to colony size, spatial distribution relative to colony foraging range, frequency of occurrence in time relative to worker life span, and depletability (i.e., whether the colony can cause a change in resource frequency), I demonstrate that different foraging strategies are indeed associated with specific spatiotemporal resource attributes. The general patterns I describe here can therefore be used as a framework to inform predictions in future studies of ant foraging behavior. No differences were found between resources collected via short-term recruitment strategies (group recruitment, short-term trails, and volatile recruitment), whereas different resource distributions were associated with solitary foraging, trunk trails, long-term trail networks, group raiding, and raiding. In many cases, ant species use a combination of different foraging strategies to collect diverse resources. It is useful to consider these foraging strategies not as separate options but as modular parts of the total foraging effort of a colony. PMID:25525497

Sociogenomics of Cooperation and Conflict during Colony Founding in the Fire Ant Solenopsis invicta

PubMed Central

Manfredini, Fabio; Riba-Grognuz, Oksana; Wurm, Yannick; Keller, Laurent; Shoemaker, DeWayne; Grozinger, Christina M.

2013-01-01

One of the fundamental questions in biology is how cooperative and altruistic behaviors evolved. The majority of studies seeking to identify the genes regulating these behaviors have been performed in systems where behavioral and physiological differences are relatively fixed, such as in the honey bee. During colony founding in the monogyne (one queen per colony) social form of the fire ant Solenopsis invicta, newly-mated queens may start new colonies either individually (haplometrosis) or in groups (pleometrosis). However, only one queen (the “winner”) in pleometrotic associations survives and takes the lead of the young colony while the others (the “losers”) are executed. Thus, colony founding in fire ants provides an excellent system in which to examine the genes underpinning cooperative behavior and how the social environment shapes the expression of these genes. We developed a new whole genome microarray platform for S. invicta to characterize the gene expression patterns associated with colony founding behavior. First, we compared haplometrotic queens, pleometrotic winners and pleometrotic losers. Second, we manipulated pleometrotic couples in order to switch or maintain the social ranks of the two cofoundresses. Haplometrotic and pleometrotic queens differed in the expression of genes involved in stress response, aging, immunity, reproduction and lipid biosynthesis. Smaller sets of genes were differentially expressed between winners and losers. In the second experiment, switching social rank had a much greater impact on gene expression patterns than the initial/final rank. Expression differences for several candidate genes involved in key biological processes were confirmed using qRT-PCR. Our findings indicate that, in S. invicta, social environment plays a major role in the determination of the patterns of gene expression, while the queen's physiological state is secondary. These results highlight the powerful influence of social environment on regulation of the genomic state, physiology and ultimately, social behavior of animals. PMID:23950725

Stable isotope enrichment in laboratory ant colonies: effects of colony age, metamorphosis, diet, and fat storage

USDA-ARS?s Scientific Manuscript database

Ecologists use stable isotopes to infer diets and trophic levels of animals in food webs, yet some assumptions underlying these inferences have not been thoroughly tested. We used laboratory-reared colonies of Solenopsis invicta Buren (Formicidae: Solenopsidini) to test the effects of metamorphosis,...

Estimating timber losses from a town ant colony with aerial photographs

Treesearch

John C. Moser

1986-01-01

Aerial photographs were used to locate an individual nest of Atta texana (Buckley) and to estimate the area of damage in a plantation of loblolly pine (Pinus taeda L.). Stumpage loss from the nest over a period of 30 years was estimated to be $653.

Ant-like task allocation and recruitment in cooperative robots

NASA Astrophysics Data System (ADS)

Krieger, Michael J. B.; Billeter, Jean-Bernard; Keller, Laurent

2000-08-01

One of the greatest challenges in robotics is to create machines that are able to interact with unpredictable environments in real time. A possible solution may be to use swarms of robots behaving in a self-organized manner, similar to workers in an ant colony. Efficient mechanisms of division of labour, in particular series-parallel operation and transfer of information among group members, are key components of the tremendous ecological success of ants. Here we show that the general principles regulating division of labour in ant colonies indeed allow the design of flexible, robust and effective robotic systems. Groups of robots using ant-inspired algorithms of decentralized control techniques foraged more efficiently and maintained higher levels of group energy than single robots. But the benefits of group living decreased in larger groups, most probably because of interference during foraging. Intriguingly, a similar relationship between group size and efficiency has been documented in social insects. Moreover, when food items were clustered, groups where robots could recruit other robots in an ant-like manner were more efficient than groups without information transfer, suggesting that group dynamics of swarms of robots may follow rules similar to those governing social insects.

Vitellogenin Underwent Subfunctionalization to Acquire Caste and Behavioral Specific Expression in The Harvester Ant Pogonomyrmex barbatus

USDA-ARS?s Scientific Manuscript database

Similarly to others advanced social insects, ants and bees have an age-associated division of labor, whereby young workers normally perform tasks inside the colony and old workers forage outside the nest, but this pattern is more variable in ants. It is unknown whether, notwithstanding their differe...

Dissecting ant recognition systems in the age of genomics.

PubMed

Tsutsui, Neil D

2013-01-01

Hamilton is probably best known for his seminal work demonstrating the role of kin selection in social evolution. His work made it clear that, for individuals to direct their altruistic behaviours towards appropriate recipients (kin), mechanisms must exist for kin recognition. In the social insects, colonies are typically comprised of kin, and colony recognition cues are used as proxies for kinship cues. Recent years have brought rapid advances in our understanding of the genetic and molecular mechanisms that are used for this process. Here, I review some of the most notable advances, particularly the contributions from recent ant genome sequences and molecular biology.

The evolution of intermediate castration virulence and ant coexistence in a spatially structured environment.

PubMed

Szilágyi, András; Scheuring, István; Edwards, David P; Orivel, Jerome; Yu, Douglas W

2009-12-01

Theory suggests that spatial structuring should select for intermediate levels of virulence in parasites, but empirical tests are rare and have never been conducted with castration (sterilizing) parasites. To test this theory in a natural landscape, we construct a spatially explicit model of the symbiosis between the ant-plant Cordia nodosa and its two, protecting ant symbionts, Allomerus and Azteca. Allomerus is also a castration parasite, preventing fruiting to increase colony fecundity. Limiting the dispersal of Allomerus and host plant selects for intermediate castration virulence. Increasing the frequency of the mutualist, Azteca, selects for higher castration virulence in Allomerus, because seeds from Azteca-inhabited plants are a public good that Allomerus exploits. These results are consistent with field observations and, to our knowledge, provide the first empirical evidence supporting the hypothesis that spatial structure can reduce castration virulence and the first such evidence in a natural landscape for either mortality or castration virulence.

Young fire ant workers feign death and survive aggressive neighbors

NASA Astrophysics Data System (ADS)

Cassill, Deby L.; Vo, Kim; Becker, Brandie

2008-07-01

Feigning death is a method of self-defense employed among a wide range of prey species when threatened by predator species. This paper reports on death-feigning behavior by the fire ant, Solenopsis invicta, during intraspecific aggression among neighboring fire ant workers. Days-old workers responded to aggression by death feigning, weeks-old workers responded by fleeing and months-old workers responded by fighting back. By feigning death, days-old workers were four times more likely to survive aggression than older workers. From a proximate perspective, retaliation by young workers against aggressive older workers is certain to fail. With their relatively soft exoskeleton, young workers would be prone to injury and death and unable to execute an effective attack of biting or stinging older workers with harder exoskeletons. From an ultimate perspective, death feigning allows young workers to survive and contribute to brood care and colony growth, both of which are essential to queen survival and fitness.

Neurohormonal changes associated with ritualized combat and the formation of a reproductive hierarchy in the ant Harpegnathos saltator

USDA-ARS?s Scientific Manuscript database

Dominance rank in animal societies is correlated with changes in both reproductive physiology and behavior. In some social insects, dominance status is used to determine a reproductive division of labor, where a few colony members reproduce while most remain functionally sterile. Changes in reproduc...

A Study of Blackfly (Aphis fabae Scop.) on Broad Bean plants, and of Insects Associated Directly or Indirectly with the Colony

ERIC Educational Resources Information Center

Backhouse, Mary

1972-01-01

Describes the results of a study of the ecology of the bean plant/aphid/ant/associated insects/fungi system and suggests a series of experiments that secondary school students could undertake by observing or manipulating this system. (Species recorded are British) (AL)

An ant-plant by-product mutualism is robust to selective logging of rain forest and conversion to oil palm plantation.

PubMed

Fayle, Tom M; Edwards, David P; Foster, William A; Yusah, Kalsum M; Turner, Edgar C

2015-06-01

Anthropogenic disturbance and the spread of non-native species disrupt natural communities, but also create novel interactions between species. By-product mutualisms, in which benefits accrue as side effects of partner behaviour or morphology, are often non-specific and hence may persist in novel ecosystems. We tested this hypothesis for a two-way by-product mutualism between epiphytic ferns and their ant inhabitants in the Bornean rain forest, in which ants gain housing in root-masses while ferns gain protection from herbivores. Specifically, we assessed how the specificity (overlap between fern and ground-dwelling ants) and the benefits of this interaction are altered by selective logging and conversion to an oil palm plantation habitat. We found that despite the high turnover of ant species, ant protection against herbivores persisted in modified habitats. However, in ferns growing in the oil palm plantation, ant occupancy, abundance and species richness declined, potentially due to the harsher microclimate. The specificity of the fern-ant interactions was also lower in the oil palm plantation habitat than in the forest habitats. We found no correlations between colony size and fern size in modified habitats, and hence no evidence for partner fidelity feedbacks, in which ants are incentivised to protect fern hosts. Per species, non-native ant species in the oil palm plantation habitat (18 % of occurrences) were as important as native ones in terms of fern protection and contributed to an increase in ant abundance and species richness with fern size. We conclude that this by-product mutualism persists in logged forest and oil palm plantation habitats, with no detectable shift in partner benefits. Such persistence of generalist interactions in novel ecosystems may be important for driving ecosystem functioning.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

Cost- and reliability-oriented aggregation point association in long-term evolution and passive optical network hybrid access infrastructure for smart grid neighborhood area network

NASA Astrophysics Data System (ADS)

Cheng, Xiao; Feng, Lei; Zhou, Fanqin; Wei, Lei; Yu, Peng; Li, Wenjing

2018-02-01

With the rapid development of the smart grid, the data aggregation point (AP) in the neighborhood area network (NAN) is becoming increasingly important for forwarding the information between the home area network and wide area network. Due to limited budget, it is unable to use one-single access technology to meet the ongoing requirements on AP coverage. This paper first introduces the wired and wireless hybrid access network with the integration of long-term evolution (LTE) and passive optical network (PON) system for NAN, which allows a good trade-off among cost, flexibility, and reliability. Then, based on the already existing wireless LTE network, an AP association optimization model is proposed to make the PON serve as many APs as possible, considering both the economic efficiency and network reliability. Moreover, since the features of the constraints and variables of this NP-hard problem, a hybrid intelligent optimization algorithm is proposed, which is achieved by the mixture of the genetic, ant colony and dynamic greedy algorithm. By comparing with other published methods, simulation results verify the performance of the proposed method in improving the AP coverage and the performance of the proposed algorithm in terms of convergence.

Viruses of invasive Argentine ants from the European Main supercolony: characterization, interactions and evolution.

PubMed

Viljakainen, Lumi; Holmberg, Ida; Abril, Sílvia; Jurvansuu, Jaana

2018-06-25

The Argentine ant (Linepithema humile) is a highly invasive pest, yet very little is known about its viruses. We analysed individual RNA-sequencing data from 48 Argentine ant queens to identify and characterisze their viruses. We discovered eight complete RNA virus genomes - all from different virus families - and one putative partial entomopoxvirus genome. Seven of the nine virus sequences were found from ant samples spanning 7 years, suggesting that these viruses may cause long-term infections within the super-colony. Although all nine viruses successfully infect Argentine ants, they have very different characteristics, such as genome organization, prevalence, loads, activation frequencies and rates of evolution. The eight RNA viruses constituted in total 23 different virus combinations which, based on statistical analysis, were non-random, suggesting that virus compatibility is a factor in infections. We also searched for virus sequences from New Zealand and Californian Argentine ant RNA-sequencing data and discovered that many of the viruses are found on different continents, yet some viruses are prevalent only in certain colonies. The viral loads described here most probably present a normal asymptomatic level of infection; nevertheless, detailed knowledge of Argentine ant viruses may enable the design of viral biocontrol methods against this pest.

Ant brood function as life preservers during floods.

PubMed

Purcell, Jessica; Avril, Amaury; Jaffuel, Geoffrey; Bates, Sarah; Chapuisat, Michel

2014-01-01

Social organisms can surmount many ecological challenges by working collectively. An impressive example of such collective behavior occurs when ants physically link together into floating 'rafts' to escape from flooded habitat. However, raft formation may represent a social dilemma, with some positions posing greater individual risks than others. Here, we investigate the position and function of different colony members, and the costs and benefits of this functional geometry in rafts of the floodplain-dwelling ant Formica selysi. By causing groups of ants to raft in the laboratory, we observe that workers are distributed throughout the raft, queens are always in the center, and 100% of brood items are placed on the base. Through a series of experiments, we show that workers and brood are extremely resistant to submersion. Both workers and brood exhibit high survival rates after they have rafted, suggesting that occupying the base of the raft is not as costly as expected. The placement of all brood on the base of one cohesive raft confers several benefits: it preserves colony integrity, takes advantage of brood buoyancy, and increases the proportion of workers that immediately recover after rafting.

A Y-like social chromosome causes alternative colony organization in fire ants

USDA-ARS?s Scientific Manuscript database

Intraspecific variability in social organization is common, yet the underlying causes are rarely known1-3. In the fire ant Solenopsis invicta, the existence of two divergent forms of social organisation is under the control of a single Mendelian genomic element marked by two variants of an odorant b...

Plant resources and colony growth in an invasive ant: the importance of honeydew-producing Hemiptera in carbohydrate transfer across trophic levels.

PubMed

Helms, Ken R; Vinson, S Bradleigh

2008-04-01

Studies have suggested that plant-based nutritional resources are important in promoting high densities of omnivorous and invasive ants, but there have been no direct tests of the effects of these resources on colony productivity. We conducted an experiment designed to determine the relative importance of plants and honeydew-producing insects feeding on plants to the growth of colonies of the invasive ant Solenopsis invicta (Buren). We found that colonies of S. invicta grew substantially when they only had access to unlimited insect prey; however, colonies that also had access to plants colonized by honeydew-producing Hemiptera grew significantly and substantially ( approximately 50%) larger. Our experiment also showed that S. invicta was unable to acquire significant nutritional resources directly from the Hemiptera host plant but acquired them indirectly from honeydew. Honeydew alone is unlikely to be sufficient for colony growth, however, and both carbohydrates abundant in plants and proteins abundant in animals are likely to be necessary for optimal growth. Our experiment provides important insight into the effects of a common tritrophic interaction among an invasive mealybug, Antonina graminis (Maskell), an invasive host grass, Cynodon dactylon L. Pers., and S. invicta in the southeastern United States, suggesting that interactions among these species can be important in promoting extremely high population densities of S. invicta.

Gene selection for cancer classification with the help of bees.

PubMed

Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

2016-08-10

Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

How many gamergates is an ant queen worth?

NASA Astrophysics Data System (ADS)

Monnin, Thibaud; Peeters, Christian

2008-02-01

Ant reproductives exhibit different morphological adaptations linked to dispersal and fertility. By reviewing the literature on taxa where workers can reproduce sexually (i.e. become gamergates) we show that (1) species with a single gamergate generally have lost the winged queen caste, whereas only half of the species with several gamergates have, and (2) single-gamergate species have smaller colonies than multiple-gamergate species. Comparison with “classical” ants without gamergates, where having one vs having several winged queens are two distinct syndromes, suggests that having one vs having several gamergates are not. Gamergate number does not affect the success of colony fission, but retention of the queen caste permits the option of independent foundation.

Thelytokous parthenogenesis by queens in the dacetine ant Pyramica membranifera (Hymenoptera: Formicidae).

PubMed

Ito, Fuminori; Touyama, Yoshifumi; Gotoh, Ayako; Kitahiro, Shungo; Billen, Johan

2010-08-01

Thelytokous parthenogenesis in which diploid females are produced from unfertilized eggs, was recently reported for some ant species. Here, we document thelytokous reproduction by queens in the polygynous species Pyramica membranifera. Queens that emerged in the laboratory were kept with or without workers under laboratory conditions. Independent colony founding was successful for a few queens if prey was provided. All artificial colonies, which started with a newly emerged queen and workers produced new workers and some of the colonies also produced female sexuals. Some of the female sexuals shed their wings in the laboratory and started formation of new polygynous colonies. Workers had no ovaries and thus, were obligatorily sterile.

Predation by ants controls swallow bug (Hemiptera: Cimicidae: Oeciacus vicarius) infestations.

PubMed

Brown, Charles R; Page, Catherine E; Robison, Grant A; O'Brien, Valerie A; Booth, Warren

2015-06-01

The swallow bug (Oeciacus vicarius) is the only known vector for Buggy Creek virus (BCRV), an alphavirus that circulates in cliff swallows (Petrochelidon pyrrhonota) and house sparrows (Passer domesticus) in North America. We discovered ants (Crematogaster lineolata and Formica spp.) preying on swallow bugs at cliff swallow colonies in western Nebraska, U.S.A. Ants reduced the numbers of visible bugs on active swallow nests by 74-90%, relative to nests in the same colony without ants. Ant predation on bugs had no effect on the reproductive success of cliff swallows inhabiting the nests where ants foraged. Ants represent an effective and presumably benign way of controlling swallow bugs at nests in some colonies. They may constitute an alternative to insecticide use at sites where ecologists wish to remove the effects of swallow bugs on cliff swallows or house sparrows. By reducing bug numbers, ant presence may also lessen BCRV transmission at the spatial foci (bird colony sites) where epizootics occur. The effect of ants on swallow bugs should be accounted for in studying variation among sites in vector abundance. © 2015 The Society for Vector Ecology.

Limiting spread of a unicolonial invasive insect and characterization of seasonal patterns of range expansion

USGS Publications Warehouse

Krushelnycky, Paul D.; Loope, Lloyd L.; Joe, Stephanie M.

2004-01-01

Limiting dispersal is a fundamental strategy in the control of invasive species, and in certain situations containment of incipient populations may be an important management technique. To test the feasibility of slowing the rapid spread of two Argentine ant (Linepithema humile) supercolonies in Haleakala National Park, Hawaii, we applied ant bait and toxicant within an experimental plot situated along a supercolony boundary. The 120×260 m plot simulated a small section of what could potentially be a 120 m wide treatment encompassing the entire expanding boundaries of both supercolonies. Foraging ant numbers at baited monitoring stations decreased sharply within two weeks after treatment, and ant spread was completely halted within the plot for at least one year. In contrast, an adjacent untreated colony boundary advanced an average of 65.2 m over the course of 1 year. Most of this spread took place in the summer and fall, at the time of highest ant abundance at bait monitoring stations, while no outward dispersal occurred during the spring and early summer. These patterns are consistent with the hypothesis that local budding dispersal in this unicolonial species stems from density dependent pressure rather than inherent founding behavior associated with mating. Based on results from this experiment, we are investigating the effectiveness of annual boundary treatments in slowing the Argentine ant invasion at Haleakala National Park. The goals of this program are to protect populations of native arthropods and to keep options open for eventual attempts at eradication.

Evaluation of Liquid and Bait Insecticides against the Dark Rover Ant (Brachymyrmex patagonicus)

PubMed Central

Miguelena, Javier G.; Baker, Paul B.

2014-01-01

Dark rover ants (Brachymyrmex patagonicus, Mayr) are an exotic ant species native to South America that has recently spread through the southern US. We evaluated the residual activity of three liquid insecticides (indoxacarb, fipronil and lambda-cyhalothrin) as potential barrier treatments against these ants. The factors we considered include the use of a porous or non-porous surface, a short or long exposure time and the changes in insecticide activity after treatment during a 90 day period. We also tested the effect of baits containing three different active ingredients (imidacloprid, sodium tetraborate and indoxacarb) on colony fragments of this species for a 15 day period. Both lambda-cyhalothrin® and indoxacarb® resulted in high levels of ant mortality up to 90 days after application. The results of exposure to fipronil® resembled those from the control treatment. Application of insecticides on a porous surface and the shorter exposure time generally resulted in greater ant survival. Of the baits tested, only the imidacloprid based one decreased ant survival significantly during the evaluation period. Within three days, the imidacloprid bait produced over 50% mortality which increased to over 95% by the end of the experiment. Results from the other two bait treatments were not significantly different from the control. PMID:26462943

Isolation of a pyrazine alarm pheromone component from the fire ant, Solenopsis invicta.

PubMed

Vander Meer, Robert K; Preston, Catherine A; Choi, Man-Yeon

2010-02-01

Alarm pheromones in social insects are an essential part of a complex of pheromone interactions that contribute to the maintenance of colony integrity and sociality. The alarm pheromones of ants were among the first examples of animal pheromones identified, primarily because of the large amount of chemical produced and the distinctive responses of ants to the pheromone. However, the alarm pheromone of the fire ant, Solenopsis invicta, eluded identification for over four decades. We identified 2-ethyl-3,6-dimethylpyrazine as an alarm pheromone component of S. invicta. Worker fire ants detect the pyrazine alarm pheromone at 30 pg/ml, which is comparable to alarm pheromone sensitivities reported for other ant species. The source of this alarm pheromone are the mandibular glands, which, in fire ants, are not well developed and contain only about 300 pg of the compound, much less than the microgram quantities of alarm pheromones reported for several other ant species. Female and male sexuals and workers produce the pyrazine, which suggests that it may be involved in fire ant mating flight initiation, as well as the typical worker alarm response. This is the first report of 2-ethyl-3,6-dimethylpyrazine from a Solenopsis species and the first example of this alkaloid functioning as an alarm pheromone.

Thelytokous parthenogenesis by queens in the dacetine ant Pyramica membranifera (Hymenoptera: Formicidae)

NASA Astrophysics Data System (ADS)

Ito, Fuminori; Touyama, Yoshifumi; Gotoh, Ayako; Kitahiro, Shungo; Billen, Johan

2010-08-01

Thelytokous parthenogenesis in which diploid females are produced from unfertilized eggs, was recently reported for some ant species. Here, we document thelytokous reproduction by queens in the polygynous species Pyramica membranifera. Queens that emerged in the laboratory were kept with or without workers under laboratory conditions. Independent colony founding was successful for a few queens if prey was provided. All artificial colonies, which started with a newly emerged queen and workers produced new workers and some of the colonies also produced female sexuals. Some of the female sexuals shed their wings in the laboratory and started formation of new polygynous colonies. Workers had no ovaries and thus, were obligatorily sterile.

Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ketabchi, Hamed

2017-12-01

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs.

Marking individual ants for behavioral sampling in a laboratory colony.

PubMed

Holbrook, C Tate

2009-07-01

Ant societies are tractable and malleable, two features that make them ideal models for probing the organization of complex biological systems. The ability to identify specific individuals while they function as part of a colony permits an integrative analysis of social complexity, including self-organizational processes (i.e., how individual-level properties and social interactions give rise to emergent, colony-level attributes such as division of labor and collective decision making). Effects of genotype, nutrition, and physiology on individual behavior and the organization of work also can be investigated in this manner, through correlative and manipulative approaches. Moreover, aspects of colony demography (e.g., colony size, and age and size distributions of workers) can be altered experimentally to examine colony development and regulatory mechanisms underlying colony homeostasis and resiliency. This protocol describes how to sample the behavior of ants living in a colony under laboratory conditions. Specifically, it outlines how to identify and observe individuals within a colony, an approach that can be used to quantify individual- and colony-level patterns of behavior. When a lower-resolution measure of overall group behavior is desired, individual identities might not be required. Given the diversity of ants and their study, this protocol provides a very general methodology; the details can be modified according to the body size, colony size, and ecology of the focal species, as well as to specific research aims. These basic techniques can also be extended to more advanced experimental designs such as manipulation of colony demography and hormone treatment.

Imperfect chemical female mimicry in males of the ant Cardiocondyla obscurior

NASA Astrophysics Data System (ADS)

Cremer, Sylvia; D'Ettorre, Patrizia; Drijfhout, Falko P.; Sledge, Matthew F.; Turillazzi, Stefano; Heinze, Jürgen

2008-11-01

Winged and wingless males coexist in the ant Cardiocondyla obscurior. Wingless (“ergatoid”) males never leave their maternal colony and fight remorselessly among each other for the access to emerging females. The peaceful winged males disperse after about 10 days, but beforehand also mate in the nest. In the first 5 days of their life, winged males perform a chemical female mimicry that protects them against attack and even makes them sexually attractive to ergatoid males. When older, the chemical profile of winged males no longer matches that of virgin females; nevertheless, they are still tolerated, which so far has been puzzling. Contrasting this general pattern, we have identified a single aberrant colony in which all winged males were attacked and killed by the ergatoid males. A comparative analysis of the morphology and chemical profile of these untypical attacked winged males and the tolerated males from several normal colonies revealed that normal old males are still performing some chemical mimicry to the virgin queens, though less perfect than in their young ages. The anomalous attacked winged males, on the other hand, had a very different odour to the females. Our study thus exemplifies that the analysis of rare malfunctioning can add valuable insight on functioning under normal conditions and allows the conclusion that older winged males from normal colonies of the ant C. obscurior are guarded through an imperfect chemical female mimicry, still close enough to protect against attacks by the wingless fighters yet dissimilar enough not to elicit their sexual interest.

Pseudacteon decapitating fly parasitism rates in fire ant colonies around Gainesville, Florida

USDA-ARS?s Scientific Manuscript database

In order to assess the impacts of phorid flies on fire ants in the Gainesville area, we collected 3 g of worker ants from 36 colonies. A total of 672 parasitized workers were recovered from the 36 colony samples. Confirmed parasitism rates ranged from 0-5% with an average of about 0.5%. Including c...

Differentiating causality and correlation in allometric scaling: ant colony size drives metabolic hypometry

PubMed Central

Ochs, Alison; Fewell, Jennifer H.; Harrison, Jon F.

2017-01-01

Metabolic rates of individual animals and social insect colonies generally scale hypometrically, with mass-specific metabolic rates decreasing with increasing size. Although this allometry has wide ranging effects on social behaviour, ecology and evolution, its causes remain controversial. Because it is difficult to experimentally manipulate body size of organisms, most studies of metabolic scaling depend on correlative data, limiting their ability to determine causation. To overcome this limitation, we experimentally reduced the size of harvester ant colonies (Pogonomyrmex californicus) and quantified the consequent increase in mass-specific metabolic rates. Our results clearly demonstrate a causal relationship between colony size and hypometric changes in metabolic rate that could not be explained by changes in physical density. These findings provide evidence against prominent models arguing that the hypometric scaling of metabolic rate is primarily driven by constraints on resource delivery or surface area/volume ratios, because colonies were provided with excess food and colony size does not affect individual oxygen or nutrient transport. We found that larger colonies had lower median walking speeds and relatively more stationary ants and including walking speed as a variable in the mass-scaling allometry greatly reduced the amount of residual variation in the model, reinforcing the role of behaviour in metabolic allometry. Following the experimental size reduction, however, the proportion of stationary ants increased, demonstrating that variation in locomotory activity cannot solely explain hypometric scaling of metabolic rates in these colonies. Based on prior studies of this species, the increase in metabolic rate in size-reduced colonies could be due to increased anabolic processes associated with brood care and colony growth. PMID:28228514

Founding weaver ant queens (Oecophylla longinoda) increase production and nanitic worker size when adopting non-nestmate pupae.

PubMed

Ouagoussounon, Issa; Offenberg, Joachim; Sinzogan, Antonio; Adandonon, Appolinaire; Kossou, Dansou; Vayssières, Jean-François

2015-01-01

Weaver ants (Oecophylla longinoda Latreille) are used commercially to control pest insects and for protein production. In this respect fast colony growth is desirable for managed colonies. Transplantation of non-nestmate pupae to incipient colonies has been shown to boost colony growth. Our objectives were to find the maximum number of pupae a founding queen can handle, and to measure the associated colony growth. Secondly, we tested if transplantation of pupae led to production of larger nanitic workers (defined as unusually small worker ants produced by founding queens in their first batch of offspring). Forty-five fertilized queens were divided into three treatments: 0 (control), 100 or 300 non-nestmate pupae transplanted to each colony. Pupae transplantation resulted in highly increased growth rates, as pupae were readily adopted by the queens and showed high proportions of surviving (mean = 76%). However, survival was significantly higher when 100 pupae were transplanted compared to transplantation of 300 pupae, indicating that queens were unable to handle 300 pupae adequately and that pupae require some amount of nursing. Nevertheless, within the 60-day experiment the transplantation of 300 pupae increased total colony size more than 10-fold whereas 100 pupae increased the size 5.6 fold, compared to control. This increase was due not only to the individuals added in the form of pupae but also to an increased per capita brood production by the resident queen, triggered by the adopted pupae. The size of hatching pupae produced by the resident queen also increased with the number of pupae transplanted, leading to larger nanitic workers in colonies adopting pupae. In conclusion, pupae transplantation may be used to produce larger colonies with larger worker ants and may thus reduce the time to produce weaver ant colonies for commercial purposes. This in turn may facilitate the implementation of the use of weaver ants.

Harnessing ant defence at fruits reduces bruchid seed predation in a symbiotic ant–plant mutualism

PubMed Central

Pringle, Elizabeth G.

2014-01-01

In horizontally transmitted mutualisms, mutualists disperse separately and reassemble in each generation with partners genetically unrelated to those in the previous generation. Because of this, there should be no selection on either partner to enhance the other's reproductive output directly. In symbiotic ant–plant mutualisms, myrmecophytic plants host defensive ant colonies, and ants defend the plants from herbivores. Plants and ants disperse separately, and, although ant defence can indirectly increase plant reproduction by reducing folivory, it is unclear whether ants can also directly increase plant reproduction by defending seeds. The neotropical tree Cordia alliodora hosts colonies of Azteca pittieri ants. The trees produce domatia where ants nest at stem nodes and also at the node between the peduncle and the rachides of the infloresence. Unlike the stem domatia, these reproductive domatia senesce after the tree fruits each year. In this study, I show that the tree's resident ant colony moves into these ephemeral reproductive domatia, where they tend honeydew-producing scale insects and patrol the nearby developing fruits. The presence of ants significantly reduced pre-dispersal seed predation by Amblycerus bruchid beetles, thereby directly increasing plant reproductive output. PMID:24807259

Evolution of thorax architecture in ant castes highlights trade-off between flight and ground behaviors.

PubMed

Keller, Roberto A; Peeters, Christian; Beldade, Patrícia

2014-01-01

The concerted evolution of morphological and behavioral specializations has compelling examples in ant castes. Unique to ants is a marked divergence between winged queens and wingless workers, but morphological specializations for behaviors on the ground have been overlooked. We analyzed thorax morphology of queens and workers in species from 21 of the 25 ant subfamilies. We uncovered unique skeletomuscular modifications in workers that presumably increase power and flexibility of head-thorax articulation, emphasizing that workers are not simply wingless versions of queens. We also identified two distinct types of queens and showed repeated evolutionary associations with strategies of colony foundation. Solitary founding queens that hunt have a more worker-like thorax. Our results reveal that ants invest in the relative size of thorax segments according to their tasks. Versatility of head movements allows for better manipulation of food and objects, which arguably contributed to the ants' ecological and evolutionary success. DOI: http://dx.doi.org/10.7554/eLife.01539.001.

Evolution of thorax architecture in ant castes highlights trade-off between flight and ground behaviors

PubMed Central

Keller, Roberto A; Peeters, Christian; Beldade, Patrícia

2014-01-01

The concerted evolution of morphological and behavioral specializations has compelling examples in ant castes. Unique to ants is a marked divergence between winged queens and wingless workers, but morphological specializations for behaviors on the ground have been overlooked. We analyzed thorax morphology of queens and workers in species from 21 of the 25 ant subfamilies. We uncovered unique skeletomuscular modifications in workers that presumably increase power and flexibility of head–thorax articulation, emphasizing that workers are not simply wingless versions of queens. We also identified two distinct types of queens and showed repeated evolutionary associations with strategies of colony foundation. Solitary founding queens that hunt have a more worker-like thorax. Our results reveal that ants invest in the relative size of thorax segments according to their tasks. Versatility of head movements allows for better manipulation of food and objects, which arguably contributed to the ants’ ecological and evolutionary success. DOI: http://dx.doi.org/10.7554/eLife.01539.001 PMID:24399458

Facultative slave-making ants Formica sanguinea label their slaves with own recognition cues instead of employing the strategy of chemical mimicry.

PubMed

Włodarczyk, Tomasz; Szczepaniak, Lech

2017-01-01

Slave-making ant species use the host workforce to ensure normal colony functioning. Slaves are robbed as pupae from their natal nest and after eclosion, assume the parasite colony as their own. A possible factor promoting the successful integration of slaves into a foreign colony is congruence with the slave-makers in terms of cuticular hydrocarbons, which are known to play the role of recognition cues in social insects. Such an adaptation is observed in the obligate slave-making ant species, which are chemically adjusted to their slaves. To date, however, no reports have been available on facultative slave-making species, which represent an earlier stage of the evolution of slavery. Such an example is Formica sanguinea, which exploit F. fusca colonies as their main source of a slave workforce. Our results show that F. sanguinea ants have a distinct cuticular hydrocarbon profile, which contains compounds not present in free-living F. fusca ants from potential target nests. Moreover, enslaved F. fusca ants acquire hydrocarbons from their slave-making nestmates to such an extent that they become chemically differentiated from free-living, conspecific ants. Our study shows that F. sanguinea ants promote their own recognition cues in their slaves, rather than employing the strategy of chemical mimicry. Possible reasons why F. sanguinea is not chemically well adjusted to its main host species are discussed in this paper. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical and behavioral integration of army ant-associated rove beetles - a comparison between specialists and generalists.

PubMed

von Beeren, Christoph; Brückner, Adrian; Maruyama, Munetoshi; Burke, Griffin; Wieschollek, Jana; Kronauer, Daniel J C

2018-01-01

Host-symbiont interactions are embedded in ecological communities and range from unspecific to highly specific relationships. Army ants and their arthropod guests represent a fascinating example of species-rich host-symbiont associations where host specificity ranges across the entire generalist - specialist continuum. In the present study, we compared the behavioral and chemical integration mechanisms of two extremes of the generalist - specialist continuum: generalist ant-predators in the genus Tetradonia (Staphylinidae: Aleocharinae: Athetini), and specialist ant-mimics in the genera Ecitomorpha and Ecitophya (Staphylinidae: Aleocharinae: Ecitocharini). Similar to a previous study of Tetradonia beetles, we combined DNA barcoding with morphological studies to define species boundaries in ant-mimicking beetles. This approach found four ant-mimicking species at our study site at La Selva Biological Station in Costa Rica. Community sampling of Eciton army ant parasites revealed that ant-mimicking beetles were perfect host specialists, each beetle species being associated with a single Eciton species. These specialists were seamlessly integrated into the host colony, while generalists avoided physical contact to host ants in behavioral assays. Analysis of the ants' nestmate recognition cues, i.e. cuticular hydrocarbons (CHCs), showed close similarity in CHC composition and CHC concentration between specialists and Eciton burchellii foreli host ants. On the contrary, the chemical profiles of generalists matched host profiles less well, indicating that high accuracy in chemical host resemblance is only accomplished by socially integrated species. Considering the interplay between behavior, morphology, and cuticular chemistry, specialists but not generalists have cracked the ants' social code with respect to various sensory modalities. Our results support the long-standing idea that the evolution of host-specialization in parasites is a trade-off between the range of potential host species and the level of specialization on any particular host.

A review of myrmecophily in ant nest beetles (Coleoptera: Carabidae: Paussinae): linking early observations with recent findings

NASA Astrophysics Data System (ADS)

Geiselhardt, Stefanie F.; Peschke, Klaus; Nagel, Peter

2007-11-01

Myrmecophily provides various examples of how social structures can be overcome to exploit vast and well-protected resources. Ant nest beetles (Paussinae) are particularly well suited for ecological and evolutionary considerations in the context of association with ants because life habits within the subfamily range from free-living and predatory in basal taxa to obligatory myrmecophily in derived Paussini. Adult Paussini are accepted in the ant society, although parasitising the colony by preying on ant brood. Host species mainly belong to the ant families Myrmicinae and Formicinae, but at least several paussine genera are not host-specific. Morphological adaptations, such as special glands and associated tufts of hair (trichomes), characterise Paussini as typical myrmecophiles and lead to two different strategical types of body shape: while certain Paussini rely on the protective type with less exposed extremities, other genera access ant colonies using glandular secretions and trichomes (symphile type). We compare these adaptations with other taxonomic groups of insects by joining contemporary research and early sources and discuss the possibility of an attracting or appeasing effect of the secretion. Species that are ignored by their host ants might use chemical mimicry instead. Furthermore, vibrational signals may contribute to ant-beetle communication, and chemical signals have proven to play a role in host finding. The powerful defense chemistry of paussines as “bombardier beetles” is not used in contact with host ants. We attempt to trace the evolution of myrmecophily in paussines by reviewing important aspects of the association between paussine beetles and ants, i.e. morphological and potential chemical adaptations, life cycle, host specificity, alimentation, parasitism and sound production.

Arms races and the evolution of big fierce societies.

PubMed

Boswell, G P; Franks, N R; Britton, N F

2001-08-22

The causes of biological gigantism have received much attention, but only for individual organisms. What selection pressures might favour the evolution of gigantic societies? Here we consider the largest single-queen insect societies, those of the Old World army ant Dorylus, single colonies of which can have 20 million workers. We propose that colony gigantism in Dorylus arises as a result of an arms race and test this prediction by developing a size-structured mathematical model. We use this model for exploring and potentially explaining differences in colony size, colony aggression and colony propagation strategies in populations of New World army ants Eciton and Old World army ants Dorylus. The model shows that, by determining evolutionarily stable strategies (ESSs), differences in the trophic levels at which these army ants live feed forwards into differences in their densities and collision rates and, hence, into different strategies of growth, aggression and propagation. The model predicts large colony size and the occurrence of battles and a colony-propagation strategy involving highly asymmetrical divisions in Dorylus and that Eciton colonies should be smaller, non-combative and exhibit equitable binary fission. These ESSs are in excellent agreement with field observations and demonstrate that gargantuan societies can arise through arms races.

A cuckoo-like parasitic moth leads African weaver ant colonies to their ruin

PubMed Central

Dejean, Alain; Orivel, Jérôme; Azémar, Frédéric; Hérault, Bruno; Corbara, Bruno

2016-01-01

In myrmecophilous Lepidoptera, mostly lycaenids and riodinids, caterpillars trick ants into transporting them to the ant nest where they feed on the brood or, in the more derived “cuckoo strategy”, trigger regurgitations (trophallaxis) from the ants and obtain trophic eggs. We show for the first time that the caterpillars of a moth (Eublemma albifascia; Noctuidae; Acontiinae) also use this strategy to obtain regurgitations and trophic eggs from ants (Oecophylla longinoda). Females short-circuit the adoption process by laying eggs directly on the ant nests, and workers carry just-hatched caterpillars inside. Parasitized colonies sheltered 44 to 359 caterpillars, each receiving more trophallaxis and trophic eggs than control queens. The thus-starved queens lose weight, stop laying eggs (which transport the pheromones that induce infertility in the workers) and die. Consequently, the workers lay male-destined eggs before and after the queen’s death, allowing the colony to invest its remaining resources in male production before it vanishes. PMID:27021621

Tolerating an infection: an indirect benefit of co-founding queen associations in the ant Lasius niger

NASA Astrophysics Data System (ADS)

Pull, Christopher D.; Hughes, William O. H.; Brown, Mark J. F.

2013-12-01

Pathogens exert a strong selection pressure on organisms to evolve effective immune defences. In addition to individual immunity, social organisms can act cooperatively to produce collective defences. In many ant species, queens have the option to found a colony alone or in groups with other, often unrelated, conspecifics. These associations are transient, usually lasting only as long as each queen benefits from the presence of others. In fact, once the first workers emerge, queens fight to the death for dominance. One potential advantage of co-founding may be that queens benefit from collective disease defences, such as mutual grooming, that act against common soil pathogens. We test this hypothesis by exposing single and co-founding queens to a fungal parasite, in order to assess whether queens in co-founding associations have improved survival. Surprisingly, co-foundresses exposed to the entomopathogenic fungus Metarhizium did not engage in cooperative disease defences, and consequently, we find no direct benefit of multiple queens on survival. However, an indirect benefit was observed, with parasite-exposed queens producing more brood when they co-founded, than when they were alone. We suggest this is due to a trade-off between reproduction and immunity. Additionally, we report an extraordinary ability of the queens to tolerate an infection for long periods after parasite exposure. Our study suggests that there are no social immunity benefits for co-founding ant queens, but that in parasite-rich environments, the presence of additional queens may nevertheless improve the chances of colony founding success.

Ant Brood Function as Life Preservers during Floods

PubMed Central

Purcell, Jessica; Avril, Amaury; Jaffuel, Geoffrey; Bates, Sarah; Chapuisat, Michel

2014-01-01

Social organisms can surmount many ecological challenges by working collectively. An impressive example of such collective behavior occurs when ants physically link together into floating ‘rafts’ to escape from flooded habitat. However, raft formation may represent a social dilemma, with some positions posing greater individual risks than others. Here, we investigate the position and function of different colony members, and the costs and benefits of this functional geometry in rafts of the floodplain-dwelling ant Formica selysi. By causing groups of ants to raft in the laboratory, we observe that workers are distributed throughout the raft, queens are always in the center, and 100% of brood items are placed on the base. Through a series of experiments, we show that workers and brood are extremely resistant to submersion. Both workers and brood exhibit high survival rates after they have rafted, suggesting that occupying the base of the raft is not as costly as expected. The placement of all brood on the base of one cohesive raft confers several benefits: it preserves colony integrity, takes advantage of brood buoyancy, and increases the proportion of workers that immediately recover after rafting. PMID:24586600

Ant Abundance along a Productivity Gradient: Addressing Two Conflicting Hypotheses

PubMed Central

Segev, Udi; Kigel, Jaime; Lubin, Yael; Tielbörger, Katja

2015-01-01

The number of individuals within a population or community and their body size can be associated with changes in resource supply. While these relationships may provide a key to better understand the role of abiotic vs. biotic constraints in animal communities, little is known about the way size and abundance of organisms change along resource gradients. Here, we studied this interplay in ants, addressing two hypotheses with opposite predictions regarding variation in population densities along resource gradients- the ‘productivity hypothesis’ and the ‘productivity-based thinning hypothesis’. The hypotheses were tested in two functional groups of ground-dwelling ants that are directly primary consumers feeding on seeds: specialized seed-eaters and generalist species. We examined variations in colony density and foraging activity (a size measurement of the forager caste) in six ant assemblages along a steep productivity gradient in a semi-arid region, where precipitation and plant biomass vary 6-fold over a distance of 250km. An increase in the density or foraging activity of ant colonies along productivity gradients is also likely to affect competitive interactions among colonies, and consequently clinal changes in competition intensity were also examined. Ant foraging activity increased with productivity for both functional groups. However, colony density revealed opposing patterns: it increased with productivity for the specialized seed-eaters, but decreased for the generalist species. Competition intensity, evaluated by spatial partitioning of species at food baits and distribution of colonies, was uncorrelated with productivity in the specialized seed-eaters, but decreased with increasing productivity in the generalists. Our results provide support for two contrasting hypotheses regarding the effect of resource availability on the abundance of colonial organisms- the ‘productivity hypothesis’ for specialized seed-eaters and the ‘productivity-based thinning hypothesis’ for generalist species. These results also stress the importance of considering the role of functional groups in studies of community structure. PMID:26176853

Chaos-order transition in foraging behavior of ants.

PubMed

Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian; Schellnhuber, Hans Joachim

2014-06-10

The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. Biologists have discovered that single ants exhibit low-dimensional deterministic-chaotic activities. However, the influences of the nest, ants' physical abilities, and ants' knowledge (or experience) on foraging behavior have received relatively little attention in studies of the collective behavior of ants. This paper provides new insights into basic mechanisms of effective foraging for social insects or group animals that have a home. We propose that the whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. A mathematical model is developed to study this complex scheme. We show that the transition from chaotic to periodic regimes observed in our model results from an optimization scheme for group animals with a home. According to our investigation, the behavior of such insects is not represented by random but rather deterministic walks (as generated by deterministic dynamical systems, e.g., by maps) in a random environment: the animals use their intelligence and experience to guide them. The more knowledge an ant has, the higher its foraging efficiency is. When young insects join the collective to forage with old and middle-aged ants, it benefits the whole colony in the long run. The resulting strategy can even be optimal.

Ant groups optimally amplify the effect of transiently informed individuals

NASA Astrophysics Data System (ADS)

Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer

2015-07-01

To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis.

PubMed

Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

2013-06-21

A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well.

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

NASA Astrophysics Data System (ADS)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Chaos–order transition in foraging behavior of ants

PubMed Central

Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian; Schellnhuber, Hans Joachim

2014-01-01

The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. Biologists have discovered that single ants exhibit low-dimensional deterministic-chaotic activities. However, the influences of the nest, ants’ physical abilities, and ants’ knowledge (or experience) on foraging behavior have received relatively little attention in studies of the collective behavior of ants. This paper provides new insights into basic mechanisms of effective foraging for social insects or group animals that have a home. We propose that the whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. A mathematical model is developed to study this complex scheme. We show that the transition from chaotic to periodic regimes observed in our model results from an optimization scheme for group animals with a home. According to our investigation, the behavior of such insects is not represented by random but rather deterministic walks (as generated by deterministic dynamical systems, e.g., by maps) in a random environment: the animals use their intelligence and experience to guide them. The more knowledge an ant has, the higher its foraging efficiency is. When young insects join the collective to forage with old and middle-aged ants, it benefits the whole colony in the long run. The resulting strategy can even be optimal. PMID:24912159

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

NASA Astrophysics Data System (ADS)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

Sequential Fuzzy Diagnosis Method for Motor Roller Bearing in Variable Operating Conditions Based on Vibration Analysis

PubMed Central

Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

2013-01-01

A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well. PMID:23793021

An ant colony based algorithm for overlapping community detection in complex networks

NASA Astrophysics Data System (ADS)

Zhou, Xu; Liu, Yanheng; Zhang, Jindong; Liu, Tuming; Zhang, Di

2015-06-01

Community detection is of great importance to understand the structures and functions of networks. Overlap is a significant feature of networks and overlapping community detection has attracted an increasing attention. Many algorithms have been presented to detect overlapping communities. In this paper, we present an ant colony based overlapping community detection algorithm which mainly includes ants' location initialization, ants' movement and post processing phases. An ants' location initialization strategy is designed to identify initial location of ants and initialize label list stored in each node. During the ants' movement phase, the entire ants move according to the transition probability matrix, and a new heuristic information computation approach is redefined to measure similarity between two nodes. Every node keeps a label list through the cooperation made by ants until a termination criterion is reached. A post processing phase is executed on the label list to get final overlapping community structure naturally. We illustrate the capability of our algorithm by making experiments on both synthetic networks and real world networks. The results demonstrate that our algorithm will have better performance in finding overlapping communities and overlapping nodes in synthetic datasets and real world datasets comparing with state-of-the-art algorithms.

The Dynamics of Plant Cell-Wall Polysaccharide Decomposition in Leaf-Cutting Ant Fungus Gardens

PubMed Central

Harholt, Jesper; Willats, William G. T.; Boomsma, Jacobus J.

2011-01-01

The degradation of live plant biomass in fungus gardens of leaf-cutting ants is poorly characterised but fundamental for understanding the mutual advantages and efficiency of this obligate nutritional symbiosis. Controversies about the extent to which the garden-symbiont Leucocoprinus gongylophorus degrades cellulose have hampered our understanding of the selection forces that induced large scale herbivory and of the ensuing ecological footprint of these ants. Here we use a recently established technique, based on polysaccharide microarrays probed with antibodies and carbohydrate binding modules, to map the occurrence of cell wall polymers in consecutive sections of the fungus garden of the leaf-cutting ant Acromyrmex echinatior. We show that pectin, xyloglucan and some xylan epitopes are degraded, whereas more highly substituted xylan and cellulose epitopes remain as residuals in the waste material that the ants remove from their fungus garden. These results demonstrate that biomass entering leaf-cutting ant fungus gardens is only partially utilized and explain why disproportionally large amounts of plant material are needed to sustain colony growth. They also explain why substantial communities of microbial and invertebrate symbionts have evolved associations with the dump material from leaf-cutting ant nests, to exploit decomposition niches that the ant garden-fungus does not utilize. Our approach thus provides detailed insight into the nutritional benefits and shortcomings associated with fungus-farming in ants. PMID:21423735

Selection for protection in an ant-plant mutualism: host sanctions, host modularity, and the principal-agent game.

PubMed

Edwards, David P; Hassall, Mark; Sutherland, William J; Yu, Douglas W

2006-03-07

Retaliation against cheaters can prevent the breakdown of cooperation. Here we ask whether the ant-plant Cordia nodosa is able to apply retaliatory sanctions against its ant symbiont Allomerus octoarticulatus, which patrols new shoots to prevent herbivory. We test the hypothesis that the modular design of C. nodosa physiologically ties the growth of housing (stem swellings known as domatia) to the successful development of the attached leaves. We experimentally simulated herbivory by cutting leaves from patrolled shoots and found that the domatia on such 'cheated' shoots suffered higher mortality and lower growth than did controls, evidence for a host sanction. On the other hand, patrolling is costly to the ant, and experiment shows that non-patrollers run a low risk of being sanctioned because most leaves (and the attached domatia) escape heavy herbivory even when patrollers are absent. This suggests that cheaters might enjoy a higher fitness than do mutualists, despite sanctions, but we find that patrolling provides a net fecundity benefit when the colony and plant exceed a minimum size, which requires sustained ant investment in patrolling. These results map directly onto the principal-agent (P-A) game from economics, which we suggest can be used as a framework for studying stability in mutualisms, where high sampling costs and cheating do not allow market effects to select for mutual benefits.

Improving Societal Resilience Through Enhanced Reconnection Speed of Damaged Networks

NASA Astrophysics Data System (ADS)

Vodák, Rostislav; Bíl, Michal

2017-04-01

Road networks rank among the foundations of civilization. They enable people, services and goods to be transported to arbitrary places at any time. Its functioning can be impacted by various events, not only by natural hazards and their combinations. This can lead to the concurrent interruption of a number of roads and even cut-off parts of the network from vital services. The impact of these events can be reduced by various measures, but cannot be fully eliminated. We are aware of the fact that extreme events which result in road network break up will occur regardless of the ongoing process of hazard reduction using, for example, the improvement of the structural robustness of roads. The next problem is that many of the events are unpredictable and thus the needed costs of the improvement can easily spiral out of control. We therefore focus on the speed of the recovery process which can be optimized. This means that the time during which the damaged network is reconnected again will be as short as possible. The result of the optimization procedure is a sequence of road links which represent the routes of the repair units. The optimization process is, however, highly nontrivial because of the large number of possible routes for repair units. This prevents anyone from finding an optimal solution. We consequently introduce an approach based on the Ant Colony Optimization algorithm which is able to suggest an almost optimal solution under various constraints which can be established by the administrator of the network. We will also demonstrate its results and variability with several case examples.

Recourse-based facility-location problems in hybrid uncertain environment.

PubMed

Wang, Shuming; Watada, Junzo; Pedrycz, Witold

2010-08-01

The objective of this paper is to study facility-location problems in the presence of a hybrid uncertain environment involving both randomness and fuzziness. A two-stage fuzzy-random facility-location model with recourse (FR-FLMR) is developed in which both the demands and costs are assumed to be fuzzy-random variables. The bounds of the optimal objective value of the two-stage FR-FLMR are derived. As, in general, the fuzzy-random parameters of the FR-FLMR can be regarded as continuous fuzzy-random variables with an infinite number of realizations, the computation of the recourse requires solving infinite second-stage programming problems. Owing to this requirement, the recourse function cannot be determined analytically, and, hence, the model cannot benefit from the use of techniques of classical mathematical programming. In order to solve the location problems of this nature, we first develop a technique of fuzzy-random simulation to compute the recourse function. The convergence of such simulation scenarios is discussed. In the sequel, we propose a hybrid mutation-based binary ant-colony optimization (MBACO) approach to the two-stage FR-FLMR, which comprises the fuzzy-random simulation and the simplex algorithm. A numerical experiment illustrates the application of the hybrid MBACO algorithm. The comparison shows that the hybrid MBACO finds better solutions than the one using other discrete metaheuristic algorithms, such as binary particle-swarm optimization, genetic algorithm, and tabu search.

Workers' Extra-Nest Behavioral Changes During Colony Fission in Dinoponera quadriceps (Santschi).

PubMed

Medeiros, J; Araújo, A

2014-04-01

Ant colonies can reproduce by two strategies: independent foundation, wherein the queen starts a new colony alone, and dependent foundation, in which workers assist the queen. In the queenless species Dinoponera quadriceps (Santschi), the colony reproduces obligatorily by fission, a type of dependent foundation, but this process is not well understood. This study describes a colony fission event of D. quadriceps in the field and analyzes the influence of the fission process on workers' extra-nest behavior. Based on observations of workers outside the nest, five distinct stages were identified: monodomic stage, polydomic stage, split stage, conflict stage, and post-conflict stage. The colony was initially monodomic and then occupied a second nest before it split into two independent colonies, indicating a gradual and opportunistic dependent foundation. After the fission event, the daughter colony had aggressive conflicts with the parental colony, resulting in the latter's disappearance. Colony fission affected workers' extra-nest behavior by increasing the frequency of rubbing the gaster against the substrate (which probably has a chemical marking function) and by decreasing the frequency of foraging during the split stage. After the fission event, the number of foragers was halved and foragers remained nearer to the nest during extra-nest activity. The spatial closeness of the parental and daughter colonies led to competition that caused the extinction or migration of the parental colony. Intraspecific competition was indicated by foraging directionality at the colony level, whereby areas of neighbor colonies were avoided; this directionality was stronger while both colonies coexisted.

Sex ratio and Wolbachia infection in the ant Formica exsecta.

PubMed

Keller, L; Liautard, C; Reuter, M; Brown, W D; Sundström, L; Chapuisat, M

2001-08-01

Sex allocation data in social Hymenoptera provide some of the best tests of kin selection, parent-offspring conflict and sex ratio theories. However, these studies critically depend on controlling for confounding ecological factors and on identifying all parties that potentially manipulate colony sex ratio. It has been suggested that maternally inherited parasites may influence sex allocation in social Hymenoptera. If the parasites can influence sex allocation, infected colonies are predicted to invest more resources in females than non-infected colonies, because the parasites are transmitted through females but not males. Prime candidates for such sex ratio manipulation are Wolbachia, because these cytoplasmically transmitted bacteria have been shown to affect the sex ratio of host arthropods by cytoplasmic incompatibility, parthenogenesis, male-killing and feminization. In this study, we tested whether Wolbachia infection is associated with colony sex ratio in two populations of the ant Formica exsecta that have been the subject of extensive sex ratio studies. In these populations colonies specialize in the production of one sex or the other. We found that almost all F. exsecta colonies in both populations are infected with Wolbachia. However, in neither population did we find a significant association in the predicted direction between the prevalence of Wolbachia and colony sex ratio. In particular, colonies with a higher proportion of infected workers did not produce more females. Hence, we conclude that Wolbachia does not seem to alter the sex ratio of its hosts as a means to increase transmission rate in these two populations of ants.

Comparison of Decisions Quality of Heuristic Methods with Limited Depth-First Search Techniques in the Graph Shortest Path Problem

NASA Astrophysics Data System (ADS)

Vatutin, Eduard

2017-12-01

The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

Ant groups optimally amplify the effect of transiently informed individuals

PubMed Central

Gelblum, Aviram; Pinkoviezky, Itai; Fonio, Ehud; Ghosh, Abhijit; Gov, Nir; Feinerman, Ofer

2015-01-01

To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge. PMID:26218613

Characterization of actinobacteria associated with three ant-plant mutualisms.

PubMed

Hanshew, Alissa S; McDonald, Bradon R; Díaz Díaz, Carol; Djiéto-Lordon, Champlain; Blatrix, Rumsaïs; Currie, Cameron R

2015-01-01

Ant-plant mutualisms are conspicuous and ecologically important components of tropical ecosystems that remain largely unexplored in terms of insect-associated microbial communities. Recent work has revealed that ants in some ant-plant systems cultivate fungi (Chaetothyriales) within their domatia, which are fed to larvae. Using Pseudomyrmex penetrator/Tachigali sp. from French Guiana and Petalomyrmex phylax/Leonardoxa africana and Crematogaster margaritae/Keetia hispida, both from Cameroon, as models, we tested the hypothesis that ant-plant-fungus mutualisms co-occur with culturable Actinobacteria. Using selective media, we isolated 861 putative Actinobacteria from the three systems. All C. margaritae/K. hispida samples had culturable Actinobacteria with a mean of 10.0 colony forming units (CFUs) per sample, while 26 % of P. penetrator/Tachigali samples (mean CFUs 1.3) and 67 % of P. phylax/L. africana samples (mean CFUs 3.6) yielded Actinobacteria. The largest number of CFUs was obtained from P. penetrator workers, P. phylax alates, and C. margaritae pupae. 16S rRNA gene sequencing and phylogenetic analysis revealed the presence of four main clades of Streptomyces and one clade of Nocardioides within these three ant-plant mutualisms. Streptomyces with antifungal properties were isolated from all three systems, suggesting that they could serve as protective symbionts, as found in other insects. In addition, a number of isolates from a clade of Streptomyces associated with P. phylax/L. africana and C. margaritae/K. hispida were capable of degrading cellulose, suggesting that Streptomyces in these systems may serve a nutritional role. Repeated isolation of particular clades of Actinobacteria from two geographically distant locations supports these isolates as residents in ant-plant-fungi niches.

Smaller Brains and Optic Lobes in Reproductive Workers of the Ant Harpegnathos

NASA Astrophysics Data System (ADS)

Gronenberg, Wulfila; Liebig, Jürgen

Most animals show long-term modifications of their behavior which often reflect an adaptation to seasonal variations (e.g., hibernation) or result from changes in the animal's internal state (e.g., estrous cycle or sexual maturity). Such modifications may substantially affect the nervous system [1, 2]. A particularly striking behavioral change can occur in workers of the ant Harpegnathos. A few young workers in the colony may become reproductives and are thus confined to their dark nest chambers, whereas most workers spend their lives as foragers, employing acute vision when hunting prey. This behavioral difference coincides with a marked decrease in brain volume and with an even stronger reduction in the large visual brain centers. Instead of maintaining superfluous brain functions, these ants reduce brain matter which is expensive to support.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

PubMed

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level. The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved. Copyright © 2014 Elsevier B.V. All rights reserved.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

NASA Astrophysics Data System (ADS)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems.

PubMed

Su, Weixing; Chen, Hanning; Liu, Fang; Lin, Na; Jing, Shikai; Liang, Xiaodan; Liu, Wei

2017-03-01

There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC) for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell's pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

Societies drifting apart? Behavioural, genetic and chemical differentiation between supercolonies in the yellow crazy ant Anoplolepis gracilipes.

PubMed

Drescher, Jochen; Blüthgen, Nico; Schmitt, Thomas; Bühler, Jana; Feldhaar, Heike

2010-10-22

In populations of most social insects, gene flow is maintained through mating between reproductive individuals from different colonies in periodic nuptial flights followed by dispersal of the fertilized foundresses. Some ant species, however, form large polygynous supercolonies, in which mating takes place within the maternal nest (intranidal mating) and fertilized queens disperse within or along the boundary of the supercolony, leading to supercolony growth (colony budding). As a consequence, gene flow is largely confined within supercolonies. Over time, such supercolonies may diverge genetically and, thus, also in recognition cues (cuticular hydrocarbons, CHC's) by a combination of genetic drift and accumulation of colony-specific, neutral mutations. We tested this hypothesis for six supercolonies of the invasive ant Anoplolepis gracilipes in north-east Borneo. Within supercolonies, workers from different nests tolerated each other, were closely related and showed highly similar CHC profiles. Between supercolonies, aggression ranged from tolerance to mortal encounters and was negatively correlated with relatedness and CHC profile similarity. Supercolonies were genetically and chemically distinct, with mutually aggressive supercolony pairs sharing only 33.1%±17.5% (mean ± SD) of their alleles across six microsatellite loci and 73.8%±11.6% of the compounds in their CHC profile. Moreover, the proportion of alleles that differed between supercolony pairs was positively correlated to the proportion of qualitatively different CHC compounds. These qualitatively differing CHC compounds were found across various substance classes including alkanes, alkenes and mono-, di- and trimethyl-branched alkanes. We conclude that positive feedback between genetic, chemical and behavioural traits may further enhance supercolony differentiation through genetic drift and neutral evolution, and may drive colonies towards different evolutionary pathways, possibly including speciation.

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction

PubMed Central

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John BO

2008-01-01

Background We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024–1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581–590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Results Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6°C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, ε of 0.21) and an RMSE of 45.1°C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3°C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5°C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. Conclusion With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors. PMID:18959785

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

Biased and greedy random walks on two-dimensional lattices with quenched randomness: The greedy ant within a disordered environment

NASA Astrophysics Data System (ADS)

Mitran, T. L.; Melchert, O.; Hartmann, A. K.

2013-12-01

The main characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here the disorder allows for negative edge weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter ρ that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. The random walks are “greedy” in the sense that the local optimal choice of the walker is to preferentially traverse edges with a negative weight (associated with a net gain of “energy” for the walker). Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of ρ for different bias strengths B is put under scrutiny. Upon tuning ρ, the probability to find such a feasible lattice walk increases from zero to 1. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point ρc, resulting from numerically exact and “static” simulations in terms of the NWP model, can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

A novel type of nutritional ant-plant interaction: ant partners of carnivorous pitcher plants prevent nutrient export by dipteran pitcher infauna.

PubMed

Scharmann, Mathias; Thornham, Daniel G; Grafe, T Ulmar; Federle, Walter

2013-01-01

Many plants combat herbivore and pathogen attack indirectly by attracting predators of their herbivores. Here we describe a novel type of insect-plant interaction where a carnivorous plant uses such an indirect defence to prevent nutrient loss to kleptoparasites. The ant Camponotus schmitzi is an obligate inhabitant of the carnivorous pitcher plant Nepenthes bicalcarata in Borneo. It has recently been suggested that this ant-plant interaction is a nutritional mutualism, but the detailed mechanisms and the origin of the ant-derived nutrient supply have remained unexplained. We confirm that N. bicalcarata host plant leaves naturally have an elevated (15)N/(14)N stable isotope abundance ratio (δ(15)N) when colonised by C. schmitzi. This indicates that a higher proportion of the plants' nitrogen is insect-derived when C. schmitzi ants are present (ca. 100%, vs. 77% in uncolonised plants) and that more nitrogen is available to them. We demonstrated direct flux of nutrients from the ants to the host plant in a (15)N pulse-chase experiment. As C. schmitzi ants only feed on nectar and pitcher contents of their host, the elevated foliar δ(15)N cannot be explained by classic ant-feeding (myrmecotrophy) but must originate from a higher efficiency of the pitcher traps. We discovered that C. schmitzi ants not only increase the pitchers' capture efficiency by keeping the pitchers' trapping surfaces clean, but they also reduce nutrient loss from the pitchers by predating dipteran pitcher inhabitants (infauna). Consequently, nutrients the pitchers would have otherwise lost via emerging flies become available as ant colony waste. The plants' prey is therefore conserved by the ants. The interaction between C. schmitzi, N. bicalcarata and dipteran pitcher infauna represents a new type of mutualism where animals mitigate the damage by nutrient thieves to a plant.

Rediscovery and reclassification of the dipteran taxon Nothomicrodon Wheeler, an exclusive endoparasitoid of gyne ant larvae

PubMed Central

Pérez-Lachaud, Gabriela; Jahyny, Benoit J. B.; Ståhls, Gunilla; Rotheray, Graham; Delabie, Jacques H. C.; Lachaud, Jean-Paul

2017-01-01

The myrmecophile larva of the dipteran taxon Nothomicrodon Wheeler is rediscovered, almost a century after its original description and unique report. The systematic position of this dipteran has remained enigmatic due to the absence of reared imagos to confirm indentity. We also failed to rear imagos, but we scrutinized entire nests of the Brazilian arboreal dolichoderine ant Azteca chartifex which, combined with morphological and molecular studies, enabled us to establish beyond doubt that Nothomicrodon belongs to the Phoridae (Insecta: Diptera), not the Syrphidae where it was first placed, and that the species we studied is an endoparasitoid of the larvae of A. chartifex, exclusively attacking sexual female (gyne) larvae. Northomicrodon parasitism can exert high fitness costs to a host colony. Our discovery adds one more case to the growing number of phorid taxa known to parasitize ant larvae and suggests that many others remain to be discovered. Our findings and literature review confirm that the Phoridae is the only taxon known that parasitizes both adults and the immature stages of different castes of ants, thus threatening ants on all fronts. PMID:28361946

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

PubMed

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John Bo

2008-10-29

We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors.

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood.

PubMed

Ferral, Nolan; Holloway, Kyara; Li, Mingzhong; Yin, Zhaozheng; Hou, Chen

2018-06-01

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. We further hypothesize that the energy use of ant worker groups that are allowed to move freely increases more slowly than the group size even if they are isolated from queen and brood. Previous studies only provided indirect evidence for these hypotheses due to technical difficulties. In this study, we applied the automated behavioral monitoring and respirometry simultaneously on isolated worker groups for long time periods, and analyzed the image with the state-of-the-art algorithms. Our results show that when activity was not confined, large groups had lower per capita energy use, a lower percentage of active members, and lower average walking speed than small groups; while locomotion was confined, however, the per capita energy use was a constant regardless of the group size. The quantitative analysis shows a direct link between variation in group energy use and the activity level of ant workers when isolated from queen and brood. © 2016 Institute of Zoology, Chinese Academy of Sciences.

A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

PubMed

Kentzoglanakis, Kyriakos; Poole, Matthew

2012-01-01

In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

An ACOR-Based Multi-Objective WSN Deployment Example for Lunar Surveying.

PubMed

López-Matencio, Pablo

2016-02-06

Wireless sensor networks (WSNs) can gather in situ real data measurements and work unattended for long periods, even in remote, rough places. A critical aspect of WSN design is node placement, as this determines sensing capacities, network connectivity, network lifetime and, in short, the whole operational capabilities of the WSN. This paper proposes and studies a new node placement algorithm that focus on these aspects. As a motivating example, we consider a network designed to describe the distribution of helium-3 (³He), a potential enabling element for fusion reactors, on the Moon. ³He is abundant on the Moon's surface, and knowledge of its distribution is essential for future harvesting purposes. Previous data are inconclusive, and there is general agreement that on-site measurements, obtained over a long time period, are necessary to better understand the mechanisms involved in the distribution of this element on the Moon. Although a mission of this type is extremely complex, it allows us to illustrate the main challenges involved in a multi-objective WSN placement problem, i.e., selection of optimal observation sites and maximization of the lifetime of the network. To tackle optimization, we use a recent adaptation of the ant colony optimization (ACOR) metaheuristic, extended to continuous domains. Solutions are provided in the form of a Pareto frontier that shows the optimal equilibria. Moreover, we compared our scheme with the four-directional placement (FDP) heuristic, which was outperformed in all cases.

Identification of an ant queen pheromone regulating worker sterility.

PubMed

Holman, Luke; Jørgensen, Charlotte G; Nielsen, John; d'Ettorre, Patrizia

2010-12-22

The selective forces that shape and maintain eusocial societies are an enduring puzzle in evolutionary biology. Ordinarily sterile workers can usually reproduce given the right conditions, so the factors regulating reproductive division of labour may provide insight into why eusociality has persisted over evolutionary time. Queen-produced pheromones that affect worker reproduction have been implicated in diverse taxa, including ants, termites, wasps and possibly mole rats, but to date have only been definitively identified in the honeybee. Using the black garden ant Lasius niger, we isolate the first sterility-regulating ant queen pheromone. The pheromone is a cuticular hydrocarbon that comprises the majority of the chemical profile of queens and their eggs, and also affects worker behaviour, by reducing aggression towards objects bearing the pheromone. We further show that the pheromone elicits a strong response in worker antennae and that its production by queens is selectively reduced following an immune challenge. These results suggest that the pheromone has a central role in colony organization and support the hypothesis that worker sterility represents altruistic self-restraint in response to an honest quality signal.

Rediscovery and reclassification of the dipteran taxon Nothomicrodon Wheeler, an exclusive endoparasitoid of gyne ant larvae.

PubMed

Pérez-Lachaud, Gabriela; Jahyny, Benoit J B; Ståhls, Gunilla; Rotheray, Graham; Delabie, Jacques H C; Lachaud, Jean-Paul

2017-03-31

The myrmecophile larva of the dipteran taxon Nothomicrodon Wheeler is rediscovered, almost a century after its original description and unique report. The systematic position of this dipteran has remained enigmatic due to the absence of reared imagos to confirm indentity. We also failed to rear imagos, but we scrutinized entire nests of the Brazilian arboreal dolichoderine ant Azteca chartifex which, combined with morphological and molecular studies, enabled us to establish beyond doubt that Nothomicrodon belongs to the Phoridae (Insecta: Diptera), not the Syrphidae where it was first placed, and that the species we studied is an endoparasitoid of the larvae of A. chartifex, exclusively attacking sexual female (gyne) larvae. Northomicrodon parasitism can exert high fitness costs to a host colony. Our discovery adds one more case to the growing number of phorid taxa known to parasitize ant larvae and suggests that many others remain to be discovered. Our findings and literature review confirm that the Phoridae is the only taxon known that parasitizes both adults and the immature stages of different castes of ants, thus threatening ants on all fronts.

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

NASA Astrophysics Data System (ADS)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this application of the proposed algorithm, TSEA, with several state-of-the-art multiobjective optimization algorithms reveals that TSEA outperforms these algorithms by providing retrofit solutions with greater reliability for the same costs (i.e., closer to the Pareto-optimal front) after the algorithms are executed for the same number of generations. This research also demonstrates that TSEA competes with and, in some situations, outperforms state-of-the-art multiobjective optimization algorithms such as NSGA II and SPEA 2 when applied to classic bicriteria test problems in the technical literature and other complex, sizable real-world applications. The successful implementation of TSEA contributes to the safety of aeronautical structures by providing a systematic way to guide aircraft structural retrofitting efforts, as well as a potentially useful algorithm for a wide range of multiobjective optimization problems in engineering and other fields.

Enhancing artificial bee colony algorithm with self-adaptive searching strategy and artificial immune network operators for global optimization.

PubMed

Chen, Tinggui; Xiao, Renbin

2014-01-01

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.

Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

PubMed Central

Chen, Tinggui; Xiao, Renbin

2014-01-01

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023

Pheromone communication and the mushroom body of the ant, Camponotus obscuripes (Hymenoptera: Formicidae)

NASA Astrophysics Data System (ADS)

Yamagata, Nobuhiro; Fujiwara-Tsujii, Nao; Yamaoka, Ryohei; Mizunami, Makoto

2005-11-01

Communication by means of pheromones plays predominant roles in colony integration by social insects. However, almost nothing is known about pheromone processing in the brains of social insects. In this study, we successfully applied intracellular recording and staining techniques to anatomically and physiologically characterize brain neurons of the ant Camponotus obscuripes. We identified 42 protocerebral neurons that responded to undecane and/or formic acid, components of alarm pheromones that evoke attraction or evasive behavior, respectively. Notably, 30 (71%) of these neurons were efferent (output) or feedback neurons of the mushroom body, and many of these exhibited different responses to formic acid and undecane. Eight of the remaining 12 neurons had arborizations in the lateral and/or medial protocerebrum, which receive terminations of efferent neurons of the mushroom body and from which premotor descending neurons originate. The remaining four neurons were bilateral neurons that connect lateral accessory lobes or dorsal protocerebrums of both hemispheres. We suggest that the mushroom body of the ant participates in the processing of alarm pheromones. Seventeen (40%) of 42 neurons exhibited responses to nonpheromonal odors, indicating that the pheromonal and nonpheromonal signals are not fully segregated when they are processed in the protocerebrum. This may be related to modulatory functions of alarm pheromones, i.e., they change alertness of the ant and change responses to a variety of sensory stimuli.

Using Smart Phone Sensors to Detect Transportation Modes

PubMed Central

Xia, Hao; Qiao, Yanyou; Jian, Jun; Chang, Yuanfei

2014-01-01

The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users. PMID:25375756

Using smart phone sensors to detect transportation modes.

PubMed

Xia, Hao; Qiao, Yanyou; Jian, Jun; Chang, Yuanfei

2014-11-04

The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users.

Research on schedulers for astronomical observatories

NASA Astrophysics Data System (ADS)

Colome, Josep; Colomer, Pau; Guàrdia, Josep; Ribas, Ignasi; Campreciós, Jordi; Coiffard, Thierry; Gesa, Lluis; Martínez, Francesc; Rodler, Florian

2012-09-01

The main task of a scheduler applied to astronomical observatories is the time optimization of the facility and the maximization of the scientific return. Scheduling of astronomical observations is an example of the classical task allocation problem known as the job-shop problem (JSP), where N ideal tasks are assigned to M identical resources, while minimizing the total execution time. A problem of higher complexity, called the Flexible-JSP (FJSP), arises when the tasks can be executed by different resources, i.e. by different telescopes, and it focuses on determining a routing policy (i.e., which machine to assign for each operation) other than the traditional scheduling decisions (i.e., to determine the starting time of each operation). In most cases there is no single best approach to solve the planning system and, therefore, various mathematical algorithms (Genetic Algorithms, Ant Colony Optimization algorithms, Multi-Objective Evolutionary algorithms, etc.) are usually considered to adapt the application to the system configuration and task execution constraints. The scheduling time-cycle is also an important ingredient to determine the best approach. A shortterm scheduler, for instance, has to find a good solution with the minimum computation time, providing the system with the capability to adapt the selected task to varying execution constraints (i.e., environment conditions). We present in this contribution an analysis of the task allocation problem and the solutions currently in use at different astronomical facilities. We also describe the schedulers for three different projects (CTA, CARMENES and TJO) where the conclusions of this analysis are applied to develop a suitable routine.

The Organization of Foraging in the Fire Ant, Solenopsis invicta

PubMed Central

Tschinkel, Walter R.

2011-01-01

Although natural selection in ants acts most strongly at the colony, or superorganismal level, foraging patterns have rarely been studied at that level, focusing instead on the behavior of individual foragers or groups of foragers. The experiments and observations in this paper reveal in broad strokes how colonies of the fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae), allocate their available labor to foraging, how they disperse that force within their territory, and how this force changes with colony size, season and worker age. Territory area is positively related to colony size and the number of foragers, more so during the spring than fall. Changes of colony size and territory area are driven by seasonal variation of sexual and worker production, which in turn drive seasonal variation of worker age-distribution. During spring sexual production, colonies shrink because worker production falls below replacement. This loss is proportional to colony size, causing forager density in the spring to be negatively related to colony and territory size. In the fall, colonies emphasize worker production, bringing colony size back up. However, because smaller colonies curtailed spring worker production less than larger ones, their fall forager populations are proportionally greater, causing them to gain territory at the expense of large colonies. Much variation of territory area remains unexplained and can probably be attributed to pressure from neighboring colonies. Boundaries between territories are characterized by “no ants' zones” mostly devoid of fire ants. The forager population can be divided into a younger group of recruitable workers that wait for scouts to activate them to help retrieve large food finds. About one-third of the recruits wait near openings in the foraging tunnels that underlie the entire territory, while two-thirds wait in the nest. Recruitment to food is initially very rapid and local from the foraging tunnels, while sustained recruitment gradually involves the recruits waiting in the nest. As recruits age, they become scouts searching for food on the surface, and die about two weeks later. Foraging tunnels decrease in cross-sectional area with distance from the nest, in keeping with the gradual bleeding off of workers to the surface with distance. Foragers lack route-faithfulness, and having been marked and released at one point within the territory, they can be recaptured at any other point a day later. The size of the territory actually occupied may be limited during dry weather, resulting in very large no-ants' zones. PMID:21529150

An effective inversion algorithm for retrieving bimodal aerosol particle size distribution from spectral extinction data

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Yao, Yuchen; Ruan, Liming

2014-12-01

The Ant Colony Optimization algorithm based on the probability density function (PDF-ACO) is applied to estimate the bimodal aerosol particle size distribution (PSD). The direct problem is solved by the modified Anomalous Diffraction Approximation (ADA, as an approximation for optically large and soft spheres, i.e., χ⪢1 and |m-1|⪡1) and the Beer-Lambert law. First, a popular bimodal aerosol PSD and three other bimodal PSDs are retrieved in the dependent model by the multi-wavelength extinction technique. All the results reveal that the PDF-ACO algorithm can be used as an effective technique to investigate the bimodal PSD. Then, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution function to retrieve the bimodal PSDs under the independent model. Finally, the J-SB and M-β functions are applied to recover actual measurement aerosol PSDs over Beijing and Shanghai obtained from the aerosol robotic network (AERONET). The numerical simulation and experimental results demonstrate that these two general functions, especially the J-SB function, can be used as a versatile distribution function to retrieve the bimodal aerosol PSD when no priori information about the PSD is available.

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data.

PubMed

Zhang, Peng; Li, Houqiang; Wang, Honghui; Wong, Stephen T C; Zhou, Xiaobo

2011-01-01

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments.

PubMed

Lemos, Marcus Vinícius de S; Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L; de Carvalho, Carlos Giovanni N; Mendes, Douglas Lopes de S; Costa, Valney da Gama

2018-02-26

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user's queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user's queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios.

Trophallaxis-inspired model for distributed transport between randomly interacting agents.

PubMed

Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G; Katifori, Eleni

2017-08-01

Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

The Evolutionary Innovation of Nutritional Symbioses in Leaf-Cutter Ants

PubMed Central

Aylward, Frank O.; Currie, Cameron R.; Suen, Garret

2012-01-01

Fungus-growing ants gain access to nutrients stored in plant biomass through their association with a mutualistic fungus they grow for food. This 50 million-year-old obligate mutualism likely facilitated some of these species becoming dominant Neotropical herbivores that can achieve immense colony sizes. Recent culture-independent investigations have shed light on the conversion of plant biomass into nutrients within ant fungus gardens, revealing that this process involves both the fungal cultivar and a symbiotic community of bacteria including Enterobacter, Klebsiella, and Pantoea species. Moreover, the genome sequences of the leaf-cutter ants Atta cephalotes and Acromyrmex echinatior have provided key insights into how this symbiosis has shaped the evolution of these ants at a genetic level. Here we summarize the findings of recent research on the microbial community dynamics within fungus-growing ant fungus gardens and discuss their implications for this ancient symbiosis. PMID:26467948

Ant colony algorithm implementation in electron and photon Monte Carlo transport: application to the commissioning of radiosurgery photon beams.

PubMed

García-Pareja, S; Galán, P; Manzano, F; Brualla, L; Lallena, A M

2010-07-01

In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within approximately 3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

Modified artificial bee colony algorithm for reactive power optimization

NASA Astrophysics Data System (ADS)

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-05-01

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

PubMed

Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

2018-04-10

A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

The role of abiotic conditions in shaping the long-term patterns of a high-elevation Argentine ant invasion

USGS Publications Warehouse

Krushelnycky, P.D.; Joe, S.M.; Medeiros, A.C.; Daehler, C.C.; Loope, L.L.

2005-01-01

Analysis of long-term patterns of invasion can reveal the importance of abiotic factors in influencing invasion dynamics, and can help predict future patterns of spread. In the case of the invasive Argentine ant (Linepithema humile), most prior studies have investigated this species' limitations in hot and dry climates. However, spatial and temporal patterns of spread involving two ant populations over the course of 30 years at a high elevation site in Hawaii suggest that cold and wet conditions have influenced both the ant's distribution and its rate of invasion. In Haleakala National Park on Maui, we found that a population invading at lower elevation is limited by increasing rainfall and presumably by associated decreasing temperatures. A second, higher elevation population has spread outward in all directions, but rates of spread in different directions appear to have been strongly influenced by differences in elevation and temperature. Patterns of foraging activity were strongly tied to soil temperatures, supporting the hypothesis that variation in temperature can influence rates of spread. Based on past patterns of spread, we predicted a total potential range that covers nearly 50% of the park and 75% of the park's subalpine habitats. We compared this rough estimate with point predictions derived from a degree-day model for Argentine ant colony reproduction, and found that the two independent predictions match closely when soil temperatures are used in the model. The cold, wet conditions that have influenced Argentine ant invasion at this site are likely to be influential at other locations in this species' current and future worldwide distribution. ?? 2005 Blackwell Publishing Ltd.

Nonmathematical models for evolution of altruism, and for group selection (peck order-territoriality-ant colony-dual-determinant model-tri-determinant model).

PubMed

Darlington, P J

1972-02-01

Mathematical biologists have failed to produce a satisfactory general model for evolution of altruism, i.e., of behaviors by which "altruists" benefit other individuals but not themselves; kin selection does not seem to be a sufficient explanation of nonreciprocal altruism. Nonmathematical (but mathematically acceptable) models are now proposed for evolution of negative altruism in dual-determinant and of positive altruism in tri-determinant systems. Peck orders, territorial systems, and an ant society are analyzed as examples. In all models, evolution is primarily by individual selection, probably supplemented by group selection. Group selection is differential extinction of populations. It can act only on populations preformed by selection at the individual level, but can either cancel individual selective trends (effecting evolutionary homeostasis) or supplement them; its supplementary effect is probably increasingly important in the evolution of increasingly organized populations.

Trophallaxis-inspired model for distributed transport between randomly interacting agents

NASA Astrophysics Data System (ADS)

Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.; Katifori, Eleni

2017-08-01

Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Facilitating the 3D Indoor Search and Rescue Problem: An Overview of the Problem and an Ant Colony Solution Approach

NASA Astrophysics Data System (ADS)

Tashakkori, H.; Rajabifard, A.; Kalantari, M.

2016-10-01

Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.

Worker reproduction of the invasive yellow crazy ant Anoplolepis gracilipes.

PubMed

Lee, Ching-Chen; Nakao, Hirotaka; Tseng, Shu-Ping; Hsu, Hung-Wei; Lin, Gwo-Li; Tay, Jia-Wei; Billen, Johan; Ito, Fuminori; Lee, Chow-Yang; Lin, Chung-Chi; Yang, Chin-Cheng Scotty

2017-01-01

Reproductive division of labor is one of the key features of social insects. Queens are adapted for reproduction while workers are adapted for foraging and colony maintenance. In many species, however, workers retain functional ovaries and can lay unfertilized male eggs or trophic eggs. Here we report for the first time on the occurrence of physogastric workers and apparent worker reproduction in the invasive yellow crazy ant Anoplolepis gracilipes (Fr. Smith). We further examined the reproductive potential and nutritional role of physogastric workers through multidisciplinary approaches including morphological characterization, laboratory manipulation, genetic analysis and behavioral observation. Egg production with two types of eggs, namely reproductive and trophic eggs, by physogastric workers was found. The reproductive egg was confirmed to be haploid and male-destined, suggesting that the workers produced males via arrhenotokous parthenogenesis as no spermatheca was discovered. Detailed observations suggested that larvae were mainly fed with trophic eggs. Along with consumption of trophic eggs by queens and other castes as part of their diet, the vital role of physogastric workers as "trophic specialist" is confirmed. We propose that adaptive advantages derived from worker reproduction for A. gracilipes may include 1) trophic eggs provisioned by physogastric workers likely assist colonies of A. gracilipes in overcoming unfavorable conditions such as paucity of food during critical founding stage; 2) worker-produced males are fertile and thus might offer an inclusive fitness advantage for the doomed orphaned colony.

Ant trophallactic networks: simultaneous measurement of interaction patterns and food dissemination

NASA Astrophysics Data System (ADS)

Greenwald, Efrat; Segre, Enrico; Feinerman, Ofer

2015-07-01

Eusocial societies and ants, in particular, maintain tight nutritional regulation at both individual and collective levels. The mechanisms that underlie this control are far from trivial since, in these distributed systems, information about the global supply and demand is not available to any single individual. Here we present a novel technique for non-intervening frequent measurement of the food load of all individuals in an ant colony, including during trophallactic events in which food is transferred by mouth-to-mouth feeding. Ants are imaged using a dual camera setup that produces both barcode-based identification and fluorescence measurement of labeled food. This system provides detailed measurements that enable one to quantitatively study the adaptive food distribution network. To demonstrate the capabilities of our method, we present sample observations that were unattainable using previous techniques, and could provide insight into the mechanisms underlying food exchange.

Leucoagaricus gongylophorus Produces Diverse Enzymes for the Degradation of Recalcitrant Plant Polymers in Leaf-Cutter Ant Fungus Gardens

PubMed Central

Aylward, Frank O.; Burnum-Johnson, Kristin E.; Tringe, Susannah G.; Teiling, Clotilde; Tremmel, Daniel M.; Moeller, Joseph A.; Scott, Jarrod J.; Barry, Kerrie W.; Piehowski, Paul D.; Nicora, Carrie D.; Malfatti, Stephanie A.; Monroe, Matthew E.; Purvine, Samuel O.; Goodwin, Lynne A.; Smith, Richard D.; Weinstock, George M.; Gerardo, Nicole M.; Suen, Garret; Lipton, Mary S.

2013-01-01

Plants represent a large reservoir of organic carbon comprised primarily of recalcitrant polymers that most metazoans are unable to deconstruct. Many herbivores gain access to nutrients in this material indirectly by associating with microbial symbionts, and leaf-cutter ants are a paradigmatic example. These ants use fresh foliar biomass as manure to cultivate gardens composed primarily of Leucoagaricus gongylophorus, a basidiomycetous fungus that produces specialized hyphal swellings that serve as a food source for the host ant colony. Although leaf-cutter ants are conspicuous herbivores that contribute substantially to carbon turnover in Neotropical ecosystems, the process through which plant biomass is degraded in their fungus gardens is not well understood. Here we present the first draft genome of L. gongylophorus, and, using genomic and metaproteomic tools, we investigate its role in lignocellulose degradation in the gardens of both Atta cephalotes and Acromyrmex echinatior leaf-cutter ants. We show that L. gongylophorus produces a diversity of lignocellulases in ant gardens and is likely the primary driver of plant biomass degradation in these ecosystems. We also show that this fungus produces distinct sets of lignocellulases throughout the different stages of biomass degradation, including numerous cellulases and laccases that likely play an important role in lignocellulose degradation. Our study provides a detailed analysis of plant biomass degradation in leaf-cutter ant fungus gardens and insight into the enzymes underlying the symbiosis between these dominant herbivores and their obligate fungal cultivar. PMID:23584789

Chemical disguise as particular caste of host ants in the ant inquiline parasite Niphanda fusca (Lepidoptera: Lycaenidae)

PubMed Central

Hojo, Masaru K.; Wada-Katsumata, Ayako; Akino, Toshiharu; Yamaguchi, Susumu; Ozaki, Mamiko; Yamaoka, Ryohei

2008-01-01

The exploitation of parental care is common in avian and insect ‘cuckoos’ and these species engage in a coevolutionary arms race. Caterpillars of the lycaenid butterfly Niphanda fusca develop as parasites inside the nests of host ants (Camponotus japonicus) where they grow by feeding on the worker trophallaxis. We hypothesized that N. fusca caterpillars chemically mimic host larvae, or some particular castes of the host ant, so that the caterpillars are accepted and cared for by the host workers. Behaviourally, it was observed that the host workers enthusiastically tended glass dummies coated with the cuticular chemicals of larvae or males and those of N. fusca caterpillars living together. Cuticular chemical analyses revealed that N. fusca caterpillars grown in a host ant nest acquired a colony-specific blend of cuticular hydrocarbons (CHCs). Furthermore, the CHC profiles of the N. fusca caterpillars were particularly close to those of the males rather than those of the host larvae and the others. We suggest that N. fusca caterpillars exploit worker care by matching their cuticular profile to that of the host males, since the males are fed by trophallaxis with workers in their natal nests for approximately ten months. PMID:18842547

Non-native Ants Are Smaller than Related Native Ants.

PubMed

McGlynn, Terrence P

1999-12-01

I compare the sizes of non-native and native ants to evaluate how worker size may be related to the ability of a species to invade new habitats. I compare the size of 78 non-native ant species belonging to 26 genera with the size of native congeneric species; native ants are larger than non-native ants in 22 of 26 genera. Ants were sorted by genera into fighting and nonfighting groups, based on observations of interspecific interactions with other ant species. In all of the genera with monomorphic worker castes that fight during competition, the non-native species were smaller than the native species. The genera that engage in combat had a higher frequency of significantly smaller size in non-native ants. I selected Wasmannia auropunctata for further studies, to compare native and non-native populations. Specimens of W. auropunctata from non-native populations were smaller than conspecific counterparts from its native habitat. I consider hypotheses to explain why non-native ants are smaller in size than native ants, including the role of colony size in interspecific fights, changes in life history, the release from intraspecific fighting, and climate. The discovery that fighting non-natives are smaller than their closest native relatives may provide insight into the mechanisms for success of non-native species, as well as the role of worker size and colony size during interspecific competition.

Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, Hawaii

USGS Publications Warehouse

Hartley, Stephen; Krushelnycky, Paul D.; Lester, Philip J.

2010-01-01

Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species.

A Multiple Ant Colony Metahuristic for the Air Refueling Tanker Assignment Problem

DTIC Science & Technology

2002-03-01

Problem The tanker assignment problem can be modeled as a job shop scheduling problem ( JSSP ). The JSSP is made up of n jobs, composed of m ordered...points) to be processed on all the machines (tankers). The problem with using JSSP is that the tanker assignment problem has multiple objectives... JSSP will minimize the time it takes for all jobs, but this may take an inordinate number of tankers. Thus using JSSP alone is not necessarily a good

Current and potential ant impacts in the Pacific region

USGS Publications Warehouse

Loope, Lloyd L.; Krushelnycky, Paul D.

2007-01-01

Worldwide, ants are a powerful ecological force, and they appear to be dominant components of animal communities of many tropical and temperate ecosystems in terms of biomass and numbers of individuals (Bluthgen et al. 2000). For example, ants comprise up to 94% of arthropod individuals in fogging samples taken from diverse lowland tropical rainforest canopies, and 86% of the biomass (Davidson et al. 2003). The majority of these ant species and individuals obtain carbohydrates either from extrafloral nectaries or from sap-feeding Hemiptera that pass carbohydrate-rich “honeydew” to attending ants while concentrating nitrogen (N) from N-poor plant sap (Davidson et al. 2003). Honeydew and nectar represent key resources for arboreal ant species, although most ant species are at least partly carnivorous or scavengers (Bluthgen et al. 2004). In contrast to most of the terrestrial world, the biotas of many Pacific islands evolved without ants. Whereas endemic ant species are found in New Zealand (ca. 10 spp.), Tonga (ca. 10 spp.), and Samoa (ca. 12 spp.), other islands of Polynesia and parts of Micronesia likely lack native ants (Wilson and Taylor 1967, Wetterer 2002, Wetterer and Vargo 2003). About 20 Indo-Australian and western Pacific ant species range to the east and north of Samoa, but it is unclear how many of these were transported there by humans at some time (Wilson and Taylor 1967). Most of the remainder of the ant species currently found on Pacific islands are widespread species that fall in the category of “tramp species,” dispersed by recent human commerce and generally closely tied to human activity and urban areas (Wilson and Taylor 1967, McGlynn 1999). In Pacific island situations, some of these tramp ant species are able to thrive beyond areas of human activity. Relatively few ant species have been successful invaders of native communities on continents, and these include most of the species that pose the greatest problems for Pacific islands. They generally have multiple queens per colony, are unicolonial (lacking internest aggression), quickly recruit to food items, thrive in a variety of habitats including disturbed areas, and can be highly aggressive to other ant species (McGlynn 1999). Hawaii’s arthropod fauna evolved in the absence of ants and has been observed by many biologists to be highly vulnerable to displacement by non-native ants. Pacific island biotas have also very likely suffered greatly from displacement by ants. However, in contrast to Hawaii, virtually nothing has been published on effects of non-native ants on native arthropod fauna elsewhere on Pacific islands, with the exception of the Galapagos archipelago, which may have at least four species of endemic ants (Lubin 1984, Nishida and Evenhuis 2000) and New Caledonia (Jourdan et al. 2001, Le Breton et al. 2005). In addition, many ant species in the Pacific have long been a nuisance for humans, and significant agricultural impacts have occurred from ants tending hemipteran insects of crop plants.

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Enslaved ants: not as helpless as they were thought to be.

PubMed

Czechowski, W; Godzińska, E J

Slavery in ants involves robbing of brood of host ant species and rearing captured individuals in the enslaver's nest. Whereas slaves of facultative slave-makers increase the workforce of the colony, in obligate slave-makers presence of slaves is vital for colony survival. Until recently, it was generally believed that enslaved workers act solely for the benefit of their social parasite and are wholly lost for their own colony and population. However, evidence that slaves may act also in favour of their own maternal population by engaging in various forms of the so-called slave rebellions is already quite extensive and may be found in both old and recent myrmecological literature, although, unfortunately, these data are often neglected or overlooked. They may be classified into four categories: (1) acts of physical aggression directed by slaves to slave-makers, (2) attempts of slaves to reproduce within a slave-maker colony, (3) 'sabotage', i.e. activities of slaves leading to weakening of the slave-maker colony and population, and (4) slave emancipation, i.e. partial or complete self-liberation of slaves from slave-maker colonies. In this review, we present and discuss all these diverse (often interrelated) expressions of slave opposition to their enslavers, focussing our discussion on both proximate and evolutionary causation of the discussed phenomena. We also indicate some open questions which remain to be answered by future research.

Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

PubMed Central

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

PubMed

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

First evidence for slave rebellion: enslaved ant workers systematically kill the brood of their social parasite protomognathus americanus.

PubMed

Achenbach, Alexandra; Foitzik, Susanne

2009-04-01

During the process of coevolution, social parasites have evolved sophisticated strategies to exploit the brood care behavior of their social hosts. Slave-making ant queens invade host colonies and kill or eject all adult host ants. Host workers, which eclose from the remaining brood, are tricked into caring for the parasite brood. Due to their high prevalence and frequent raids, following which stolen host broods are similarly enslaved, slave-making ants exert substantial selection upon their hosts, leading to the evolution of antiparasite adaptations. However, all host defenses shown to date are active before host workers are parasitized, whereas selection was thought to be unable to act on traits of already enslaved hosts. Yet, here we demonstrate the rebellion of enslaved Temnothorax workers, which kill two-thirds of the female pupae of the slave-making ant Protomognathus americanus. Thereby, slaves decrease the long-term parasite impact on surrounding related host colonies. This novel antiparasite strategy of enslaved workers constitutes a new level in the coevolutionary battle after host colony defense has failed. Our discovery is analogous to recent findings in hosts of avian brood parasites where perfect mimicry of parasite eggs leads to the evolution of chick recognition as a second line of defense.

Which insect species numerically respond to allochthonous inputs?

NASA Astrophysics Data System (ADS)

Sugiura, Shinji; Ikeda, Hiroshi

2013-08-01

Herons (Ardeidae) frequently breed in inland forests and provide organic material in the form of carcasses of prey (that they drop) and chicks (that die) to the forest floor. Such allochthonous inputs of organic materials are known to increase arthropod populations in forests. However, the exact species that show numerical responses to allochthonous inputs in heron breeding colonies remains unclear. Very few studies have clarified which factors determine numerical responses in individual species. We used pitfall and baited traps to compare the densities of arthropods between forest patches in heron breeding colonies (five sites) and areas outside of colonies (five sites) in central Japan. The density of all arthropods was not significantly different between colonies and non-colony areas. However, significant differences between colonies and non-colony areas were found in four arthropod groups. Earwigs (Dermaptera: Anisolabididae), hister beetles (Coleoptera: Histeridae), and carrion beetles (Coleoptera: Silphidae) were more abundant in colonies, while ants (Hymenoptera: Formicidae) were less abundant in colonies. We detected numerical responses to heron breeding in two earwig, one histerid, five silphid, and one ant species. Chick and prey carcasses from herons may have directly led to increases in consumer populations such as earwigs, histerids, and silphids in colonies, while microenvironmental changes caused by heron breeding may have reduced ant abundance. In the Silphidae, five species showed numerical responses to allochthonous inputs, and the other two species did not. Numerical responses in individual species may have been determined by life history traits such as reproductive behaviour.

Escalated convergent artificial bee colony

NASA Astrophysics Data System (ADS)

Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

2016-03-01

Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

Acanthopria and Mimopriella parasitoid wasps (Diapriidae) attack Cyphomyrmex fungus-growing ants (Formicidae, Attini)

NASA Astrophysics Data System (ADS)

Fernández-Marín, Hermógenes; Zimmerman, Jess K.; Wcislo, William T.

2006-01-01

New World diapriine wasps are abundant and diverse, but the biology of most species is unknown. We provide the first description of the biology of diapriine wasps, Acanthopria spp. and Mimopriella sp., which attack the larvae of Cyphomyrmex fungus-growing ants. In Puerto Rico, the koinobiont parasitoids Acanthopria attack Cyphomyrmex minutus, while in Panama at least four morphospecies of Acanthopria and one of Mimopriella attack Cyphomyrmex rimosus. Of the total larvae per colony, 0 100% were parasitized, and 27 70% of the colonies per population were parasitized. Parasitism rate and colony size were negatively correlated for C. rimosus but not for C. minutus. Worker ants grasped at, bit, and in some cases, killed adult wasps that emerged in artificial nests or tried to enter natural nests. Parasitoid secondary sex ratios were female-biased for eclosing wasps, while field collections showed a male-biased sex ratio. Based on their abundance and success in attacking host ants, these minute wasps present excellent opportunities to explore how natural enemies impact ant colony demography and population biology.

Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms.

PubMed

Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza

2012-05-01

Effective abnormality detection and diagnosis in Magnetic Resonance Images (MRIs) requires a robust segmentation strategy. Since manual segmentation is a time-consuming task which engages valuable human resources, automatic MRI segmentations received an enormous amount of attention. For this goal, various techniques have been applied. However, Markov Random Field (MRF) based algorithms have produced reasonable results in noisy images compared to other methods. MRF seeks a label field which minimizes an energy function. The traditional minimization method, simulated annealing (SA), uses Monte Carlo simulation to access the minimum solution with heavy computation burden. For this reason, MRFs are rarely used in real time processing environments. This paper proposed a novel method based on MRF and a hybrid of social algorithms that contain an ant colony optimization (ACO) and a Gossiping algorithm which can be used for segmenting single and multispectral MRIs in real time environments. Combining ACO with the Gossiping algorithm helps find the better path using neighborhood information. Therefore, this interaction causes the algorithm to converge to an optimum solution faster. Several experiments on phantom and real images were performed. Results indicate that the proposed algorithm outperforms the traditional MRF and hybrid of MRF-ACO in speed and accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Designing Multi-target Compound Libraries with Gaussian Process Models.

PubMed

Bieler, Michael; Reutlinger, Michael; Rodrigues, Tiago; Schneider, Petra; Kriegl, Jan M; Schneider, Gisbert

2016-05-01

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

PubMed Central

Blonder, Benjamin; Dornhaus, Anna

2011-01-01

Background An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. Methodology/Findings Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. Conclusions/Significance Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales. PMID:21625450

MGA trajectory planning with an ACO-inspired algorithm

NASA Astrophysics Data System (ADS)

Ceriotti, Matteo; Vasile, Massimiliano

2010-11-01

Given a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.

Bus Stops Location and Bus Route Planning Using Mean Shift Clustering and Ant Colony in West Jakarta

NASA Astrophysics Data System (ADS)

Supangat, Kenny; Eko Soelistio, Yustinus

2017-03-01

Traffic Jam has been a daily problem for people in Jakarta which is one of the busiest city in Indonesia up until now. Even though the official government has tried to reduce the impact of traffic issues by developing a new public transportation which takes up a lot of resources and time, it failed to diminish the problem. The actual concern to this problem actually lies in how people move between places in Jakarta where they always using their own vehicle like cars, and motorcycles that fill most of the street in Jakarta. Among much other public transportations that roams the street of Jakarta, Buses is believed to be an efficient transportation that can move many people at once. However, the location of the bus stop is now have moved to the middle of the main road, and its too far for the nearby residence to access to it. This paper proposes an optimal location of optimal bus stops in West Jakarta that is experimentally proven to have a maximal distance of 350 m. The optimal location is estimated by means of mean shift clustering method while the optimal routes are calculated using Ant Colony algorithm. The bus stops locations rate of error is 0.07% with overall route area of 32 km. Based on our experiments, we believe our proposed bus stop plan can be an interesting alternative to reduce traffic congestion in West Jakarta.

Protein-ligand docking using fitness learning-based artificial bee colony with proximity stimuli.

PubMed

Uehara, Shota; Fujimoto, Kazuhiro J; Tanaka, Shigenori

2015-07-07

Protein-ligand docking is an optimization problem, which aims to identify the binding pose of a ligand with the lowest energy in the active site of a target protein. In this study, we employed a novel optimization algorithm called fitness learning-based artificial bee colony with proximity stimuli (FlABCps) for docking. Simulation results revealed that FlABCps improved the success rate of docking, compared to four state-of-the-art algorithms. The present results also showed superior docking performance of FlABCps, in particular for dealing with highly flexible ligands and proteins with a wide and shallow binding pocket.

Colony-Level Differences in the Scaling Rules Governing Wood Ant Compound Eye Structure.

PubMed

Perl, Craig D; Niven, Jeremy E

2016-04-12

Differential organ growth during development is essential for adults to maintain the correct proportions and achieve their characteristic shape. Organs scale with body size, a process known as allometry that has been studied extensively in a range of organisms. Such scaling rules, typically studied from a limited sample, are assumed to apply to all members of a population and/or species. Here we study scaling in the compound eyes of workers of the wood ant, Formica rufa, from different colonies within a single population. Workers' eye area increased with body size in all the colonies showing a negative allometry. However, both the slope and intercept of some allometric scaling relationships differed significantly among colonies. Moreover, though mean facet diameter and facet number increased with body size, some colonies primarily increased facet number whereas others increased facet diameter, showing that the cellular level processes underlying organ scaling differed among colonies. Thus, the rules that govern scaling at the organ and cellular levels can differ even within a single population.

Genetic evidence for intra- and interspecific slavery in honey ants (genus Myrmecocystus).

PubMed Central

Kronauer, D J C; Gadau, J; Hölldobler, B

2003-01-01

The New World honey ant species Myrmecocystus mimicus is well known for its highly stereotyped territorial tournaments, and for the raids on conspecific nests that can lead to intraspecific slavery. Our results from mitochondrial and nuclear markers show that the raided brood emerges in the raiding colony and is subsequently incorporated into the colony's worker force. We also found enslaved conspecifics in a second honey ant species, M. depilis, the sister taxon of M. mimicus, which occurs in sympatry with M. mimicus at the study site. Colonies of this species furthermore contained raided M. mimicus workers. Both species have an effective mating frequency that is not significantly different from 1. This study provides genetic evidence for facultative intra- and interspecific slavery in the genus Myrmecocystus. Slavery in ants has evolved repeatedly and supposedly by different means. We propose that, in honey ants, secondary contact between two closely related species that both exhibit intraspecific slavery gave rise to an early form of facultative interspecific slavery. PMID:12737658

Cheater genotypes in the parthenogenetic ant Pristomyrmex punctatus

PubMed Central

Dobata, Shigeto; Sasaki, Tomonori; Mori, Hideaki; Hasegawa, Eisuke; Shimada, Masakazu; Tsuji, Kazuki

2008-01-01

Cooperation is subject to cheating strategies that exploit the benefits of cooperation without paying the fair costs, and it has been a major goal of evolutionary biology to explain the origin and maintenance of cooperation against such cheaters. Here, we report that cheater genotypes indeed coexist in field colonies of a social insect, the parthenogenetic ant Pristomyrmex punctatus. The life history of this species is exceptional, in that there is no reproductive division of labour: all females fulfil both reproduction and cooperative tasks. Previous studies reported sporadic occurrence of larger individuals when compared with their nest-mates. These larger ants lay more eggs and hardly take part in cooperative tasks, resulting in lower fitness of the whole colony. Population genetic analysis showed that at least some of these large-bodied individuals form a genetically distinct lineage, isolated from cooperators by parthenogenesis. A phylogenetic study confirmed that this cheater lineage originated intraspecifically. Coexistence of cheaters and cooperators in this species provides a good model system to investigate the evolution of cooperation in nature. PMID:18854297

Cuticular hydrocarbons correlate with queen reproductive status in native and invasive Argentine ants (Linepithema humile, Mayr)

PubMed Central

Diaz, Mireia; Lenoir, Alain; Ivon Paris, Carolina; Boulay, Raphaël; Gómez, Crisanto

2018-01-01

In insect societies, chemical communication plays an important role in colony reproduction and individual social status. Many studies have indicated that cuticular hydrocarbons (CHCs) are the main chemical compounds encoding reproductive status. However, these studies have largely focused on queenless or monogynous species whose workers are capable of egg laying and have mainly explored the mechanisms underlying queen-worker or worker-worker reproductive conflicts. Less is known about what occurs in highly polygynous ant species with permanently sterile workers. Here, we used the Argentine ant as a model to examine the role of CHCs in communicating reproductive information in such insect societies. The Argentine ant is unicolonial, highly polygynous, and polydomous. We identified several CHCs whose presence and levels were correlated with queen age, reproductive status, and fertility. Our results also provide new insights into queen executions in the Argentine ant, a distinctive feature displayed by this species in its introduced range. Each spring, just before new sexuals appear, workers eliminate up to 90% of the mated queens in their colonies. We discovered that queens that survived execution had different CHC profiles from queens present before and during execution. More specifically, levels of some CHCs were higher in the survivors, suggesting that workers could eliminate queens based on their chemical profiles. In addition, queen CHC profiles differed based on season and species range (native vs. introduced). Overall, the results of this study provide new evidence that CHCs serve as queen signals and do more than just regulate worker reproduction. PMID:29470506

Highway concrete pavement technology development and testing. Volume 5, Field evaluation of Strategic Highway Research Program (SHRP) C-206 test sites (bridge deck overlays)

DOT National Transportation Integrated Search

2006-08-01

Two types of concrete overlays silica fume concrete (SFC) and latex-modified Type III portland cement concrete (LMC-III) were installed ant tested as part of the Strategic Highway Research Program (SHRP) Project C-206: Optimization of Highway Concret...

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments

PubMed Central

Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L.; de Carvalho, Carlos Giovanni N.; Mendes, Douglas Lopes de S.; Costa, Valney da Gama

2018-01-01

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios. PMID:29495406

Sting, Carry and Stock: How Corpse Availability Can Regulate De-Centralized Task Allocation in a Ponerine Ant Colony

PubMed Central

Schmickl, Thomas; Karsai, Istvan

2014-01-01

We develop a model to produce plausible patterns of task partitioning in the ponerine ant Ectatomma ruidum based on the availability of living prey and prey corpses. The model is based on the organizational capabilities of a “common stomach” through which the colony utilizes the availability of a natural (food) substance as a major communication channel to regulate the income and expenditure of the very same substance. This communication channel has also a central role in regulating task partitioning of collective hunting behavior in a supply&demand-driven manner. Our model shows that task partitioning of the collective hunting behavior in E. ruidum can be explained by regulation due to a common stomach system. The saturation of the common stomach provides accessible information to individual ants so that they can adjust their hunting behavior accordingly by engaging in or by abandoning from stinging or transporting tasks. The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest. This system is also able to react to external perturbations in a de-centralized homeostatic way, such as to changes in the prey density or to accumulation of food in the nest. In case of stable conditions the system develops towards an equilibrium concerning colony size and prey density. Our model shows that organization of work through a common stomach system can allow Ectatomma ruidum to collectively forage for food in a robust, reactive and reliable way. The model is compared to previously published models that followed a different modeling approach. Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions. These predictions are used to formulate a set of testable hypotheses that should be investigated empirically in future experimentation. PMID:25493558

Effect of Carbohydrate Supplementation on Investment into Offspring Number, Size, and Condition in a Social Insect

PubMed Central

Wills, Bill D.; Chong, Cody D.; Wilder, Shawn M.; Eubanks, Micky D.; Holway, David A.; Suarez, Andrew V.

2015-01-01

Resource availability can determine an organism’s investment strategies for growth and reproduction. When nutrients are limited, there are potential tradeoffs between investing into offspring number versus individual offspring size. In social insects, colony investment in offspring size and number may shift in response to colony needs and the availability of food resources. We experimentally manipulated the diet of a polymorphic ant species (Solenopsis invicta) to test how access to the carbohydrate and amino acid components of nectar resources affect colony investment in worker number, body size, size distributions, and individual percent fat mass. We reared field-collected colonies on one of four macronutrient treatment supplements: water, amino acids, carbohydrates, and amino acid and carbohydrates. Having access to carbohydrates nearly doubled colony biomass after 60 days. This increase in biomass resulted from an increase in worker number and mean worker size. Access to carbohydrates also altered worker body size distributions. Finally, we found a negative relationship between worker number and size, suggesting a tradeoff in colony investment strategies. This tradeoff was more pronounced for colonies without access to carbohydrate resources. The monopolization of plant-based resources has been implicated in the ecological success of ants. Our results shed light on a possible mechanism for this success, and also have implications for the success of introduced species. In addition to increases in colony size, our results suggest that having access to plant-based carbohydrates can also result in larger workers that may have better individual fighting ability, and that can withstand greater temperature fluctuations and periods of food deprivation. PMID:26196147

Interaction specificity between leaf-cutting ants and vertically transmitted Pseudonocardia bacteria.

PubMed

Andersen, Sandra B; Yek, Sze Huei; Nash, David R; Boomsma, Jacobus J

2015-02-25

The obligate mutualism between fungus-growing ants and microbial symbionts offers excellent opportunities to study the specificity and stability of multi-species interactions. In addition to cultivating fungus gardens, these ants have domesticated actinomycete bacteria to defend gardens against the fungal parasite Escovopsis and possibly other pathogens. Panamanian Acromyrmex echinatior leaf-cutting ants primarily associate with actinomycetes of the genus Pseudonocardia. Colonies are inoculated with one of two vertically transmitted phylotypes (Ps1 or Ps2), and maintain the same phylotype over their lifetime. We performed a cross-fostering experiment to test whether co-adaptations between ants and bacterial phylotypes have evolved, and how this affects bacterial growth and ant prophylactic behavior after infection with Escovopsis. We show that Pseudonocardia readily colonized ants irrespective of their colony of origin, but that the Ps2 phylotype, which was previously shown to be better able to maintain its monocultural integrity after workers became foragers than Ps1, reached a higher final cover when grown on its native host than on alternative hosts. The frequencies of major grooming and weeding behaviors co-varied with symbiont/host combinations, showing that ant behavior also was affected when cuticular actinomycete phylotypes were swapped. These results show that the interactions between leaf-cutting ants and Pseudonocardia bear signatures of mutual co-adaptation within a single ant population.

The effect of individual variation on the structure and function of interaction networks in harvester ants

PubMed Central

Pinter-Wollman, Noa; Wollman, Roy; Guetz, Adam; Holmes, Susan; Gordon, Deborah M.

2011-01-01

Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant's interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow. PMID:21490001

Colony image acquisition and genetic segmentation algorithm and colony analyses

NASA Astrophysics Data System (ADS)

Wang, W. X.

2012-01-01

Colony anaysis is used in a large number of engineerings such as food, dairy, beverages, hygiene, environmental monitoring, water, toxicology, sterility testing. In order to reduce laboring and increase analysis acuracy, many researchers and developers have made efforts for image analysis systems. The main problems in the systems are image acquisition, image segmentation and image analysis. In this paper, to acquire colony images with good quality, an illumination box was constructed. In the box, the distances between lights and dishe, camra lens and lights, and camera lens and dishe are adjusted optimally. In image segmentation, It is based on a genetic approach that allow one to consider the segmentation problem as a global optimization,. After image pre-processing and image segmentation, the colony analyses are perfomed. The colony image analysis consists of (1) basic colony parameter measurements; (2) colony size analysis; (3) colony shape analysis; and (4) colony surface measurements. All the above visual colony parameters can be selected and combined together, used to make a new engineeing parameters. The colony analysis can be applied into different applications.

Temporal polyethism, life expectancy, and entropy of workers of the ant Ectatomma vizottoi Almeida, 1987 (Formicidae: Ectatomminae).

PubMed

Santana Vieira, Alexsandro; Desidério Fernandes, Wedson; Fernando Antonialli-Junior, William

2010-05-01

We investigated the changes in the behavioral repertoire over the course of life and determined the life expectancy and entropy of workers of the ant Ectatomma vizottoi. Newly emerged ants were individually marked with model airplane paint for observation of behaviors and determination of the age and life expectancy. Ants were divided into two groups: young and old workers. The 36 behaviors observed were divided into eight categories. Workers exhibit a clear division of tasks throughout their lives, with young workers performing more tasks inside the colony and old workers, outside, unlike species that have small colonies. This species also exhibits an intermediate life expectancy compared to workers of other species that are also intermediary in size. This supports the hypothesis of a relationship between size and maximum life expectancy, but it also suggests that other factors may also be acting in concert. Entropy value shows a high mortality rate during the first life intervals.

Artificial Bee Colony Optimization of Capping Potentials for Hybrid Quantum Mechanical/Molecular Mechanical Calculations.

PubMed

Schiffmann, Christoph; Sebastiani, Daniel

2011-05-10

We present an algorithmic extension of a numerical optimization scheme for analytic capping potentials for use in mixed quantum-classical (quantum mechanical/molecular mechanical, QM/MM) ab initio calculations. Our goal is to minimize bond-cleavage-induced perturbations in the electronic structure, measured by means of a suitable penalty functional. The optimization algorithm-a variant of the artificial bee colony (ABC) algorithm, which relies on swarm intelligence-couples deterministic (downhill gradient) and stochastic elements to avoid local minimum trapping. The ABC algorithm outperforms the conventional downhill gradient approach, if the penalty hypersurface exhibits wiggles that prevent a straight minimization pathway. We characterize the optimized capping potentials by computing NMR chemical shifts. This approach will increase the accuracy of QM/MM calculations of complex biomolecules.

Genetic evidence for intra- and interspecific slavery in honey ants (genus Myrmecocystus).

PubMed

Kronauer, D J C; Gadau, J; Hölldobler, B

2003-04-22

The New World honey ant species Myrmecocystus mimicus is well known for its highly stereotyped territorial tournaments, and for the raids on conspecific nests that can lead to intraspecific slavery. Our results from mitochondrial and nuclear markers show that the raided brood emerges in the raiding colony and is subsequently incorporated into the colony's worker force. We also found enslaved conspecifics in a second honey ant species, M. depilis, the sister taxon of M. mimicus, which occurs in sympatry with M. mimicus at the study site. Colonies of this species furthermore contained raided M. mimicus workers. Both species have an effective mating frequency that is not significantly different from 1. This study provides genetic evidence for facultative intra- and interspecific slavery in the genus Myrmecocystus. Slavery in ants has evolved repeatedly and supposedly by different means. We propose that, in honey ants, secondary contact between two closely related species that both exhibit intraspecific slavery gave rise to an early form of facultative interspecific slavery.

The Red Imported Fire Ant (Solenopsis invicta Buren) Kept Y not F: Predicted sNPY Endogenous Ligands Deorphanize the Short NPF (sNPF) Receptor

PubMed Central

Bajracharya, Prati; Lu, Hsiao-Ling; Pietrantonio, Patricia V.

2014-01-01

Neuropeptides and their receptors play vital roles in controlling the physiology and behavior of animals. Short neuropeptide F (sNPF) signaling regulates several physiological processes in insects such as feeding, locomotion, circadian rhythm and reproduction, among others. Previously, the red imported fire ant (Solenopsis invicta) sNPF receptor (S. invicta sNPFR), a G protein-coupled receptor, was immunolocalized in queen and worker brain and queen ovaries. Differential distribution patterns of S. invicta sNPFR protein in fire ant worker brain were associated both with worker subcastes and with presence or absence of brood in the colony. However, the cognate ligand for this sNPFR has not been characterized and attempts to deorphanize the receptor with sNPF peptides from other insect species which ended in the canonical sequence LRLRFamide, failed. Receptor deorphanization is an important step to understand the neuropeptide receptor downstream signaling cascade. We cloned the full length cDNA of the putative S. invicta sNPF prepropeptide and identified the putative “sNPF” ligand within its sequence. The peptide ends with an amidated Tyr residue whereas in other insect species sNPFs have an amidated Phe or Trp residue at the C-terminus. We stably expressed the HA-tagged S. invicta sNPFR in CHO-K1 cells. Two S. invicta sNPFs differing at their N-terminus were synthesized that equally activated the sNPFR, SLRSALAAGHLRYa (EC50 = 3.2 nM) and SALAAGHLRYa (EC50 = 8.6 nM). Both peptides decreased the intracellular cAMP concentration, indicating signaling through the Gαi-subunit. The receptor was not activated by sNPF peptides from other insect species, honey bee long NPF (NPY) or mammalian PYY. Further, a synthesized peptide otherwise identical to the fire ant sequence but in which the C-terminal amidated amino acid residue ‘Y’ was switched to ‘F’, failed to activate the sNPFR. This discovery will now allow us to investigate the function of sNPY and its cognate receptor in fire ant biology. PMID:25310341

A Novel Type of Nutritional Ant–Plant Interaction: Ant Partners of Carnivorous Pitcher Plants Prevent Nutrient Export by Dipteran Pitcher Infauna

PubMed Central

Scharmann, Mathias; Thornham, Daniel G.; Grafe, T. Ulmar; Federle, Walter

2013-01-01

Many plants combat herbivore and pathogen attack indirectly by attracting predators of their herbivores. Here we describe a novel type of insect–plant interaction where a carnivorous plant uses such an indirect defence to prevent nutrient loss to kleptoparasites. The ant Camponotus schmitzi is an obligate inhabitant of the carnivorous pitcher plant Nepenthes bicalcarata in Borneo. It has recently been suggested that this ant–plant interaction is a nutritional mutualism, but the detailed mechanisms and the origin of the ant-derived nutrient supply have remained unexplained. We confirm that N. bicalcarata host plant leaves naturally have an elevated 15N/14N stable isotope abundance ratio (δ15N) when colonised by C. schmitzi. This indicates that a higher proportion of the plants’ nitrogen is insect-derived when C. schmitzi ants are present (ca. 100%, vs. 77% in uncolonised plants) and that more nitrogen is available to them. We demonstrated direct flux of nutrients from the ants to the host plant in a 15N pulse-chase experiment. As C. schmitzi ants only feed on nectar and pitcher contents of their host, the elevated foliar δ15N cannot be explained by classic ant-feeding (myrmecotrophy) but must originate from a higher efficiency of the pitcher traps. We discovered that C. schmitzi ants not only increase the pitchers' capture efficiency by keeping the pitchers’ trapping surfaces clean, but they also reduce nutrient loss from the pitchers by predating dipteran pitcher inhabitants (infauna). Consequently, nutrients the pitchers would have otherwise lost via emerging flies become available as ant colony waste. The plants’ prey is therefore conserved by the ants. The interaction between C. schmitzi, N. bicalcarata and dipteran pitcher infauna represents a new type of mutualism where animals mitigate the damage by nutrient thieves to a plant. PMID:23717446

Cuticular hydrocarbons correlate with queen reproductive status in native and invasive Argentine ants (Linepithema humile, Mayr).

PubMed

Abril, Sílvia; Diaz, Mireia; Lenoir, Alain; Ivon Paris, Carolina; Boulay, Raphaël; Gómez, Crisanto

2018-01-01

In insect societies, chemical communication plays an important role in colony reproduction and individual social status. Many studies have indicated that cuticular hydrocarbons (CHCs) are the main chemical compounds encoding reproductive status. However, these studies have largely focused on queenless or monogynous species whose workers are capable of egg laying and have mainly explored the mechanisms underlying queen-worker or worker-worker reproductive conflicts. Less is known about what occurs in highly polygynous ant species with permanently sterile workers. Here, we used the Argentine ant as a model to examine the role of CHCs in communicating reproductive information in such insect societies. The Argentine ant is unicolonial, highly polygynous, and polydomous. We identified several CHCs whose presence and levels were correlated with queen age, reproductive status, and fertility. Our results also provide new insights into queen executions in the Argentine ant, a distinctive feature displayed by this species in its introduced range. Each spring, just before new sexuals appear, workers eliminate up to 90% of the mated queens in their colonies. We discovered that queens that survived execution had different CHC profiles from queens present before and during execution. More specifically, levels of some CHCs were higher in the survivors, suggesting that workers could eliminate queens based on their chemical profiles. In addition, queen CHC profiles differed based on season and species range (native vs. introduced). Overall, the results of this study provide new evidence that CHCs serve as queen signals and do more than just regulate worker reproduction.

Nonlinear optimization simplified by hypersurface deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stillinger, F.H.; Weber, T.A.

1988-09-01

A general strategy is advanced for simplifying nonlinear optimization problems, the ant-lion method. This approach exploits shape modifications of the cost-function hypersurface which distend basins surrounding low-lying minima (including global minima). By intertwining hypersurface deformations with steepest-descent displacements, the search is concentrated on a small relevant subset of all minima. Specific calculations demonstrating the value of this method are reported for the partitioning of two classes of irregular but nonrandom graphs, the prime-factor graphs and the pi graphs. We also indicate how this approach can be applied to the traveling salesman problem and to design layout optimization, and that itmore » may be useful in combination with simulated annealing strategies.« less

Storage assignment optimization in a multi-tier shuttle warehousing system

NASA Astrophysics Data System (ADS)

Wang, Yanyan; Mou, Shandong; Wu, Yaohua

2016-03-01

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Enemy recognition is linked to soldier size in a polymorphic stingless bee.

PubMed

Grüter, Christoph; Segers, Francisca H I D; Santos, Luana L G; Hammel, Benedikt; Zimmermann, Uwe; Nascimento, Fabio S

2017-10-01

Many ant and termite colonies are defended by soldiers with powerful mandibles or chemical weaponry. Recently, it was reported that several stingless bee species also have soldiers for colony defence. These soldiers are larger than foragers, but otherwise lack obvious morphological adaptations for defence. Thus, how these soldiers improve colony fitness is not well understood. Robbing is common in stingless bees and we hypothesized that increased body size improves the ability to recognize intruders based on chemosensory cues. We studied the Neotropical species Tetragonisca angustula and found that large soldiers were better than small soldiers at recognizing potential intruders. Larger soldiers also had more olfactory pore plates on their antennae, which is likely to increase their chemosensory sensitivity. Our results suggest that improved enemy recognition might select for increased guard size in stingless bees. © 2017 The Author(s).

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and stillmore » serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.« less

Disease in the Society: Infectious Cadavers Result in Collapse of Ant Sub-Colonies.

PubMed

Loreto, Raquel G; Hughes, David P

2016-01-01

Despite the growing number of experimental studies on mechanisms of social immunity in ant societies, little is known about how social behavior relates to disease progression within the nests of ants. In fact, when empirically studying disease in ant societies, it is common to remove dead ants from experiments to confirm infection by the studied parasite. This unfortunately does not allow disease to progress within the nest as it may be assumed would happen under natural conditions. Therefore, the approach taken so far has resulted in a limited knowledge of diseases dynamics within the nest environment. Here we introduced a single infectious cadaver killed by the fungus Beauveria bassiana into small nests of the ant Camponotus castaneus. We then observed the natural progression of the disease by not removing the corpses of the ants that died following the first entry of the disease. Because some behaviors such as social isolation of sick individuals or the removal of cadavers by nestmates are considered social immune functions and thus adaptations at the colony level that reduce disease spread, we also experimentally confined some sub-colonies to one or two chamber nests to prevent the expression of such behaviors. Based on 51 small nests and survival studies in 1,003 ants we found that a single introduced infectious cadaver was able to transmit within the nest, and social immunity did not prevent the collapse of the small sub-colonies here tested. This was true whether ants did or did not have the option to remove the infectious cadaver. Therefore, we found no evidence that the typically studied social immunity behaviors can reduce disease spread in the conditions here tested.

Selection for protection in an ant–plant mutualism: host sanctions, host modularity, and the principal–agent game

PubMed Central

Edwards, David P; Hassall, Mark; Sutherland, William J; Yu, Douglas W

2005-01-01

Retaliation against cheaters can prevent the breakdown of cooperation. Here we ask whether the ant–plant Cordia nodosa is able to apply retaliatory sanctions against its ant symbiont Allomerus octoarticulatus, which patrols new shoots to prevent herbivory. We test the hypothesis that the modular design of C. nodosa physiologically ties the growth of housing (stem swellings known as domatia) to the successful development of the attached leaves. We experimentally simulated herbivory by cutting leaves from patrolled shoots and found that the domatia on such ‘cheated’ shoots suffered higher mortality and lower growth than did controls, evidence for a host sanction. On the other hand, patrolling is costly to the ant, and experiment shows that non-patrollers run a low risk of being sanctioned because most leaves (and the attached domatia) escape heavy herbivory even when patrollers are absent. This suggests that cheaters might enjoy a higher fitness than do mutualists, despite sanctions, but we find that patrolling provides a net fecundity benefit when the colony and plant exceed a minimum size, which requires sustained ant investment in patrolling. These results map directly onto the principal–agent (P–A) game from economics, which we suggest can be used as a framework for studying stability in mutualisms, where high sampling costs and cheating do not allow market effects to select for mutual benefits. PMID:16537131

Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

PubMed

Lin, Kuan-Cheng; Hsieh, Yi-Hsiu

2015-10-01

The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a problem of feature subset selection, such as combination optimization problems. Evolutionary algorithms using random search methods have proven highly effective in obtaining solutions to problems of optimization in a diversity of applications. In this study, we developed a hybrid evolutionary algorithm based on endocrine-based particle swarm optimization (EPSO) and artificial bee colony (ABC) algorithms in conjunction with a support vector machine (SVM) for the selection of optimal feature subsets for the classification of datasets. The results of experiments using specific UCI medical datasets demonstrate that the accuracy of the proposed hybrid evolutionary algorithm is superior to that of basic PSO, EPSO and ABC algorithms, with regard to classification accuracy using subsets with a reduced number of features.

Application of the artificial bee colony algorithm for solving the set covering problem.

PubMed

Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

2014-01-01

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.

Pyrokinin β-neuropeptide affects necrophoretic behavior in fire ants (S. invicta), and expression of β-NP in a mycoinsecticide increases its virulence.

PubMed

Fan, Yanhua; Pereira, Roberto M; Kilic, Engin; Casella, George; Keyhani, Nemat O

2012-01-01

Fire ants are one of the world's most damaging invasive pests, with few means for their effective control. Although ecologically friendly alternatives to chemical pesticides such as the insecticidal fungus Beauveria bassiana have been suggested for the control of fire ant populations, their use has been limited due to the low virulence of the fungus and the length of time it takes to kill its target. We present a means of increasing the virulence of the fungal agent by expressing a fire ant neuropeptide. Expression of the fire ant (Solenopsis invicta) pyrokinin β-neuropeptide (β-NP) by B. bassiana increased fungal virulence six-fold towards fire ants, decreased the LT(50), but did not affect virulence towards the lepidopteran, Galleria mellonella. Intriguingly, ants killed by the β-NP expressing fungus were disrupted in the removal of dead colony members, i.e. necrophoretic behavior. Furthermore, synthetic C-terminal amidated β-NP but not the non-amidated peptide had a dramatic effect on necrophoretic behavior. These data link chemical sensing of a specific peptide to a complex social behavior. Our results also confirm a new approach to insect control in which expression of host molecules in an insect pathogen can by exploited for target specific augmentation of virulence. The minimization of the development of potential insect resistance by our approach is discussed.

Chemical Characterization of Young Virgin Queens and Mated Egg-Laying Queens in the Ant Cataglyphis cursor: Random Forest Classification Analysis for Multivariate Datasets.

PubMed

Monnin, Thibaud; Helft, Florence; Leroy, Chloé; d'Ettorre, Patrizia; Doums, Claudie

2018-02-01

Social insects are well known for their extremely rich chemical communication, yet their sex pheromones remain poorly studied. In the thermophilic and thelytokous ant, Cataglyphis cursor, we analyzed the cuticular hydrocarbon profiles and Dufour's gland contents of queens of different age and reproductive status (sexually immature gynes, sexually mature gynes, mated and egg-laying queens) and of workers. Random forest classification analyses showed that the four groups of individuals were well separated for both chemical sources, except mature gynes that clustered with queens for cuticular hydrocarbons and with immature gynes for Dufour's gland secretions. Analyses carried out with two groups of females only allowed identification of candidate chemicals for queen signal and for sexual attractant. In particular, gynes produced more undecane in the Dufour's gland. This chemical is both the sex pheromone and the alarm pheromone of the ant Formica lugubris. It may therefore act as sex pheromone in C. cursor, and/or be involved in the restoration of monogyny that occurs rapidly following colony fission. Indeed, new colonies often start with several gynes and all but one are rapidly culled by workers, and this process likely involves chemical signals between gynes and workers. These findings open novel opportunities for experimental studies of inclusive mate choice and queen choice in C. cursor.

Pyrokinin β-Neuropeptide Affects Necrophoretic Behavior in Fire Ants (S. invicta), and Expression of β-NP in a Mycoinsecticide Increases Its Virulence

PubMed Central

Fan, Yanhua; Pereira, Roberto M.; Kilic, Engin; Casella, George; Keyhani, Nemat O.

2012-01-01

Fire ants are one of the world's most damaging invasive pests, with few means for their effective control. Although ecologically friendly alternatives to chemical pesticides such as the insecticidal fungus Beauveria bassiana have been suggested for the control of fire ant populations, their use has been limited due to the low virulence of the fungus and the length of time it takes to kill its target. We present a means of increasing the virulence of the fungal agent by expressing a fire ant neuropeptide. Expression of the fire ant (Solenopsis invicta) pyrokinin β -neuropeptide (β-NP) by B. bassiana increased fungal virulence six-fold towards fire ants, decreased the LT50, but did not affect virulence towards the lepidopteran, Galleria mellonella. Intriguingly, ants killed by the β-NP expressing fungus were disrupted in the removal of dead colony members, i.e. necrophoretic behavior. Furthermore, synthetic C-terminal amidated β-NP but not the non-amidated peptide had a dramatic effect on necrophoretic behavior. These data link chemical sensing of a specific peptide to a complex social behavior. Our results also confirm a new approach to insect control in which expression of host molecules in an insect pathogen can by exploited for target specific augmentation of virulence. The minimization of the development of potential insect resistance by our approach is discussed. PMID:22238569

Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem

PubMed Central

Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

2014-01-01

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem. PMID:24883356

Variation in spatial scale of competing polydomous twig-nesting ants in coffee agroecosystems

PubMed Central

Mathis, Kaitlyn A.; Philpott, Stacy M.; Ramirez, Santiago R.

2016-01-01

Arboreal ants are both highly diverse and ecologically dominant in the tropics. This ecologically important group is particularly useful in ongoing efforts to understand processes that regulate species diversity and coexistence. Our study addresses how polydomy can influence patterns of nest occupation in competing arboreal ants. We examined the spatial structure of nest occupation (nest distance, abundance and density) in three polydomous co-occurring twig-nesting ant species (Pseudomyrmex simplex, P. ejectus and P. PSW-53) by mapping twigs occupied by ants from each species within plots in our study site. We then used two colony structure estimators (intraspecific aggression and cuticular hydrocarbon variation) to determine the relative degree of polydomy for each species. All work was conducted in coffee agroforests in Chiapas, Mexico. Our results revealed that the two species with highest abundance and nest density were also highly polydomous, where both species had either single or multiple non-aggressive colonies occupying nests on a large spatial scale (greater than the hectare level). Our results also indicate that the species with the lowest abundance and density is less polydomous, occupying several overlapping and territorial colonies at the hectare level in which multiple colonies never co-occur on the same host plant. These results contribute evidence that successful coexistence and highly polydomous colony structure may allow ants, through reduced intraspecific aggression, to successfully occupy more nests more densely than ant species that have multiple territorial colonies. Furthermore our study highlights the importance of considering intraspecific interactions when examining community assembly of ants. PMID:27795573

Specialization and group size: brain and behavioural correlates of colony size in ants lacking morphological castes

PubMed Central

Amador-Vargas, Sabrina; Gronenberg, Wulfila; Wcislo, William T.; Mueller, Ulrich

2015-01-01

Group size in both multicellular organisms and animal societies can correlate with the degree of division of labour. For ants, the task specialization hypothesis (TSH) proposes that increased behavioural specialization enabled by larger group size corresponds to anatomical specialization of worker brains. Alternatively, the social brain hypothesis proposes that increased levels of social stimuli in larger colonies lead to enlarged brain regions in all workers, regardless of their task specialization. We tested these hypotheses in acacia ants (Pseudomyrmex spinicola), which exhibit behavioural but not morphological task specialization. In wild colonies, we marked, followed and tested ant workers involved in foraging tasks on the leaves (leaf-ants) and in defensive tasks on the host tree trunk (trunk-ants). Task specialization increased with colony size, especially in defensive tasks. The relationship between colony size and brain region volume was task-dependent, supporting the TSH. Specifically, as colony size increased, the relative size of regions within the mushroom bodies of the brain decreased in trunk-ants but increased in leaf-ants; those regions play important roles in learning and memory. Our findings suggest that workers specialized in defence may have reduced learning abilities relative to leaf-ants; these inferences remain to be tested. In societies with monomorphic workers, brain polymorphism enhanced by group size could be a mechanism by which division of labour is achieved. PMID:25567649

Host Plant Use by Competing Acacia-Ants: Mutualists Monopolize While Parasites Share Hosts

PubMed Central

Kautz, Stefanie; Ballhorn, Daniel J.; Kroiss, Johannes; Pauls, Steffen U.; Moreau, Corrie S.; Eilmus, Sascha; Strohm, Erhard; Heil, Martin

2012-01-01

Protective ant-plant mutualisms that are exploited by non-defending parasitic ants represent prominent model systems for ecology and evolutionary biology. The mutualist Pseudomyrmex ferrugineus is an obligate plant-ant and fully depends on acacias for nesting space and food. The parasite Pseudomyrmex gracilis facultatively nests on acacias and uses host-derived food rewards but also external food sources. Integrative analyses of genetic microsatellite data, cuticular hydrocarbons and behavioral assays showed that an individual acacia might be inhabited by the workers of several P. gracilis queens, whereas one P. ferrugineus colony monopolizes one or more host trees. Despite these differences in social organization, neither of the species exhibited aggressive behavior among conspecific workers sharing a tree regardless of their relatedness. This lack of aggression corresponds to the high similarity of cuticular hydrocarbon profiles among ants living on the same tree. Host sharing by unrelated colonies, or the presence of several queens in a single colony are discussed as strategies by which parasite colonies could achieve the observed social organization. We argue that in ecological terms, the non-aggressive behavior of non-sibling P. gracilis workers — regardless of the route to achieve this social structure — enables this species to efficiently occupy and exploit a host plant. By contrast, single large and long-lived colonies of the mutualist P. ferrugineus monopolize individual host plants and defend them aggressively against invaders from other trees. Our findings highlight the necessity for using several methods in combination to fully understand how differing life history strategies affect social organization in ants. PMID:22662191

Immune defense in leaf-cutting ants: a cross-fostering approach.

PubMed

Armitage, Sophie A O; Broch, Jens F; Marín, Hermogenes Fernández; Nash, David R; Boomsma, Jacobus J

2011-06-01

To ameliorate the impact of disease, social insects combine individual innate immune defenses with collective social defenses. This implies that there are different levels of selection acting on investment in immunity, each with their own trade-offs. We present the results of a cross-fostering experiment designed to address the influences of genotype and social rearing environment upon individual and social immune defenses. We used a multiply mating leaf-cutting ant, enabling us to test for patriline effects within a colony, as well as cross-colony matriline effects. The worker's father influenced both individual innate immunity (constitutive antibacterial activity) and the size of the metapleural gland, which secretes antimicrobial compounds and functions in individual and social defense, indicating multiple mating could have important consequences for both defense types. However, the primarily social defense, a Pseudonocardia bacteria that helps to control pathogens in the ants' fungus garden, showed a significant colony of origin by rearing environment interaction, whereby ants that acquired the bacteria of a foster colony obtained a less abundant cover of bacteria: one explanation for this pattern would be co-adaptation between host colonies and their vertically transmitted mutualist. These results illustrate the complexity of the selection pressures that affect the expression of multilevel immune defenses. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

Disease in the Society: Infectious Cadavers Result in Collapse of Ant Sub-Colonies

PubMed Central

Loreto, Raquel G.; Hughes, David P.

2016-01-01

Despite the growing number of experimental studies on mechanisms of social immunity in ant societies, little is known about how social behavior relates to disease progression within the nests of ants. In fact, when empirically studying disease in ant societies, it is common to remove dead ants from experiments to confirm infection by the studied parasite. This unfortunately does not allow disease to progress within the nest as it may be assumed would happen under natural conditions. Therefore, the approach taken so far has resulted in a limited knowledge of diseases dynamics within the nest environment. Here we introduced a single infectious cadaver killed by the fungus Beauveria bassiana into small nests of the ant Camponotus castaneus. We then observed the natural progression of the disease by not removing the corpses of the ants that died following the first entry of the disease. Because some behaviors such as social isolation of sick individuals or the removal of cadavers by nestmates are considered social immune functions and thus adaptations at the colony level that reduce disease spread, we also experimentally confined some sub-colonies to one or two chamber nests to prevent the expression of such behaviors. Based on 51 small nests and survival studies in 1,003 ants we found that a single introduced infectious cadaver was able to transmit within the nest, and social immunity did not prevent the collapse of the small sub-colonies here tested. This was true whether ants did or did not have the option to remove the infectious cadaver. Therefore, we found no evidence that the typically studied social immunity behaviors can reduce disease spread in the conditions here tested. PMID:27529548

Genetic diversity promotes homeostasis in insect colonies.

PubMed

Oldroyd, Benjamin P; Fewell, Jennifer H

2007-08-01

Although most insect colonies are headed by a singly mated queen, some ant, wasp and bee taxa have evolved high levels of multiple mating or 'polyandry'. We argue here that a contributing factor towards the evolution of polyandry is that the resulting genetic diversity within colonies provides them with a system of genetically based task specialization, enabling them to respond resiliently to environmental perturbation. An alternate view is that genetic contributions to task specialization are a side effect of multiple mating, which evolved through other causes, and that genetically based task specialization now makes little or no contribution to colony fitness.

A new improved artificial bee colony algorithm for ship hull form optimization

NASA Astrophysics Data System (ADS)

Huang, Fuxin; Wang, Lijue; Yang, Chi

2016-04-01

The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

NASA Astrophysics Data System (ADS)

Ellappan, Vijayan; Ashwini, J.

2017-11-01

In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

Non-transferable signals on ant queen eggs

NASA Astrophysics Data System (ADS)

D'Ettorre, Patrizia; Tofilski, Adam; Heinze, Jürgen; Ratnieks, Francis L. W.

2006-03-01

How biological systems resolve internal conflicts is a major evolutionary question. Social insect workers cooperate but also pursue individual interests, such as laying male eggs. The rewards of this individual selfishness can be reduced by policing, such as by killing worker-laid eggs. However, selfish individuals may evade policing. What factors prevent individuals from being able to evade policing? In the ant Pachycondyla inversa, workers kill (police) worker-laid eggs. Because the colony keeps eggs in piles and worker-laid and queen-laid eggs are chemically distinct, worker-laid eggs might become more acceptable once placed in the egg pile by odour transfer from touching queen-laid eggs. Here, we show that such “cue scrambling” does not occur. Worker-laid eggs that were sandwiched between three queen-laid eggs for 45 min were not more acceptable in a policing bioassay than control worker-laid eggs. Chemical analyses also showed that the surface hydrocarbon profile of these eggs was unchanged. Policing, therefore, is stable against this potential cheating mechanism probably because queen-laid eggs are made chemically distinct using chemicals, that are not easily transferred by physical contact.

Spatial grain and the causes of regional diversity gradients in ants.

PubMed

Kaspari, Michael; Yuan, May; Alonso, Leeanne

2003-03-01

Gradients of species richness (S; the number of species of a given taxon in a given area and time) are ubiquitous. A key goal in ecology is to understand whether and how the many processes that generate these gradients act at different spatial scales. Here we evaluate six hypotheses for diversity gradients with 49 New World ant communities, from tundra to rain forest. We contrast their performance at three spatial grains from S(plot), the average number of ant species nesting in a m2 plot, through Fisher's alpha, an index that treats our 30 1-m2 plots as subsamples of a locality's diversity. At the smallest grain, S(plot), was tightly correlated (r2 = 0.99) with colony abundance in a fashion indistinguishable from the packing of randomly selected individuals into a fixed space. As spatial grain increased, the coaction of two factors linked to high net rates of diversification--warm temperatures and large areas of uniform climate--accounted for 75% of the variation in Fisher's alpha. However, the mechanisms underlying these correlations (i.e., precisely how temperature and area shape the balance of speciation to extinction) remain elusive.

Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization

PubMed Central

Zhu, Zhouquan

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions. PMID:24385879

Differential Sharing of Chemical Cues by Social Parasites Versus Social Mutualists in a Three-Species Symbiosis.

PubMed

Emery, Virginia J; Tsutsui, Neil D

2016-04-01

Chemical recognition systems are crucial for maintaining the unity of social insect colonies. It has been proposed that colonies form a common chemical signature, called the gestalt odor, which is used to distinguish colony members and non-members. This chemical integration is achieved actively through social interactions such as trophallaxis and allogrooming, or passively such as through exposure to common nest material. When colonies are infiltrated by social parasites, the intruders often use some form of chemical mimicry. However, it is not always clear how this chemical mimicry is accomplished. Here, we used a three-species nesting symbiosis to test the differences in chemical integration of mutualistic (parabiotic) and parasitic ant species. We found that the parasite (Solenopsis picea) obtains chemical cues from both of the two parabiotic host ant species. However, the two parabiotic species (Crematogaster levior and Camponotus femoratus) maintain species-specific cues, and do not acquire compounds from the other species. Our findings suggest that there is a fundamental difference in how social mutualists and social parasites use chemicals to integrate themselves into colonies.

Seasonal Life Cycle of Linepithema micans (Forel) (Hymenoptera: Formicidae) in Vineyards.

PubMed

Nondillo, A; Baronio, C A; Bernardi, D; Bueno, O C; Botton, M

2016-08-01

Linepithema micans (Forel) is considered to be the main ant species responsible for the spread of Eurhizococcus brasiliensis (Wille), a soil scale that damages vine plants in southern Brazil. In this work, the seasonal life cycle of L. micans was evaluated in vineyards to define the most appropriate time for the application of toxic baits for control. Ant nests were transported to the laboratory in plastic bags, and individual ants were separated into groups of eggs, larvae, pupae, workers, males, and queens, recording the number of individuals per colony. The seasonal life cycle of L. micans in the vineyards began in spring with the deposition of eggs by queens. During the warm months of the year (spring and summer), it was possible to observe nests consisting primarily of eggs and pupae. During the autumn and winter months, the colonies were composed predominantly of larvae and a reduction in eggs was observed. Because the main control strategy targets the larval stage of the insect, the application of toxic baits for the control of L. micans must be performed during the winter.

Defensive traits exhibit an evolutionary trade-off and drive diversification in ants.

PubMed

Blanchard, Benjamin D; Moreau, Corrie S

2017-02-01

Evolutionary biologists have long predicted that evolutionary trade-offs among traits should constrain morphological divergence and species diversification. However, this prediction has yet to be tested in a broad evolutionary context in many diverse clades, including ants. Here, we reconstruct an expanded ant phylogeny representing 82% of ant genera, compile a new family-wide trait database, and conduct various trait-based analyses to show that defensive traits in ants do exhibit an evolutionary trade-off. In particular, the use of a functional sting negatively correlates with a suite of other defensive traits including spines, large eye size, and large colony size. Furthermore, we find that several of the defensive traits that trade off with a sting are also positively correlated with each other and drive increased diversification, further suggesting that these traits form a defensive suite. Our results support the hypothesis that trade-offs in defensive traits significantly constrain trait evolution and influence species diversification in ants. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Raman spectral feature selection using ant colony optimization for breast cancer diagnosis.

PubMed

Fallahzadeh, Omid; Dehghani-Bidgoli, Zohreh; Assarian, Mohammad

2018-06-04

Pathology as a common diagnostic test of cancer is an invasive, time-consuming, and partially subjective method. Therefore, optical techniques, especially Raman spectroscopy, have attracted the attention of cancer diagnosis researchers. However, as Raman spectra contain numerous peaks involved in molecular bounds of the sample, finding the best features related to cancerous changes can improve the accuracy of diagnosis in this method. The present research attempted to improve the power of Raman-based cancer diagnosis by finding the best Raman features using the ACO algorithm. In the present research, 49 spectra were measured from normal, benign, and cancerous breast tissue samples using a 785-nm micro-Raman system. After preprocessing for removal of noise and background fluorescence, the intensity of 12 important Raman bands of the biological samples was extracted as features of each spectrum. Then, the ACO algorithm was applied to find the optimum features for diagnosis. As the results demonstrated, by selecting five features, the classification accuracy of the normal, benign, and cancerous groups increased by 14% and reached 87.7%. ACO feature selection can improve the diagnostic accuracy of Raman-based diagnostic models. In the present study, features corresponding to ν(C-C) αhelix proline, valine (910-940), νs(C-C) skeletal lipids (1110-1130), and δ(CH2)/δ(CH3) proteins (1445-1460) were selected as the best features in cancer diagnosis.

Targeted Removal of Ant Colonies in Ecological Experiments, Using Hot Water

PubMed Central

Tschinkel, Walter R.; King, Joshua R.

2007-01-01

Ecological experiments on fire ants cannot, or should not, use poison baits to eliminate the fire ants because such baits are not specific to fire ants, or even to ants. Hot water is an extremely effective and specific killing agent for fire ant colonies, but producing large amounts of hot water in the field, and making the production apparatus mobile have been problematical. The construction and use of a charcoal-fired kiln made from a 55-gal. oil drum lined with a sand-fireclay mixture is described. An automobile heater fan powered from a 12-v battery provided a draft. Dual bilge pumps pumped water from a large tank through a long coil of copper tubing within the kiln to produce 4 to 5 l. of hot water per min. The hot water was collected in 20 l. buckets and poured into fire ant nests previously opened by piercing with a stick. The entire assembly was transported in and operated from the back of a pickup truck. Five experimental plots containing 32 to 38 colonies of the fire ant, Solenopsis invicta, Buren (Hymenoptera: Formicidae), were treated with hot water over a period of two years. All colonies on the treatment plots were treated twice with hot water early in 2004, reducing their numbers to zero. However new colonies were formed, and mature colonies expanded into the plots. A third treatment was made in the spring of 2005, after which fire ant populations were suppressed for over a year. Whereas the 5 control plots contained a total of 166 mostly large colonies, the 5 treatment plots contained no live colonies at all. Averaged over a two-year period, a 70% reduction in total number of colonies was achieved (P < 0.001) on the treatment plots, and a 93% reduction of large, mature colonies. Over this same time span, the number of colonies in control plots remained stable. The reduction in colony numbers on the treatment plots was reflected in the pitfall trap samples that recorded a 60% reduction in fire ants. PMID:20233079

ABCluster: the artificial bee colony algorithm for cluster global optimization.

PubMed

Zhang, Jun; Dolg, Michael

2015-10-07

Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

Seven-spot ladybird optimization: a novel and efficient metaheuristic algorithm for numerical optimization.

PubMed

Wang, Peng; Zhu, Zhouquan; Huang, Shuai

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.

Non-transferable signals on ant queen eggs.

PubMed

D'Ettorre, Patrizia; Tofilski, Adam; Heinze, Jürgen; Ratnieks, Francis L W

2006-03-01

How biological systems resolve internal conflicts is a major evolutionary question. Social insect workers cooperate but also pursue individual interests, such as laying male eggs. The rewards of this individual selfishness can be reduced by policing, such as by killing worker-laid eggs. However, selfish individuals may evade policing. What factors prevent individuals from being able to evade policing? In the ant Pachycondyla inversa, workers kill (police) worker-laid eggs. Because the colony keeps eggs in piles and worker-laid and queen-laid eggs are chemically distinct, worker-laid eggs might become more acceptable once placed in the egg pile by odour transfer from touching queen-laid eggs. Here, we show that such "cue scrambling" does not occur. Worker-laid eggs that were sandwiched between three queen-laid eggs for 45 min were not more acceptable in a policing bioassay than control worker-laid eggs. Chemical analyses also showed that the surface hydrocarbon profile of these eggs was unchanged. Policing, therefore, is stable against this potential cheating mechanism probably because queen-laid eggs are made chemically distinct using chemicals, that are not easily transferred by physical contact.

A hybrid artificial bee colony algorithm for numerical function optimization

NASA Astrophysics Data System (ADS)

Alqattan, Zakaria N.; Abdullah, Rosni

2015-02-01

Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).

Oral transfer of chemical cues, growth proteins and hormones in social insects

PubMed Central

LeBoeuf, Adria C; Waridel, Patrice; Brent, Colin S; Gonçalves, Andre N; Menin, Laure; Ortiz, Daniel; Riba-Grognuz, Oksana; Koto, Akiko; Soares, Zamira G; Privman, Eyal; Miska, Eric A; Benton, Richard; Keller, Laurent

2016-01-01

Social insects frequently engage in oral fluid exchange – trophallaxis – between adults, and between adults and larvae. Although trophallaxis is widely considered a food-sharing mechanism, we hypothesized that endogenous components of this fluid might underlie a novel means of chemical communication between colony members. Through protein and small-molecule mass spectrometry and RNA sequencing, we found that trophallactic fluid in the ant Camponotus floridanus contains a set of specific digestion- and non-digestion related proteins, as well as hydrocarbons, microRNAs, and a key developmental regulator, juvenile hormone. When C. floridanus workers’ food was supplemented with this hormone, the larvae they reared via trophallaxis were twice as likely to complete metamorphosis and became larger workers. Comparison of trophallactic fluid proteins across social insect species revealed that many are regulators of growth, development and behavioral maturation. These results suggest that trophallaxis plays previously unsuspected roles in communication and enables communal control of colony phenotypes. DOI: http://dx.doi.org/10.7554/eLife.20375.001 PMID:27894417

Isolating antifungals from fungus-growing ant symbionts using a genome-guided chemistry approach.

PubMed

Seipke, Ryan F; Grüschow, Sabine; Goss, Rebecca J M; Hutchings, Matthew I

2012-01-01

We describe methods used to isolate and identify antifungal compounds from actinomycete strains associated with the leaf-cutter ant Acromyrmex octospinosus. These ants use antibiotics produced by symbiotic actinomycete bacteria to protect themselves and their fungal cultivar against bacterial and fungal infections. The fungal cultivar serves as the sole food source for the ant colony, which can number up to tens of thousands of individuals. We describe how we isolate bacteria from leaf-cutter ants collected in Trinidad and analyze the antifungal compounds made by two of these strains (Pseudonocardia and Streptomyces spp.), using a combination of genome analysis, mutagenesis, and chemical isolation. These methods should be generalizable to a wide variety of insect-symbiont situations. Although more time consuming than traditional activity-guided fractionation methods, this approach provides a powerful technique for unlocking the complete biosynthetic potential of individual strains and for avoiding the problems of rediscovery of known compounds. We describe the discovery of a novel nystatin compound, named nystatin P1, and identification of the biosynthetic pathway for antimycins, compounds that were first described more than 60 years ago. We also report that disruption of two known antifungal pathways in a single Streptomyces strain has revealed a third, and likely novel, antifungal plus four more pathways with unknown products. This validates our approach, which clearly has the potential to identify numerous new compounds, even from well-characterized actinomycete strains. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of the selection methods used in the exIWO algorithm based on the optimization of multidimensional functions

NASA Astrophysics Data System (ADS)

Kostrzewa, Daniel; Josiński, Henryk

2016-06-01

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version inspired by dynamic growth of weeds colony. The authors of the present paper have modified the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals' selection. The goal of the project was to evaluate the modified exIWO by testing its usefulness for multidimensional numerical functions optimization. The optimized functions: Griewank, Rastrigin, and Rosenbrock are frequently used as benchmarks because of their characteristics.

Targeted removal of ant colonies in ecological experiments, using hot water.

PubMed

Tschinkel, Walter R; King, Joshua R

2007-01-01

Ecological experiments on fire ants cannot, or should not, use poison baits to eliminate the fire ants because such baits are not specific to fire ants, or even to ants. Hot water is an extremely effective and specific killing agent for fire ant colonies, but producing large amounts of hot water in the field, and making the production apparatus mobile have been problematical. The construction and use of a charcoal-fired kiln made from a 55-gal. oil drum lined with a sand-fireclay mixture is described. An automobile heater fan powered from a 12-v battery provided a draft. Dual bilge pumps pumped water from a large tank through a long coil of copper tubing within the kiln to produce 4 to 5 l. of hot water per min. The hot water was collected in 20 l. buckets and poured into fire ant nests previously opened by piercing with a stick. The entire assembly was transported in and operated from the back of a pickup truck. Five experimental plots containing 32 to 38 colonies of the fire ant, Solenopsis invicta, Buren (Hymenoptera: Formicidae), were treated with hot water over a period of two years. All colonies on the treatment plots were treated twice with hot water early in 2004, reducing their numbers to zero. However new colonies were formed, and mature colonies expanded into the plots. A third treatment was made in the spring of 2005, after which fire ant populations were suppressed for over a year. Whereas the 5 control plots contained a total of 166 mostly large colonies, the 5 treatment plots contained no live colonies at all. Averaged over a two-year period, a 70% reduction in total number of colonies was achieved (P < 0.001) on the treatment plots, and a 93% reduction of large, mature colonies. Over this same time span, the number of colonies in control plots remained stable. The reduction in colony numbers on the treatment plots was reflected in the pitfall trap samples that recorded a 60% reduction in fire ants.

Nest odor dynamics in the social wasp Vespula vulgaris

NASA Astrophysics Data System (ADS)

Steinmetz, Inge; Schmolz, Erik

2005-09-01

We investigated nest odor dynamics in the common yellow jacket, Vespula vulgaris. In six isolated colonies, we tested the aggression rates toward dead nestmates that had been stored for 10 min, 10 and 19 days outside their colonies at 76 °C. The aggression rate increased from about 12% toward recently killed nestmates up to 30% toward nestmates killed 19 days before the experiment. Obviously, the conserved nest odor profile of the nestmates frozen for several days did not match with that of their colony anymore. This indicates a change of the nest odor within the colony. In a second experiment, we kept two colonies each in one nest box with a complete separation of both neighbor nests by a solid wall inside the box for 28 days. In confrontation experiments, the colony members treated dead foragers from the neighbor nest as aggressively as dead foreign, non-neighbor workers (about 39% each) whereas only about 14% reacted aggressively toward dead nestmates. Seventeen days after the replacement of the solid wall by a metallic grid, which allowed no physical contact but air exchange between the two neighbor colonies, the aggression rates toward foreign workers and nestmates remained relatively unaffected whereas it decreased significantly toward dead neighbors to about 11%. These results suggest a nest odor dynamic caused by volatiles transferred between two adjacent colonies, resulting in an equalization of the former colony specific nest odors. A change of nest odor dynamics influenced by volatiles was so far described only for one ant species at all.

Knowing your enemies: seasonal dynamics of host-social parasite recognition.

PubMed

D'Ettorre, Patrizia; Brunner, Elisabeth; Wenseleers, Tom; Heinze, Jürgen

2004-12-01

Despite its evolutionary significance, behavioural flexibility of social response has rarely been investigated in insects. We studied a host-social parasite system: the slave-making ant Polyergus rufescens and its host Formica rufibarbis. Free-living host workers from parasitized and from unparasitized areas were compared in their level of aggression against the parasite and alien conspecifics. We expected that a seasonal change would occur in the acceptance threshold of F. rufibarbis workers from a parasitized area towards the parasite, whereas F. rufibarbis workers from an unparasitized area would not show substantial changes connected with the parasite's peak in activity (raiding and colony-founding season). The results showed a significant adaptive behavioural flexibility of host species workers and are consistent with the acceptance threshold model's (Reeve 1989) prediction that recognition systems are not fixed but context-dependent. In particular, host workers from the unparasitized area were highly aggressive towards the parasite regardless of the season, whereas host workers from the parasitized area significantly increased their aggression towards the parasite during its raiding and colony-founding season. Being able to detect and possibly kill a Polyergus scout searching for host nests can be an effective strategy for a Formica colony to avoid being raided or usurped by a parasite queen.

Knowing your enemies: seasonal dynamics of host social parasite recognition

NASA Astrophysics Data System (ADS)

D'Ettorre, Patrizia; Brunner, Elisabeth; Wenseleers, Tom; Heinze, Jürgen

2004-12-01

Despite its evolutionary significance, behavioural flexibility of social response has rarely been investigated in insects. We studied a host social parasite system: the slave-making ant Polyergus rufescens and its host Formica rufibarbis. Free-living host workers from parasitized and from unparasitized areas were compared in their level of aggression against the parasite and alien conspecifics. We expected that a seasonal change would occur in the acceptance threshold of F. rufibarbis workers from a parasitized area towards the parasite, whereas F. rufibarbis workers from an unparasitized area would not show substantial changes connected with the parasite’s peak in activity (raiding and colony-founding season). The results showed a significant adaptive behavioural flexibility of host species workers and are consistent with the acceptance threshold model’s (Reeve 1989) prediction that recognition systems are not fixed but context-dependent. In particular, host workers from the unparasitized area were highly aggressive towards the parasite regardless of the season, whereas host workers from the parasitized area significantly increased their aggression towards the parasite during its raiding and colony-founding season. Being able to detect and possibly kill a Polyergus scout searching for host nests can be an effective strategy for a Formica colony to avoid being raided or usurped by a parasite queen.

An adaptive grid algorithm for 3-D GIS landform optimization based on improved ant algorithm

NASA Astrophysics Data System (ADS)

Wu, Chenhan; Meng, Lingkui; Deng, Shijun

2005-07-01

The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ˜τj to ∆τj+σi and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.

Specialization and group size: brain and behavioural correlates of colony size in ants lacking morphological castes.

PubMed

Amador-Vargas, Sabrina; Gronenberg, Wulfila; Wcislo, William T; Mueller, Ulrich

2015-02-22

Group size in both multicellular organisms and animal societies can correlate with the degree of division of labour. For ants, the task specialization hypothesis (TSH) proposes that increased behavioural specialization enabled by larger group size corresponds to anatomical specialization of worker brains. Alternatively, the social brain hypothesis proposes that increased levels of social stimuli in larger colonies lead to enlarged brain regions in all workers, regardless of their task specialization. We tested these hypotheses in acacia ants (Pseudomyrmex spinicola), which exhibit behavioural but not morphological task specialization. In wild colonies, we marked, followed and tested ant workers involved in foraging tasks on the leaves (leaf-ants) and in defensive tasks on the host tree trunk (trunk-ants). Task specialization increased with colony size, especially in defensive tasks. The relationship between colony size and brain region volume was task-dependent, supporting the TSH. Specifically, as colony size increased, the relative size of regions within the mushroom bodies of the brain decreased in trunk-ants but increased in leaf-ants; those regions play important roles in learning and memory. Our findings suggest that workers specialized in defence may have reduced learning abilities relative to leaf-ants; these inferences remain to be tested. In societies with monomorphic workers, brain polymorphism enhanced by group size could be a mechanism by which division of labour is achieved. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

A Novel Extraction Approach of Extrinsic and Intrinsic Parameters of InGaAs/GaN pHEMTs

DTIC Science & Technology

2015-07-01

presented, for the first time, artificial bee colony algorithm is applied to the global-optimization based parameter extraction and a novel intrinsic...conservation of the gate charge is well satisfied which further validates this novel extraction method. Index Terms —InGaAs/GaN pHEMTs, artificial bee ...increase the uniqueness of the extraction. Artificial bee colony (ABC) algorithm is adopted as the optimizer due to its excellent ability to escape

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

A performance evaluation of ACO and SA TSP in a supply chain network

NASA Astrophysics Data System (ADS)

Rao, T. Srinivas

2017-07-01

Supply Chain management and E commerce business solutions are one of the prominent areas of active research. In our paper we have modelled a supply chain model which aggregates all the manufacturers requirement and the products are supplied to all the manufacturer through a common vehicle routing algorithm. An appropriate tsp has been constructed for all the manufacturers which determines the shortest route thru which the aggregated material can be supplied in the shortest possible time. In this paper we have solved the shortest route through constructing a Simulated annealing algorithm and Ant colony algorithm and their performance is evaluated.

Fermat’s Principle of Least Time Predicts Refraction of Ant Trails at Substrate Borders

PubMed Central

Zankl, Niko; Rey, Olivier; Dress, Andreas; Heinze, Jürgen

2013-01-01

Fermat’s principle of least time states that light rays passing through different media follow the fastest (and not the most direct) path between two points, leading to refraction at medium borders. Humans intuitively employ this rule, e.g., when a lifeguard has to infer the fastest way to traverse both beach and water to reach a swimmer in need. Here, we tested whether foraging ants also follow Fermat’s principle when forced to travel on two surfaces that differentially affected the ants’ walking speed. Workers of the little fire ant, Wasmannia auropunctata, established “refracted” pheromone trails to a food source. These trails deviated from the most direct path, but were not different to paths predicted by Fermat’s principle. Our results demonstrate a new aspect of decentralized optimization and underline the versatility of the simple yet robust rules governing the self-organization of group-living animals. PMID:23527263

Leucoagaricus gongylophorus Produces Diverse Enzymes for the Degradation of Recalcitrant Plant Polymers in Leaf-Cutter Ant Fungus Gardens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aylward, Frank O.; Burnum-Johnson, Kristin E.; Tringe, Susannah G.

Plants represent a large reservoir of organic carbon comprised largely of recalcitrant polymers that most metazoans are unable to deconstruct. Many herbivores gain access to nutrients in this material indirectly by associating with microbial symbionts, and leaf-cutter ants are a paradigmatic example. These ants use fresh foliar biomass as manure to cultivate fungus gardens composed primarily of Leucoagaricus gongylophorus, a basidiomycetous symbiont that produces specialized hyphal swellings that serve as a food source for the host ant colony. Although leaf-cutter ants are conspicuous herbivores that contribute substantially to carbon turnover in Neotropical ecosystems, the process through which plant biomass ismore » degraded in their fungus gardens is not well understood. Here we present the first draft genome of L. gongylophorus, and using genomic, metaproteomic, and phylogenetic tools we investigate its role in lignocellulose degradation in the fungus gardens of both Atta cephalotes and Acromyrmex echinatior leaf-cutter ants. We show that L. gongylophorus produces a diversity of lignocellulases in fungus gardens, and is likely the primary driver of plant biomass degradation in these ecosystems. We also show that this fungus produces distinct sets of lignocellulases throughout the different stages of biomass degradation, including numerous cellulases and laccases that may be playing an important but previously uncharacterized role in lignocellulose degradation. Our study provides a comprehensive analysis of plant biomass degradation in leaf-cutter ant fungus gardens and provides insight into the molecular dynamics underlying the symbiosis between these dominant herbivores and their obligate fungal cultivar.« less

Distributed leadership and adaptive decision-making in the ant Tetramorium caespitum.

PubMed

Collignon, B; Detrain, C

2010-04-22

In the ant species Tetramorium caespitum, communication and foraging patterns rely on group-mass recruitment. Scouts having discovered food recruit nestmates and behave as leaders by guiding groups of recruits to the food location. After a while, a mass recruitment takes place in which foragers follow a chemical trail. Since group recruitment is crucial to the whole foraging process, we investigated whether food characteristics induce a tuning of recruiting stimuli by leaders that act upon the dynamics and size of recruited groups. High sucrose concentration triggers the exit of a higher number of groups that contain twice as many ants and reach the food source twice as fast than towards a weakly concentrated one. Similar trends were found depending on food accessibility: for a cut mealworm, accessibility to haemolymph results in a faster formation of larger groups than for an entire mealworm. These data provide the background for developing a stochastic model accounting for exploitation patterns by group-mass recruiting species. This model demonstrates how the modulations performed by leaders drive the colony to select the most profitable food source among several ones. Our results highlight how a minority of individuals can influence collective decisions in societies based on a distributed leadership.

Response threshold variance as a basis of collective rationality

PubMed Central

Yamamoto, Tatsuhiro

2017-01-01

Determining the optimal choice among multiple options is necessary in various situations, and the collective rationality of groups has recently become a major topic of interest. Social insects are thought to make such optimal choices by collecting individuals' responses relating to an option's value (=a quality-graded response). However, this behaviour cannot explain the collective rationality of brains because neurons can make only ‘yes/no’ responses on the basis of the response threshold. Here, we elucidate the basic mechanism underlying the collective rationality of such simple units and show that an ant species uses this mechanism. A larger number of units respond ‘yes’ to the best option available to a collective decision-maker using only the yes/no mechanism; thus, the best option is always selected by majority decision. Colonies of the ant Myrmica kotokui preferred the better option in a binary choice experiment. The preference of a colony was demonstrated by the workers, which exhibited variable thresholds between two options' qualities. Our results demonstrate how a collective decision-maker comprising simple yes/no judgement units achieves collective rationality without using quality-graded responses. This mechanism has broad applicability to collective decision-making in brain neurons, swarm robotics and human societies. PMID:28484636

Fermat's principle of least time predicts refraction of ant trails at substrate borders.

PubMed

Oettler, Jan; Schmid, Volker S; Zankl, Niko; Rey, Olivier; Dress, Andreas; Heinze, Jürgen

2013-01-01

Fermat's principle of least time states that light rays passing through different media follow the fastest (and not the most direct) path between two points, leading to refraction at medium borders. Humans intuitively employ this rule, e.g., when a lifeguard has to infer the fastest way to traverse both beach and water to reach a swimmer in need. Here, we tested whether foraging ants also follow Fermat's principle when forced to travel on two surfaces that differentially affected the ants' walking speed. Workers of the little fire ant, Wasmannia auropunctata, established "refracted" pheromone trails to a food source. These trails deviated from the most direct path, but were not different to paths predicted by Fermat's principle. Our results demonstrate a new aspect of decentralized optimization and underline the versatility of the simple yet robust rules governing the self-organization of group-living animals.

Thought waves remotely affect the performance (output voltage) of photoelectric cells

NASA Astrophysics Data System (ADS)

Cao, Dayong; Cao, Daqing

2012-02-01

In our experiments, thought waves have been shown to be capable of changing (affecting) the output voltage of photovoltaic cells located from as far away as 1-3 meters. There are no wires between brain and photoelectric cell and so it is presumed only the thought waves act on the photoelectric cell. In continual rotations, the experiments tested different solar cells, measuring devices and lamps, and the experiments were done in different labs. The first experiment was conducted on Oct 2002. Tests are ongoing. Conclusions and assumptions include: 1) the slow thought wave has the energy of space-time as defined by C1.00007: The mass, energy, space and time systemic theory- MEST. Every process releases a field effect electrical vibration which be transmitted and focussed in particular paths; 2) the thought wave has the information of the order of tester; 3) the brain (with the physical system of MEST) and consciousness (with the spirit system of the mind, consciousness, emotion and desire-MECD) can produce the information (a part of them as the Genetic code); 4) through some algorithms such as ACO Ant Colony Optimization and EA Evolutionary Algorithm (or genetic algorithm) working in RAM, human can optimize the information. This Optimizational function is the intelligence; 5) In our experiments, not only can thought waves affect the voltage of the output photoelectric signals by its energy, but they can also selectively increase or decrease those photoelectric currents through remote consciousness interface and a conscious-brain information technology.

Assessment of gene order computing methods for Alzheimer's disease

PubMed Central

2013-01-01

Background Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Further, their performance in gene order computation using AD microarray data is not known. We thus set forth to evaluate the performances of current gene order computing methods with different distance formulas, and to identify additional features associated with gene order computation. Methods Using different distance formulas- Pearson distance and Euclidean distance, the squared Euclidean distance, and other conditions, gene orders were calculated by ACO and GA (including standard GA and improved GA) methods, respectively. The qualities of the gene orders were compared, and new features from the calculated gene orders were identified. Results Compared to the GA methods tested in this study, ACO fits the AD microarray data the best when calculating gene order. In addition, the following features were revealed: different distance formulas generated a different quality of gene order, and the commonly used Pearson distance was not the best distance formula when used with both GA and ACO methods for AD microarray data. Conclusion Compared with Pearson distance and Euclidean distance, the squared Euclidean distance generated the best quality gene order computed by GA and ACO methods. PMID:23369541

A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China

PubMed Central

Li, Xiaomeng; Yang, Zhuo

2017-01-01

As a sustainable transportation mode, high-speed railway (HSR) has become an efficient way to meet the huge travel demand. However, due to the high acquisition and maintenance cost, it is impossible to build enough infrastructure and purchase enough train-sets. Great efforts are required to improve the transport capability of HSR. The utilization efficiency of train-sets (carrying tools of HSR) is one of the most important factors of the transport capacity of HSR. In order to enhance the utilization efficiency of the train-sets, this paper proposed a train-set circulation optimization model to minimize the total connection time. An innovative two-stage approach which contains segments generation and segments combination was designed to solve this model. In order to verify the feasibility of the proposed approach, an experiment was carried out in the Beijing-Tianjin passenger dedicated line, to fulfill a 174 trips train diagram. The model results showed that compared with the traditional Ant Colony Algorithm (ACA), the utilization efficiency of train-sets can be increased from 43.4% (ACA) to 46.9% (Two-Stage), and 1 train-set can be saved up to fulfill the same transportation tasks. The approach proposed in the study is faster and more stable than the traditional ones, by using which, the HSR staff can draw up the train-sets circulation plan more quickly and the utilization efficiency of the HSR system is also improved. PMID:28489933

Response threshold variance as a basis of collective rationality.

PubMed

Yamamoto, Tatsuhiro; Hasegawa, Eisuke

2017-04-01

Determining the optimal choice among multiple options is necessary in various situations, and the collective rationality of groups has recently become a major topic of interest. Social insects are thought to make such optimal choices by collecting individuals' responses relating to an option's value (=a quality-graded response). However, this behaviour cannot explain the collective rationality of brains because neurons can make only 'yes/no' responses on the basis of the response threshold. Here, we elucidate the basic mechanism underlying the collective rationality of such simple units and show that an ant species uses this mechanism. A larger number of units respond 'yes' to the best option available to a collective decision-maker using only the yes/no mechanism; thus, the best option is always selected by majority decision. Colonies of the ant Myrmica kotokui preferred the better option in a binary choice experiment. The preference of a colony was demonstrated by the workers, which exhibited variable thresholds between two options' qualities. Our results demonstrate how a collective decision-maker comprising simple yes/no judgement units achieves collective rationality without using quality-graded responses. This mechanism has broad applicability to collective decision-making in brain neurons, swarm robotics and human societies.

Deleterious Wolbachia in the ant Formica truncorum.

PubMed

Wenseleers, T; Sundström, L; Billen, J

2002-03-22

Wolbachia is a maternally inherited bacterium that may manipulate the reproduction of its arthropod hosts. In insects, it is known to lead to inviable matings, cause asexual reproduction or kill male offspring, all to its own benefit, but to the detriment of its host. In social Hymenoptera, Wolbachia occurs widely, but little is known about its fitness effects. We report on a Wolbachia infection in the wood ant Formica truncorum, and evaluate whether it influences reproductive patterns. All 33 colonies of the study population were infected, suggesting that Wolbachia infection is at, or close to, fixation. Interestingly, in colonies with fewer infected workers, significantly more sexuals are produced, indicating that Wolbachia has deleterious effects in this species. In addition, adult workers are shown to have significantly lower infection rates (45%) than worker pupae (87%) or virgin queens (94%), suggesting that workers lose their infection over life. Clearance of Wolbachia infection has, to our knowledge, never been shown in any other natural system, but we argue that it may, in this case, represent an adaptive strategy to reduce colony load. The cause of fixation requires further study, but our data strongly suggest that Wolbachia has no influence on the sex ratio in this species.

Self-organized structures in a superorganism: do ants “behave” like molecules?

NASA Astrophysics Data System (ADS)

Detrain, Claire; Deneubourg, Jean-Louis

2006-09-01

While the striking structures (e.g. nest architecture, trail networks) of insect societies may seem familiar to many of us, the understanding of pattern formation still constitutes a challenging problem. Over the last two decades, self-organization has dramatically changed our view on how collective decision-making and structures may emerge out of a population of ant workers having each their own individuality as well as a limited access to information. A variety of collective behaviour spontaneously outcome from multiple interactions between nestmates, even when there is no directing influence imposed by an external template, a pacemaker or a leader. By focussing this review on foraging structures, we show that ant societies display some properties which are usually considered in physico-chemical systems, as typical signatures of self-organization. We detail the key role played by feed-back loops, fluctuations, number of interacting units and sensitivity to environmental factors in the emergence of a structured collective behaviour. Nonetheless, going beyond simple analogies with non-living self-organized patterns, we stress on the specificities of social structures made of complex living units of which the biological features have been selected throughout the evolution depending on their adaptive value. In particular, we consider the ability of each ant individual to process information about environmental and social parameters, to accordingly tune its interactions with nestmates and ultimately to determine the final pattern emerging at the collective level. We emphasize on the parsimony and simplicity of behavioural rules at the individual level which allow an efficient processing of information, energy and matter within the whole colony.

Fitness costs of worker specialization for ant societies

PubMed Central

Jongepier, Evelien; Foitzik, Susanne

2016-01-01

Division of labour is of fundamental importance for the success of societies, yet little is known about how individual specialization affects the fitness of the group as a whole. While specialized workers may be more efficient in the tasks they perform than generalists, they may also lack the flexibility to respond to rapid shifts in task needs. Such rigidity could impose fitness costs when societies face dynamic and unpredictable events, such as an attack by socially parasitic slavemakers. Here, we experimentally assess the colony-level fitness consequences of behavioural specialization in Temnothorax longispinosus ants that are attacked by the slavemaker ant T. americanus. We manipulated the social organization of 102 T. longispinosus colonies, based on the behavioural responses of all 3842 workers. We find that strict specialization is disadvantageous for a colony's annual reproduction and growth during slave raids. These fitness costs may favour generalist strategies in dynamic environments, as we also demonstrate that societies exposed to slavemakers in the field show a lower degree of specialization than those originating from slavemaker-free populations. Our findings provide an explanation for the ubiquity of generalists and highlight their importance for the flexibility and functional robustness of entire societies. PMID:26763706

Neuromodulation of Nestmate Recognition Decisions by Pavement Ants.

PubMed

Bubak, Andrew N; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

2016-01-01

Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context-isolation, nestmate interaction, or fighting non-nestmates-affects brain monoamine levels in pavement ants (Tetramorium caespitum). Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants.

Discrete bacteria foraging optimization algorithm for graph based problems - a transition from continuous to discrete

NASA Astrophysics Data System (ADS)

Sur, Chiranjib; Shukla, Anupam

2018-03-01

Bacteria Foraging Optimisation Algorithm is a collective behaviour-based meta-heuristics searching depending on the social influence of the bacteria co-agents in the search space of the problem. The algorithm faces tremendous hindrance in terms of its application for discrete problems and graph-based problems due to biased mathematical modelling and dynamic structure of the algorithm. This had been the key factor to revive and introduce the discrete form called Discrete Bacteria Foraging Optimisation (DBFO) Algorithm for discrete problems which exceeds the number of continuous domain problems represented by mathematical and numerical equations in real life. In this work, we have mainly simulated a graph-based road multi-objective optimisation problem and have discussed the prospect of its utilisation in other similar optimisation problems and graph-based problems. The various solution representations that can be handled by this DBFO has also been discussed. The implications and dynamics of the various parameters used in the DBFO are illustrated from the point view of the problems and has been a combination of both exploration and exploitation. The result of DBFO has been compared with Ant Colony Optimisation and Intelligent Water Drops Algorithms. Important features of DBFO are that the bacteria agents do not depend on the local heuristic information but estimates new exploration schemes depending upon the previous experience and covered path analysis. This makes the algorithm better in combination generation for graph-based problems and combination generation for NP hard problems.

Foraging swarms as Nash equilibria of dynamic games.

PubMed

Özgüler, Arif Bülent; Yildiz, Aykut

2014-06-01

The question of whether foraging swarms can form as a result of a noncooperative game played by individuals is shown here to have an affirmative answer. A dynamic game played by N agents in 1-D motion is introduced and models, for instance, a foraging ant colony. Each agent controls its velocity to minimize its total work done in a finite time interval. The game is shown to have a unique Nash equilibrium under two different foraging location specifications, and both equilibria display many features of a foraging swarm behavior observed in biological swarms. Explicit expressions are derived for pairwise distances between individuals of the swarm, swarm size, and swarm center location during foraging.

Neuromodulation of Nestmate Recognition Decisions by Pavement Ants

PubMed Central

Bubak, Andrew N.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.

2016-01-01

Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context—isolation, nestmate interaction, or fighting non-nestmates—affects brain monoamine levels in pavement ants (Tetramorium caespitum). Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants. PMID:27846261

Stochastic recruitment leads to symmetry breaking in foraging populations

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; Dyson, Louise; McKane, Alan

2014-03-01

When an ant colony is faced with two identical equidistant food sources, the foraging ants are found to concentrate more on one source than the other. Analogous symmetry-breaking behaviours have been reported in various population systems, (such as queueing or stock market trading) suggesting the existence of a simple universal mechanism. Past studies have neglected the effect of demographic noise and required rather complicated models to qualitatively reproduce this behaviour. I will show how including the effects of demographic noise leads to a radically different conclusion. The symmetry-breaking arises solely due to the process of recruitment and ceases to occur for large population sizes. The latter fact provides a testable prediction for a real system.

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

NASA Astrophysics Data System (ADS)

Oesterle, Jonathan; Lionel, Amodeo

2018-06-01

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization.

PubMed

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-01-01

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valles, S.M.; Porter, S.D.

Solenopsis invicta virus (SINV-1) is a positive-stranded RNA virus recently found to infect all stages of the red imported fire ant, Solenopsis invicta (Valles et al. 2004; Valles and Strong 2005). SINV-1 and a second genotype have been tentatively assigned to the Dicistroviridae (Mayo 2002). Infected individuals or colonies did not exhibit any immediate, discernible symptoms in the field. However, under stress from introduction into the laboratory, brood death was often observed among infected colonies, ultimately leading to the death of the entire colony (Valles et al. 2004). These characteristics are consistent with other insect-infecting positive-stranded RNA viruses. They oftenmore » persist as inapparent, asymptomatic infections that, under certain conditions, induce replication within the host, resulting in observable symptoms and often death (Christian and Scotti 1998; Fernandez et al. 2002). The SINV infection rate among colonies was reported to be around 25% in Gainesville, Florida (Valles et al. 2004; Valles and Strong 2005). SINV vertical and horizontal transmission were inferred based on RT-PCR detection of virus genome in eggs and successful colony to colony transfer under lab conditions (Valles et al. 2004). However, the exact mechanisms by which the virus is spread from nest to nest in the field are unknown. Our results indicate that SINV does not replicate within Pseudacteon decapitating flies that parasitize S. invicta. Flies appeared to develop normally from SINV-infected S. invicta workers. Mechanical transmission of SINV to uninfected ants by oviposition appears unlikely.« less

Cross-layer design for intrusion detection and data security in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2007-09-01

A wireless ad hoc sensor network is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. The nodes are severely resource-constrained, with limited processing, memory and power capacities and must operate cooperatively to fulfill a common mission in typically unattended modes. In a wireless sensor network (WSN), each sensor at a node can observe locally some underlying physical phenomenon and sends a quantized version of the observation to sink (destination) nodes via wireless links. Since the wireless medium can be easily eavesdropped, links can be compromised by intrusion attacks from nodes that may mount denial-of-service attacks or insert spurious information into routing packets, leading to routing loops, long timeouts, impersonation, and node exhaustion. A cross-layer design based on protocol-layer interactions is proposed for detection and identification of various intrusion attacks on WSN operation. A feature set is formed from selected cross-layer parameters of the WSN protocol to detect and identify security threats due to intrusion attacks. A separate protocol is not constructed from the cross-layer design; instead, security attributes and quantified trust levels at and among nodes established during data exchanges complement customary WSN metrics of energy usage, reliability, route availability, and end-to-end quality-of-service (QoS) provisioning. Statistical pattern recognition algorithms are applied that use observed feature-set patterns observed during network operations, viewed as security audit logs. These algorithms provide the "best" network global performance in the presence of various intrusion attacks. A set of mobile (software) agents distributed at the nodes implement the algorithms, by moving among the layers involved in the network response at each active node and trust neighborhood, collecting parametric information and executing assigned decision tasks. The communications overhead due to security mechanisms and the latency in network response are thus minimized by reducing the need to move large amounts of audit data through resource-limited nodes and by locating detection/identification programs closer to audit data. If network partitioning occurs due to uncoordinated node exhaustion, data compromise or other effects of the attacks, the mobile agents can continue to operate, thereby increasing fault tolerance in the network response to intrusions. Since the mobile agents behave like an ant colony in securing the WSN, published ant colony optimization (ACO) routines and other evolutionary algorithms are adapted to protect network security, using data at and through nodes to create audit records to detect and respond to denial-of-service attacks. Performance evaluations of algorithms are performed by simulation of a few intrusion attacks, such as black hole, flooding, Sybil and others, to validate the ability of the cross-layer algorithms to enable WSNs to survive the attacks. Results are compared for the different algorithms.

How can AN Approach to Steam BE Authentic to both Science and Art?

NASA Astrophysics Data System (ADS)

LaFayette, C. J.; Parke, Ph D., F. I.; Pierce, C.; Nakamura, T.

2015-12-01

A collaborative project engaged a team of geophysicists, engineers, entomologists, and artists to visualize tunnels and chambers of a vast, leafcutting ant colony in rural Texas. Part of the plan was to test the nature of significant outcomes in different domains and contexts. Our team used Ground Penetrating Radar to scan part of the nest, then translate the data into 3D geometry to be experienced on an immersive visualization system. This provided the ability to zoom out of and into the model. The tunnel fragment could appear like a tiny crumb floating in air, or one could move inside it to view details and tunnel architecture. Exterior and interior structure could thus be perceived in a seamless way. The system enabled a kinesthetic sense — one both saw and felt surrounded by the scene. This was the first time GPR had been used to map a living ant colony. Due to this project, entomologists have begun to use GPR with encouraging results. The Atta project inspired in us an enjoyment of experimentation and collaboration. Results were exhibited in international art venues, published in scientific journals, and demonstrated at hybrid venues for art and science. Each form of dissemination was suited to the host. Whether the result can be called art, science, or a blend is determined by its reception in a larger community. Like the species name and the pathway worn from tree to nest, the process of mapping the colony took the form of a palindrome: we pulled something out of the ground, passed it back and forth, and hoisted it out into the world. The role of art in collaboration with science can take many forms. Art can enhance science understanding for non-scientists. Artists and scientists can co-invent new tools for inquiry. Artists are adept at creating ways to experience and understand data or phenomena through multi-modal experiences, for example, aural, haptic, or olfactory. Artists are trained to foreground the process of making as part of the "performance"—"how" one approaches the question is as important as "what tools" one chooses. The end result is always mediated by those choices. The outcome of a work depends on "ways of knowing" inherent in any larger context. Creativity and innovation are not goals in themselves, but means to enable thriving and healthy communities and a sustainable planetary civilization.

AN UNUSUAL PATTERN OF GENE FLOW BETWEEN THE TWO SOCIAL FORMS OF THE FIRE ANT SOLENOPSIS INVICTA.

PubMed

Ross, Kenneth G; Shoemaker, D DeWayne

1993-10-01

Uncertainty over the role of shifts in social behavior in the process of speciation in social insects has stimulated interest in determining the extent of gene flow between conspecific populations differing in colony social organization. Allele and genotype frequencies at 12 neutral polymorphic protein markers, as well as the numbers of alleles at the sex-determining locus (loci), are shown here to be consistent with significant ongoing gene flow between two geographically adjacent populations of Solenopsis invicta that differ in colony queen number. Data from a thirteenth protein marker that is under strong differential selection in the two social forms confirm that such gene flow occurs. Data from this selected locus, combined with knowledge of the reproductive biology of the two social forms, further suggest that interform gene flow is largely unidirectional and mediated through males only. This unusual pattern of gene flow results from the influence of the unique social enviroments of the two forms on the behavior of workers and on the reproductive physiology of sexuals. © 1993 The Society for the Study of Evolution.

Feeding and stocking up: radio-labelled food reveals exchange patterns in ants.

PubMed

Buffin, Aurélie; Denis, Damien; Van Simaeys, Gaetan; Goldman, Serge; Deneubourg, Jean-Louis

2009-06-17

Food sharing is vital for a large number of species, either solitary or social, and is of particular importance within highly integrated societies, such as in colonial organisms and in social insects. Nevertheless, the mechanisms that govern the distribution of food inside a complex organizational system remain unknown. Using scintigraphy, a method developed for medical imaging, we were able to describe the dynamics of food-flow inside an ant colony. We monitored the sharing process of a radio-labelled sucrose solution inside a nest of Formica fusca. Our results show that, from the very first load that enters the nest, food present within the colony acts as negative feedback to entering food. After one hour of the experiments, 70% of the final harvest has already entered the nest. The total foraged quantity is almost four times smaller than the expected storage capacity. A finer study of the spatial distribution of food shows that although all ants have been fed rapidly (within 30 minutes), a small area representing on average 8% of the radioactive surface holds more than 25% of the stored food. Even in rather homogeneous nests, we observed a strong concentration of food in few workers. Examining the position of these workers inside the nest, we found heavily loaded ants in the centre of the aggregate. The position of the centre of this high-intensity radioactive surface remained stable for the three consecutive hours of the experiments. We demonstrate that the colony simultaneously managed to rapidly feed all workers (200 ants fed within 30 minutes) and build up food stocks to prevent food shortage, something that occurs rather often in changing environments. Though we expected the colony to forage to its maximum capacity, the flow of food entering the colony is finely tuned to the colony's needs. Indeed the food-flow decreases proportionally to the food that has already been harvested, liberating the work-force for other tasks.

New Enhanced Artificial Bee Colony (JA-ABC5) Algorithm with Application for Reactive Power Optimization

PubMed Central

2015-01-01

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement. PMID:25879054

Chemical disguise of myrmecophilous cockroaches and its implications for understanding nestmate recognition mechanisms in leaf-cutting ants.

PubMed

Nehring, Volker; Dani, Francesca R; Calamai, Luca; Turillazzi, Stefano; Bohn, Horst; Klass, Klaus-Dieter; d'Ettorre, Patrizia

2016-08-05

Cockroaches of the genus Attaphila regularly occur in leaf-cutting ant colonies. The ants farm a fungus that the cockroaches also appear to feed on. Cockroaches disperse between colonies horizontally (via foraging trails) and vertically (attached to queens on their mating flights). We analysed the chemical strategies used by the cockroaches to integrate into colonies of Atta colombica and Acromyrmex octospinosus. Analysing cockroaches from nests of two host species further allowed us to test the hypothesis that nestmate recognition is based on an asymmetric mechanism. Specifically, we test the U-present nestmate recognition model, which assumes that detection of undesirable cues (non-nestmate specific substances) leads to strong rejection of the cue-bearers, while absence of desirable cues (nestmate-specific substances) does not necessarily trigger aggression. We found that nests of Atta and Acromyrmex contained cockroaches of two different and not yet described Attaphila species. The cockroaches share the cuticular chemical substances of their specific host species and copy their host nest's colony-specific cuticular profile. Indeed, the cockroaches are accepted by nestmate but attacked by non-nestmate ant workers. Cockroaches from Acromyrmex colonies bear a lower concentration of cuticular substances and are less likely to be attacked by non-nestmate ants than cockroaches from Atta colonies. Nest-specific recognition of Attaphila cockroaches by host workers in combination with nest-specific cuticular chemical profiles suggest that the cockroaches mimic their host's recognition labels, either by synthesizing nest-specific substances or by substance transfer from ants. Our finding that the cockroach species with lower concentration of cuticular substances receives less aggression by both host species fully supports the U-present nestmate recognition model. Leaf-cutting ant nestmate recognition is thus asymmetric, responding more strongly to differences than to similarities.

Life Span Evolution in Eusocial Workers—A Theoretical Approach to Understanding the Effects of Extrinsic Mortality in a Hierarchical System

PubMed Central

Kramer, Boris H.; Schaible, Ralf

2013-01-01

While the extraordinary life span of queens and division of labor in eusocial societies have been well studied, it is less clear which selective forces act on the short life span of workers. The disparity of life span between the queen and the workers is linked to a basic issue in sociobiology: How are the resources in a colony allocated between colony maintenance and reproduction? Resources for somatic maintenance of the colony can either be invested into quality or quantity of workers. Here, we present a theoretical optimization model that uses a hierarchical trade-off within insect colonies and extrinsic mortality to explain how different aging phenotypes could have evolved to keep resources secure in the colony. The model points to the significance of two factors. First, any investment that would generate a longer intrinsic life span for workers is lost if the individual dies from external causes while foraging. As a consequence, risky environments favor the evolution of workers with a shorter life span. Second, shorter-lived workers require less investment than long-lived ones, allowing the colony to allocate these resources to sexual reproduction or colony growth. PMID:23596527

The coevolutionary dynamics of obligate ant social parasite systems--between prudence and antagonism.

PubMed

Brandt, Miriam; Foitzik, Susanne; Fischer-Blass, Birgit; Heinze, Jürgen

2005-05-01

In this synthesis we apply coevolutionary models to the interactions between socially parasitic ants and their hosts. Obligate social parasite systems are ideal models for coevolution, because the close phylogenetic relationship between these parasites and their hosts results in similar evolutionary potentials, thus making mutual adaptations in a stepwise fashion especially likely to occur. The evolutionary dynamics of host-parasite interactions are influenced by a number of parameters, for example the parasite's transmission mode and rate, the genetic structure of host and parasite populations, the antagonists' migration rates, and the degree of mutual specialisation. For the three types of obligate ant social parasites, queen-tolerant and queen-intolerant inquilines and slavemakers, several of these parameters, and thus the evolutionary trajectory, are likely to differ. Because of the fundamental differences in lifestyle between these social parasite systems, coevolution should further select for different traits in the parasites and their hosts. Queen-tolerant inquilines are true parasites that exert a low selection pressure on their host, because of their rarity and the fact that they do not conduct slave raids to replenish their labour force. Due to their high degree of specialisation and the potential for vertical transmission, coevolutionary theory would predict interactions between these workerless parasites and their hosts to become even more benign over time. Queen-intolerant inquilines that kill the host queen during colony take-over are best described as parasitoids, and their reproductive success is limited by the existing worker force of the invaded host nest. These parasites should therefore evolve strategies to best exploit this fixed resource. Slavemaking ants, by contrast, act as parasites only during colony foundation, while their frequent slave raids follow a predator prey dynamic. They often exploit a number of host species at a given site, and theory predicts that their associations are best described in terms of a highly antagonistic coevolutionary arms race.

Oviposition, Life Cycle, and Longevity of the Leaf-Cutting Ant Acromyrmex rugosus rugosus.

PubMed

Verza, Sandra S; Mussury, Rosilda M; Camargo, Roberto S; Andrade, Ana Paula P; Forti, Luiz C

2017-08-04

Studies related to the demography of individual members from ant colonies have received little attention, although they are the basis to understanding the population dynamics of colonies. Thus, the objective of this work was to study the queen oviposition rate and the duration of the life cycle and longevity of Acromyrmex rugosus rugosus workers. To determine the oviposition rate, queens from three colonies were individually placed in plastic containers, and the eggs laid were quantified over a 96 h period. The development of the immature forms was observed every 24 h, with which the duration of each stage of development was determined. To verify the longevity of workers, the newly emerged adults were marked and daily observations were made. According to the results, there is variation in the development time of immature forms within the colony itself and between colonies. In addition, the number of eggs deposited was also inconstant in the three colonies, ranging from 5 to 119 eggs per day, while the longevity of workers varied from 3 to 7 months. Occasionally, it was found that the workers feed on the eggs produced by the queen; besides, there was a disappearance of larvae and pupae during the research, indicating a possibility of the practice of cannibalism in this species.

Compound eye and ocellar structure for walking and flying modes of locomotion in the Australian ant, Camponotus consobrinus

PubMed Central

Narendra, Ajay; Ramirez-Esquivel, Fiorella; Ribi, Willi A.

2016-01-01

Ants are unusual among insects in that individuals of the same species within a single colony have different modes of locomotion and tasks. We know from walking ants that vision plays a significant role in guiding this behaviour, but we know surprisingly little about the potential contribution of visual sensory structures for a flying mode of locomotion. Here we investigate the structure of the compound eye and ocelli in pedestrian workers, alate females and alate males of an Australian ant, Camponotus consobrinus, and discuss the trade-offs involved in optical sensitivity and spatial resolution. Male ants have more but smaller ommatidia and the smallest interommatidial angles, which is most likely an adaptation to visually track individual flying females. Both walking and flying forms of ants have a similar proportion of specialized receptors sensitive to polarized skylight, but the absolute number of these receptors varies, being greatest in males. Ocelli are present only in the flying forms. Each ocellus consists of a bipartite retina with a horizon-facing dorsal retina, which contains retinula cells with long rhabdoms, and a sky-facing ventral retina with shorter rhabdoms. We discuss the implications of these and their potential for sensing the pattern of polarized skylight. PMID:26975481

Sperm mixing in the polyandrous leaf-cutting ant Acromyrmex echinatior

PubMed Central

Stürup, Marlene; Nash, David R; Hughes, William O H; Boomsma, Jacobus J

2014-01-01

The insemination of queens by sperm from multiple males (polyandry) has evolved in a number of eusocial insect lineages despite the likely costs of the behavior. The selective advantages in terms of colony fitness must therefore also be significant and there is now good evidence that polyandry increases genetic variation among workers, thereby improving the efficiency of division of labor, resistance against disease, and diluting the impact of genetically incompatible matings. However, these advantages will only be maximized if the sperm of initially discrete ejaculates are mixed when stored in queen spermathecae and used for egg fertilization in a “fair raffle.” Remarkably, however, very few studies have addressed the level of sperm mixing in social insects. Here we analyzed sperm use over time in the highly polyandrous leaf-cutting ant Acromyrmex echinatior. We genotyped cohorts of workers produced either 2 months apart or up to over a year apart, and batches of eggs laid up to over 2 years apart, and tested whether fluctuations in patriline distributions deviated from random. We show that the representation of father males in both egg and worker cohorts does not change over time, consistent with obligatorily polyandrous queens maximizing their fitness when workers are as genetically diverse as possible. PMID:25478149

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Alkaloid venom weaponry of three Megalomyrmex thief ants and the behavioral response of Cyphomyrmex costatus host ants.

PubMed

Adams, Rachelle M M; Jones, Tappey H; Longino, John T; Weatherford, Robert G; Mueller, Ulrich G

2015-04-01

Social parasites exploit other societies by invading and stealing resources. Some enter protected nests using offensive chemical weaponry made from alkaloid-based venom. We characterized the venoms of three Megalomyrmex thief ant species (M. mondabora, M. mondaboroides, and M. silvestrii) that parasitize the fungus-growing ants, and developed an ethogram to describe host ant reactions to raiding M. mondaboroides and M. silvestrii parasites. We compared piperidine, pyrrolidine, and pyrolizidine venom alkaloid structures with synthetic samples from previous studies, and describe the novel stereochemistry of trans 2-hexyl-5-[8-oxononyl]-pyrrolidine (3) from M. mondabora. We showed that workers of Cyphomyrmex costatus, the host of M. mondaboroides and M. silvestrii, react to a sting by Megalomyrmex parasites mainly with submissive behavior, playing dead or retreating. Host submission also followed brief antennal contact. The behavior of C. costatus ants observed in this study was similar to that of Cyphomyrmex cornutus, host of M. mondabora, suggesting that the alkaloidal venoms with pyrrolidines from M. mondabora, piperidines from M. mondaboroides, and pyrolizidines from M. silvestrii may function similarly as appeasement and repellent allomones against host ants, despite their different chemical structure. With the use of these chemical weapons, the Megalomyrmex thief ants are met with little host resistance and easily exploit host colony resources.