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Sample records for artificial ant colonies

  1. Laboratory Fire Ant colonies (Solenopsis invicta) fail to grow with Bhatkar Diet and three other artificial diets

    USDA-ARS?s Scientific Manuscript database

    Various artificial diets have been used for rearing imported fire ants; however most of these diets include insect supplements. This study was designed to examine growth of red imported fire ant colonies (Hymenoptera: Formicidae: Solenopsis invicta Buren) on four artificial diets: a chemically unde...

  2. Ant colony optimization: Introduction and recent trends

    NASA Astrophysics Data System (ADS)

    Blum, Christian

    2005-12-01

    Ant colony optimization is a technique for optimization that was introduced in the early 1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommunications, such as routing and load balancing. First, we deal with the biological inspiration of ant colony optimization algorithms. We show how this biological inspiration can be transfered into an algorithm for discrete optimization. Then, we outline ant colony optimization in more general terms in the context of discrete optimization, and present some of the nowadays best-performing ant colony optimization variants. After summarizing some important theoretical results, we demonstrate how ant colony optimization can be applied to continuous optimization problems. Finally, we provide examples of an interesting recent research direction: The hybridization with more classical techniques from artificial intelligence and operations research.

  3. Measuring activity in ant colonies

    NASA Astrophysics Data System (ADS)

    Noda, C.; Fernández, J.; Pérez-Penichet, C.; Altshuler, E.

    2006-12-01

    Ants, as paradigm of social insects, have become a recurrent example of efficient problem solvers via self-organization. In spite of the simple behavior of each individual, the colony as a whole displays "swarm intelligence:" the organization of ant trails for foraging is a typical output of it. But conventional techniques of observation can hardly record the amount of data needed to get a detailed understanding of self-organization of ant swarms in the wild. Here we are presenting a measurement system intended to monitor ant activity in the field comprising massive data acquisition and high sensitivity. A central role is played by an infrared sensor devised specifically to monitor relevant parameters to the activity of ants through the exits of the nest, although other sensors detecting temperature and luminosity are added to the system. We study the characteristics of the activity sensor and its performance in the field. Finally, we present massive data measured at one exit of a nest of Atta insularis, an ant endemic to Cuba, to illustrate the potential of our system.

  4. Exploration adjustment by ant colonies

    PubMed Central

    2016-01-01

    How do animals in groups organize their work? Division of labour, i.e. the process by which individuals within a group choose which tasks to perform, has been extensively studied in social insects. Variability among individuals within a colony seems to underpin both the decision over which tasks to perform and the amount of effort to invest in a task. Studies have focused mainly on discrete tasks, i.e. tasks with a recognizable end. Here, we study the distribution of effort in nest seeking, in the absence of new nest sites. Hence, this task is open-ended and individuals have to decide when to stop searching, even though the task has not been completed. We show that collective search effort declines when colonies inhabit better homes, as a consequence of a reduction in the number of bouts (exploratory events). Furthermore, we show an increase in bout exploration time and a decrease in bout instantaneous speed for colonies inhabiting better homes. The effect of treatment on bout effort is very small; however, we suggest that the organization of work performed within nest searching is achieved both by a process of self-selection of the most hard-working ants and individual effort adjustment. PMID:26909180

  5. Exploration versus exploitation in polydomous ant colonies.

    PubMed

    Cook, Zoe; Franks, Daniel W; Robinson, Elva J H

    2013-04-21

    In socially foraging species resource information can be shared between individuals, increasing foraging success. In ant colonies, nestmate recruitment allows high exploitation rates at known resources however, to maximise foraging efficiency this must be balanced with searching for new resources. Many ant species form colonies inhabiting two or more spatially separated but socially connected nests: this type of organisation is known as polydomy. Polydomous colonies may benefit from increased foraging efficiency by carrying out dispersed-central place foraging. However, decentralisation of the colony may affect recruitment success by limiting interaction between ants based in separate nests. We use an agent-based model which compares the foraging success of monodomous and polydomous colonies in different food environments, incorporating recruitment through pheromone trails and group foraging. In contrast to previous results we show that polydomy is beneficial in some but not all cases. Polydomous colonies discover resources at a higher rate, making them more successful when food is highly dispersed, but their relative success can be lowered by limitations on recruitment success. Monodomous colonies can have higher foraging efficiency than polydomous colonies by exploiting food more rapidly. The results show the importance of interactions between recruitment strategy, colony size, and colony organisation. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Ant Colony Optimization Algorithm for Continuous Domains Based on Position Distribution Model of Ant Colony Foraging

    PubMed Central

    Liu, Liqiang; Dai, Yuntao

    2014-01-01

    Ant colony optimization algorithm for continuous domains is a major research direction for ant colony optimization algorithm. In this paper, we propose a distribution model of ant colony foraging, through analysis of the relationship between the position distribution and food source in the process of ant colony foraging. We design a continuous domain optimization algorithm based on the model and give the form of solution for the algorithm, the distribution model of pheromone, the update rules of ant colony position, and the processing method of constraint condition. Algorithm performance against a set of test trials was unconstrained optimization test functions and a set of optimization test functions, and test results of other algorithms are compared and analyzed to verify the correctness and effectiveness of the proposed algorithm. PMID:24955402

  7. Ant colony optimization algorithm for continuous domains based on position distribution model of ant colony foraging.

    PubMed

    Liu, Liqiang; Dai, Yuntao; Gao, Jinyu

    2014-01-01

    Ant colony optimization algorithm for continuous domains is a major research direction for ant colony optimization algorithm. In this paper, we propose a distribution model of ant colony foraging, through analysis of the relationship between the position distribution and food source in the process of ant colony foraging. We design a continuous domain optimization algorithm based on the model and give the form of solution for the algorithm, the distribution model of pheromone, the update rules of ant colony position, and the processing method of constraint condition. Algorithm performance against a set of test trials was unconstrained optimization test functions and a set of optimization test functions, and test results of other algorithms are compared and analyzed to verify the correctness and effectiveness of the proposed algorithm.

  8. Ant Colony Optimization with Cunning Ants

    NASA Astrophysics Data System (ADS)

    Tsutsui, Shigeyoshi

    In this paper, we propose the cAS, a new ACO algorithm, and evaluate the performance using TSP instances available at TSPLIB. The results show that cAS works well on the test instances and has performance that may be one of the most promising ACO algorithms. We also evaluate cAS when it is combined with LK local search heuristic using larger sized TSP instances. The results also show promising performance. cAS introduced two important schemes. One is to use the colony model divided into units, which has a stronger exploitation feature while maintaining a certain degree of diversity among units. The other is to use a scheme, we call cunning, when constructing new solutions, which can prevent premature stagnation by reducing strong positive feedback to the trail density.

  9. Polydomy enhances foraging performance in ant colonies.

    PubMed

    Stroeymeyt, N; Joye, P; Keller, L

    2017-04-26

    Collective foraging confers benefits in terms of reduced predation risk and access to social information, but it heightens local competition when resources are limited. In social insects, resource limitation has been suggested as a possible cause for the typical decrease in per capita productivity observed with increasing colony size, a phenomenon known as Michener's paradox. Polydomy (distribution of a colony's brood and workers across multiple nests) is believed to help circumvent this paradox through its positive effect on foraging efficiency, but there is still little supporting evidence for this hypothesis. Here, we show experimentally that polydomy enhances the foraging performance of food-deprived Temnothorax nylanderi ant colonies via several mechanisms. First, polydomy influences task allocation within colonies, resulting in faster retrieval of protein resources. Second, communication between sister nests reduces search times for far away resources. Third, colonies move queens, brood and workers across available nest sites in response to spatial heterogeneities in protein and carbohydrate resources. This suggests that polydomy represents a flexible mechanism for space occupancy, helping ant colonies adjust to the environment. © 2017 The Author(s).

  10. Ants and ant scent reduce bumblebee pollination of artificial flowers.

    PubMed

    Cembrowski, Adam R; Tan, Marcus G; Thomson, James D; Frederickson, Megan E

    2014-01-01

    Ants on flowers can disrupt pollination by consuming rewards or harassing pollinators, but it is difficult to disentangle the effects of these exploitative and interference forms of competition on pollinator behavior. Using highly rewarding and quickly replenishing artificial flowers that simulate male or female function, we allowed bumblebees (Bombus impatiens) to forage (1) on flowers with or without ants (Myrmica rubra) and (2) on flowers with or without ant scent cues. Bumblebees transferred significantly more pollen analogue both to and from ant-free flowers, demonstrating that interference competition with ants is sufficient to modify pollinator foraging behavior. Bees also removed significantly less pollen analogue from ant-scented flowers than from controls, making this the first study to show that bees can use ant scent to avoid harassment at flowers. Ant effects on pollinator behavior, possibly in addition to their effects on pollen viability, may contribute to the evolution of floral traits minimizing ant visitation.

  11. Parallelizing Ant Colony Optimization via Area of Expertise Learning

    DTIC Science & Technology

    2007-09-13

    ACS-TSP, is well-established and commonly used throughout the academic community. ACS-GRIDWORLD, on the other hand, represents a brand -new ant colony...van der Zwaan, S. and C. Marques . “Ant Colony Optimisation for Job Shop Scheduling”, 1999. URL citeseer.ist.psu.edu/vanderzwaan99ant.html. 103

  12. Model Specification Searches Using Ant Colony Optimization Algorithms

    ERIC Educational Resources Information Center

    Marcoulides, George A.; Drezner, Zvi

    2003-01-01

    Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

  13. Model Specification Searches Using Ant Colony Optimization Algorithms

    ERIC Educational Resources Information Center

    Marcoulides, George A.; Drezner, Zvi

    2003-01-01

    Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

  14. 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.

  15. Image feature extraction based multiple ant colonies cooperation

    NASA Astrophysics Data System (ADS)

    Zhang, Zhilong; Yang, Weiping; Li, Jicheng

    2015-05-01

    This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.

  16. Enhanced ant colony optimization for multiscale problems

    NASA Astrophysics Data System (ADS)

    Hu, Nan; Fish, Jacob

    2016-03-01

    The present manuscript addresses the issue of computational complexity of optimizing nonlinear composite materials and structures at multiple scales. Several solutions are detailed to meet the enormous computational challenge of optimizing nonlinear structures at multiple scales including: (i) enhanced sampling procedure that provides superior performance of the well-known ant colony optimization algorithm, (ii) a mapping-based meshing of a representative volume element that unlike unstructured meshing permits sensitivity analysis on coarse meshes, and (iii) a multilevel optimization procedure that takes advantage of possible weak coupling of certain scales. We demonstrate the proposed optimization procedure on elastic and inelastic laminated plates involving three scales.

  17. Improved Ant Colony Clustering Algorithm and Its Performance Study.

    PubMed

    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.

  18. 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

  19. 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

  20. An ant colony algorithm on continuous searching space

    NASA Astrophysics Data System (ADS)

    Xie, Jing; Cai, Chao

    2015-12-01

    Ant colony algorithm is heuristic, bionic and parallel. Because of it is property of positive feedback, parallelism and simplicity to cooperate with other method, it is widely adopted in planning on discrete space. But it is still not good at planning on continuous space. After a basic introduction to the basic ant colony algorithm, we will propose an ant colony algorithm on continuous space. Our method makes use of the following three tricks. We search for the next nodes of the route according to fixed-step to guarantee the continuity of solution. When storing pheromone, it discretizes field of pheromone, clusters states and sums up the values of pheromone of these states. When updating pheromone, it makes good resolutions measured in relative score functions leave more pheromone, so that ant colony algorithm can find a sub-optimal solution in shorter time. The simulated experiment shows that our ant colony algorithm can find sub-optimal solution in relatively shorter time.

  1. The Regulation of Ant Colony Foraging Activity without Spatial Information

    PubMed Central

    Prabhakar, Balaji; Dektar, Katherine N.; Gordon, Deborah M.

    2012-01-01

    Many dynamical networks, such as the ones that produce the collective behavior of social insects, operate without any central control, instead arising from local interactions among individuals. A well-studied example is the formation of recruitment trails in ant colonies, but many ant species do not use pheromone trails. We present a model of the regulation of foraging by harvester ant (Pogonomyrmex barbatus) colonies. This species forages for scattered seeds that one ant can retrieve on its own, so there is no need for spatial information such as pheromone trails that lead ants to specific locations. Previous work shows that colony foraging activity, the rate at which ants go out to search individually for seeds, is regulated in response to current food availability throughout the colony's foraging area. Ants use the rate of brief antennal contacts inside the nest between foragers returning with food and outgoing foragers available to leave the nest on the next foraging trip. Here we present a feedback-based algorithm that captures the main features of data from field experiments in which the rate of returning foragers was manipulated. The algorithm draws on our finding that the distribution of intervals between successive ants returning to the nest is a Poisson process. We fitted the parameter that estimates the effect of each returning forager on the rate at which outgoing foragers leave the nest. We found that correlations between observed rates of returning foragers and simulated rates of outgoing foragers, using our model, were similar to those in the data. Our simple stochastic model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony. PMID:22927811

  2. The regulation of ant colony foraging activity without spatial information.

    PubMed

    Prabhakar, Balaji; Dektar, Katherine N; Gordon, Deborah M

    2012-01-01

    Many dynamical networks, such as the ones that produce the collective behavior of social insects, operate without any central control, instead arising from local interactions among individuals. A well-studied example is the formation of recruitment trails in ant colonies, but many ant species do not use pheromone trails. We present a model of the regulation of foraging by harvester ant (Pogonomyrmex barbatus) colonies. This species forages for scattered seeds that one ant can retrieve on its own, so there is no need for spatial information such as pheromone trails that lead ants to specific locations. Previous work shows that colony foraging activity, the rate at which ants go out to search individually for seeds, is regulated in response to current food availability throughout the colony's foraging area. Ants use the rate of brief antennal contacts inside the nest between foragers returning with food and outgoing foragers available to leave the nest on the next foraging trip. Here we present a feedback-based algorithm that captures the main features of data from field experiments in which the rate of returning foragers was manipulated. The algorithm draws on our finding that the distribution of intervals between successive ants returning to the nest is a Poisson process. We fitted the parameter that estimates the effect of each returning forager on the rate at which outgoing foragers leave the nest. We found that correlations between observed rates of returning foragers and simulated rates of outgoing foragers, using our model, were similar to those in the data. Our simple stochastic model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony.

  3. Remarks of Elliptic Curves Derived from Ant Colony Routing

    NASA Astrophysics Data System (ADS)

    Jung, Sangsu; Kim, Daeyeoul; Singh, Dhananjay

    2011-09-01

    We deal with an ant colony based routing model for wireless multi-hop networks. Our model adopts an elliptic curve equation, which is beneficial to design pheromone dynamics for load balancing and packet delivery robustness. Due to the attribute of an elliptic curve equation, our model prevents the over-utilization of a specific node, distinctively from conventional ant colony based schemes. Numerical simulations exhibit the characteristics of our model with respect to various parameters.

  4. 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.

  5. Protein structure optimization with a "Lamarckian" ant colony algorithm.

    PubMed

    Oakley, Mark T; Richardson, E Grace; Carr, Harriet; Johnston, Roy L

    2013-01-01

    We describe the LamarckiAnt algorithm: a search algorithm that combines the features of a "Lamarckian" genetic algorithm and ant colony optimization. We have implemented this algorithm for the optimization of BLN model proteins, which have frustrated energy landscapes and represent a challenge for global optimization algorithms. We demonstrate that LamarckiAnt performs competitively with other state-of-the-art optimization algorithms.

  6. Ant Colonies Prefer Infected over Uninfected Nest Sites

    PubMed Central

    Pontieri, Luigi; Vojvodic, Svjetlana; Graham, Riley; Pedersen, Jes Søe; Linksvayer, Timothy A.

    2014-01-01

    During colony relocation, the selection of a new nest involves exploration and assessment of potential sites followed by colony movement on the basis of a collective decision making process. Hygiene and pathogen load of the potential nest sites are factors worker scouts might evaluate, given the high risk of epidemics in group-living animals. Choosing nest sites free of pathogens is hypothesized to be highly efficient in invasive ants as each of their introduced populations is often an open network of nests exchanging individuals (unicolonial) with frequent relocation into new nest sites and low genetic diversity, likely making these species particularly vulnerable to parasites and diseases. We investigated the nest site preference of the invasive pharaoh ant, Monomorium pharaonis, through binary choice tests between three nest types: nests containing dead nestmates overgrown with sporulating mycelium of the entomopathogenic fungus Metarhizium brunneum (infected nests), nests containing nestmates killed by freezing (uninfected nests), and empty nests. In contrast to the expectation pharaoh ant colonies preferentially (84%) moved into the infected nest when presented with the choice of an infected and an uninfected nest. The ants had an intermediate preference for empty nests. Pharaoh ants display an overall preference for infected nests during colony relocation. While we cannot rule out that the ants are actually manipulated by the pathogen, we propose that this preference might be an adaptive strategy by the host to “immunize” the colony against future exposure to the same pathogenic fungus. PMID:25372856

  7. Bait distribution among multiple colonies of Pharaoh ants (hymenoptera: Formicidae).

    PubMed

    Oi, D H; Vail, K M; Williams, D F

    2000-08-01

    Pharaoh ant, Monomorium pharaonis (L.), infestations often consist of several colonies located at different nest sites. To achieve control, it is desirable to suppress or eliminate the populations of a majority of these colonies. We compared the trophallactic distribution and efficacy of two ant baits, with different modes of action, among groups of four colonies of Pharaoh ants. Baits contained either the metabolic-inhibiting active ingredient hydramethylnon or the insect growth regulator (IGR) pyriproxyfen. Within 3 wk, the hydramethylnon bait reduced worker and brood populations by at least 80%, and queen reductions ranged between 73 and 100%, when nests were in proximity (within 132 cm) to the bait source. However, these nest sites were reoccupied by ants from other colonies located further from the bait source. The pyriproxyfen bait was distributed more thoroughly to all nest locations with worker populations gradually declining by 73% at all nest sites after 8 wk. Average queen reductions ranged from 31 to 49% for all nest sites throughout the study. Even though some queens survived, brood reductions were rapid in the pyriproxyfen treatment, with reductions of 95% at all locations by week 3. Unlike the metabolic inhibitor, the IGR did not kill adult worker ants quickly, thus, more surviving worker ants were available to distribute the bait to all colonies located at different nest sites. Thus, from a single bait source, the slow-acting bait toxicant provided gradual, but long-term control, whereas the fast-acting bait toxicant provided rapid, localized control for a shorter duration.

  8. Ant colonies prefer infected over uninfected nest sites.

    PubMed

    Pontieri, Luigi; Vojvodic, Svjetlana; Graham, Riley; Pedersen, Jes Søe; Linksvayer, Timothy A

    2014-01-01

    During colony relocation, the selection of a new nest involves exploration and assessment of potential sites followed by colony movement on the basis of a collective decision making process. Hygiene and pathogen load of the potential nest sites are factors worker scouts might evaluate, given the high risk of epidemics in group-living animals. Choosing nest sites free of pathogens is hypothesized to be highly efficient in invasive ants as each of their introduced populations is often an open network of nests exchanging individuals (unicolonial) with frequent relocation into new nest sites and low genetic diversity, likely making these species particularly vulnerable to parasites and diseases. We investigated the nest site preference of the invasive pharaoh ant, Monomorium pharaonis, through binary choice tests between three nest types: nests containing dead nestmates overgrown with sporulating mycelium of the entomopathogenic fungus Metarhizium brunneum (infected nests), nests containing nestmates killed by freezing (uninfected nests), and empty nests. In contrast to the expectation pharaoh ant colonies preferentially (84%) moved into the infected nest when presented with the choice of an infected and an uninfected nest. The ants had an intermediate preference for empty nests. Pharaoh ants display an overall preference for infected nests during colony relocation. While we cannot rule out that the ants are actually manipulated by the pathogen, we propose that this preference might be an adaptive strategy by the host to "immunize" the colony against future exposure to the same pathogenic fungus.

  9. Improving Emergency Management by Modeling Ant Colonies

    DTIC Science & Technology

    2015-03-01

    Charles D. Michener and Mary H. Michener, “American Social Insects: A Book About Bees, Ants, Wasps, and Termites ” (New York: D Van Nostrand, 1951...no. 2 (1978): 183–216. Michener, Charles D. and Mary H. Michener. American Social Insects: A Book About Bees, Ants, Wasps, and Termites . New York

  10. Improved ant colony algorithm for global path planning

    NASA Astrophysics Data System (ADS)

    Li, Pengfei; Wang, Hongbo; Li, Xiaogang

    2017-03-01

    The ant colony algorithm has many advantages compared with other algorithms in path planning, but its shortcomings still cannot be ignored. For example, the convergence speed is very low at initial stage, it is easy to fall into the local optimal solution, and the solution speed is slow and so on. In order to solve these problems and reduce the search time, this paper firstly makes the assignment of the main parameters of α, β, M and ρ in the ant colony algorithm through a large number of experimental data analysis. Then an improved ant colony algorithm based on dynamic parameters and new pheromone updating mechanism is proposed in this paper. Simulation results show that the improved ant colony algorithm can not only greatly shorten the algorithm running time, but also has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm. It is very advantageous for solving large-scale optimization problems.

  11. Plant-derived differences in the composition of aphid honeydew and their effects on colonies of aphid-tending ants.

    PubMed

    Pringle, Elizabeth G; Novo, Alexandria; Ableson, Ian; Barbehenn, Raymond V; Vannette, Rachel L

    2014-11-01

    In plant-ant-hemipteran interactions, ants visit plants to consume the honeydew produced by phloem-feeding hemipterans. If genetically based differences in plant phloem chemistry change the chemical composition of hemipteran honeydew, then the plant's genetic constitution could have indirect effects on ants via the hemipterans. If such effects change ant behavior, they could feed back to affect the plant itself. We compared the chemical composition of honeydews produced by Aphis nerii aphid clones on two milkweed congeners, Asclepias curassavica and Asclepias incarnata, and we measured the responses of experimental Linepithema humile ant colonies to these honeydews. The compositions of secondary metabolites, sugars, and amino acids differed significantly in the honeydews from the two plant species. Ant colonies feeding on honeydew derived from A. incarnata recruited in higher numbers to artificial diet, maintained higher queen and worker dry weight, and sustained marginally more workers than ants feeding on honeydew derived from A. curassavica. Ants feeding on honeydew from A. incarnata were also more exploratory in behavioral assays than ants feeding from A. curassavica. Despite performing better when feeding on the A. incarnata honeydew, ant workers marginally preferred honeydew from A. curassavica to honeydew from A. incarnata when given a choice. Our results demonstrate that plant congeners can exert strong indirect effects on ant colonies by means of plant-species-specific differences in aphid honeydew chemistry. Moreover, these effects changed ant behavior and thus could feed back to affect plant performance in the field.

  12. Hierarchy length in orphaned colonies of the ant Temnothorax nylanderi

    NASA Astrophysics Data System (ADS)

    Heinze, J.

    2008-08-01

    Workers of the ant Temnothorax nylanderi form dominance orders in orphaned colonies in which only one or a few top-ranking workers begin to produce males from unfertilized eggs. Between one and 11 individuals initiated 80% of all aggression in 14 queenless colonies. As predicted from inclusive fitness models (Molet M, van Baalen M, Monnin T, Insectes Soc 52:247 256, 2005), hierarchy length was found to first increase with colony size and then to level off at larger worker numbers. The frequency and skew of aggression decreased with increasing size, indicating that rank orders are less pronounced in larger colonies.

  13. Colony-level impacts of parasitoid flies on fire ants.

    PubMed Central

    Mehdiabadi, Natasha J; Gilbert, Lawrence E

    2002-01-01

    The red imported fire ant is becoming a global ecological problem, having invaded the United States, Puerto Rico, New Zealand and, most recently, Australia. In its established areas, this pest is devastating natural biodiversity. Early attempts to halt fire ant expansion with pesticides actually enhanced its spread. Phorid fly parasitoids from South America have now been introduced into the United States as potential biological control agents of the red imported fire ant, but the impact of these flies on fire ant populations is currently unknown. In the laboratory, we show that an average phorid density of as little as one attacking fly per 200 foraging ants decreased colony protein consumption nearly twofold and significantly reduced numbers of large-sized workers 50 days later. The high impact of a single phorid occurred mainly because ants decreased foraging rates in the presence of the flies. Our experiments, the first (to our knowledge) to link indirect and direct effects of phorids on fire ants, demonstrate that colonies can be stressed with surprisingly low parasitoid densities. We interpret our findings with regard to the more complex fire ant-phorid interactions in the field. PMID:12204130

  14. 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.

  15. Improved ant colony algorithm and its simulation study

    NASA Astrophysics Data System (ADS)

    Wang, Zongjiang

    2013-03-01

    Ant colony algorithm is development a new heuristic algorithm through simulation ant foraging. For its convergence rate slow, easy to fall into local optimal solution proposed for the adjustment of key parameters, pheromone update to improve the way and through the issue of TSP experiments, results showed that the improved algorithm has better overall search capabilities and demonstrated the feasibility and effectiveness of this method.

  16. Research on the ant colony algorithm in robot path planning

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Ma, Jianming; Wang, Ying

    2017-05-01

    Using the A* algorithm principle proposed adaptive adjustment heuristic function, to reduce the degree of divergence algorithm; The state transition of the next ant improvement strategies, to improve the diversity of path planning solution; Control the change of the pheromone, to avoid algorithm trapped in local optimal solution; The improved ant colony algorithm makes the robot along an optimal or suboptimal path to arrive at the target.

  17. Plant-derived differences in the composition of aphid honeydew and their effects on colonies of aphid-tending ants

    PubMed Central

    Pringle, Elizabeth G; Novo, Alexandria; Ableson, Ian; Barbehenn, Raymond V; Vannette, Rachel L

    2014-01-01

    In plant–ant–hemipteran interactions, ants visit plants to consume the honeydew produced by phloem-feeding hemipterans. If genetically based differences in plant phloem chemistry change the chemical composition of hemipteran honeydew, then the plant's genetic constitution could have indirect effects on ants via the hemipterans. If such effects change ant behavior, they could feed back to affect the plant itself. We compared the chemical composition of honeydews produced by Aphis nerii aphid clones on two milkweed congeners, Asclepias curassavica and Asclepias incarnata, and we measured the responses of experimental Linepithema humile ant colonies to these honeydews. The compositions of secondary metabolites, sugars, and amino acids differed significantly in the honeydews from the two plant species. Ant colonies feeding on honeydew derived from A. incarnata recruited in higher numbers to artificial diet, maintained higher queen and worker dry weight, and sustained marginally more workers than ants feeding on honeydew derived from A. curassavica. Ants feeding on honeydew from A. incarnata were also more exploratory in behavioral assays than ants feeding from A. curassavica. Despite performing better when feeding on the A. incarnata honeydew, ant workers marginally preferred honeydew from A. curassavica to honeydew from A. incarnata when given a choice. Our results demonstrate that plant congeners can exert strong indirect effects on ant colonies by means of plant-species-specific differences in aphid honeydew chemistry. Moreover, these effects changed ant behavior and thus could feed back to affect plant performance in the field. PMID:25505534

  18. Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

    ERIC Educational Resources Information Center

    Rastegarmoghadam, Mahin; Ziarati, Koorush

    2017-01-01

    Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

  19. 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.

  20. 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

  1. All-Optical Implementation of the Ant Colony Optimization Algorithm

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    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.

  2. Improved Robustness through Population Variance in Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Matthews, David C.; Sutton, Andrew M.; Hains, Doug; Whitley, L. Darrell

    Ant Colony Optimization algorithms are population-based Stochastic Local Search algorithms that mimic the behavior of ants, simulating pheromone trails to search for solutions to combinatorial optimization problems. This paper introduces Population Variance, a novel approach to ACO algorithms that allows parameters to vary across the population over time, leading to solution construction differences that are not strictly stochastic. The increased exploration appears to help the search escape from local optima, significantly improving the robustness of the algorithm with respect to suboptimal parameter settings.

  3. Ant Colonies Do Not Trade-Off Reproduction against Maintenance.

    PubMed

    Kramer, Boris H; Schrempf, Alexandra; Scheuerlein, Alexander; Heinze, Jürgen

    2015-01-01

    The question on how individuals allocate resources into maintenance and reproduction is one of the central questions in life history theory. Yet, resource allocation into maintenance on the organismic level can only be measured indirectly. This is different in a social insect colony, a "superorganism" where workers represent the soma and the queen the germ line of the colony. Here, we investigate whether trade-offs exist between maintenance and reproduction on two levels of biological organization, queens and colonies, by following single-queen colonies of the ant Cardiocondyla obscurior throughout the entire lifespan of the queen. Our results show that maintenance and reproduction are positively correlated on the colony level, and we confirm results of an earlier study that found no trade-off on the individual (queen) level. We attribute this unexpected outcome to the existence of a positive feedback loop where investment into maintenance (workers) increases the rate of resource acquisition under laboratory conditions. Even though food was provided ad libitum, variation in productivity among the colonies suggests that resources can only be utilized and invested into additional maintenance and reproduction by the colony if enough workers are available. The resulting relationship between per-capita and colony productivity in our study fits well with other studies conducted in the field, where decreasing per-capita productivity and the leveling off of colony productivity have been linked to density dependent effects due to competition among colonies. This suggests that the absence of trade-offs in our laboratory study might also be prevalent under natural conditions, leading to a positive association of maintenance, (= growth) and reproduction. In this respect, insect colonies resemble indeterminate growing organisms.

  4. Modal parameters estimation using ant colony optimisation algorithm

    NASA Astrophysics Data System (ADS)

    Sitarz, Piotr; Powałka, Bartosz

    2016-08-01

    The paper puts forward a new estimation method of modal parameters for dynamical systems. The problem of parameter estimation has been simplified to optimisation which is carried out using the ant colony system algorithm. The proposed method significantly constrains the solution space, determined on the basis of frequency plots of the receptance FRFs (frequency response functions) for objects presented in the frequency domain. The constantly growing computing power of readily accessible PCs makes this novel approach a viable solution. The combination of deterministic constraints of the solution space with modified ant colony system algorithms produced excellent results for systems in which mode shapes are defined by distinctly different natural frequencies and for those in which natural frequencies are similar. The proposed method is fully autonomous and the user does not need to select a model order. The last section of the paper gives estimation results for two sample frequency plots, conducted with the proposed method and the PolyMAX algorithm.

  5. Response Ant Colony Optimization of End Milling Surface Roughness

    PubMed Central

    Kadirgama, K.; Noor, M. M.; Abd Alla, Ahmed N.

    2010-01-01

    Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant Colony Optimization (ACO). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness. PMID:22294914

  6. Task scheduling based on ant colony optimization in cloud environment

    NASA Astrophysics Data System (ADS)

    Guo, Qiang

    2017-04-01

    In order to optimize the task scheduling strategy in cloud environment, we propose a cloud computing task scheduling algorithm based on ant colony algorithm. The main goal of this algorithm is to minimize the makespan and the total cost of the tasks, while making the system load more balanced. In this paper, we establish the objective function of the makespan and costs of the tasks, define the load balance function. Meanwhile, we also improve the initialization of the pheromone, the heuristic function and the pheromone update method in the ant colony algorithm. Then, some experiments were carried out on the Cloudsim platform, and the results were compared with algorithms of ACO and Min-Min. The results shows that the algorithm is more efficient than the other two algorithms in makespan, costs and system load balancing.

  7. A Hybrid Ant Colony Algorithm for Loading Pattern Optimization

    NASA Astrophysics Data System (ADS)

    Hoareau, F.

    2014-06-01

    Electricité de France (EDF) operates 58 nuclear power plant (NPP), of the Pressurized Water Reactor (PWR) type. The loading pattern (LP) optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R&D has developed automatic optimization tools that assist the experts. The latter can resort, for instance, to a loading pattern optimization software based on ant colony algorithm. This paper presents an analysis of the search space of a few realistic loading pattern optimization problems. This analysis leads us to introduce a hybrid algorithm based on ant colony and a local search method. We then show that this new algorithm is able to generate loading patterns of good quality.

  8. Improved Clonal Selection Algorithm Combined with Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Gao, Shangce; Wang, Wei; Dai, Hongwei; Li, Fangjia; Tang, Zheng

    Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based on the concept of indirect cooperative foraging process via secreting pheromones. Its positive feedback ability is nice but its convergence speed is slow because of the little initial pheromones. In this paper, we propose a pheromone-linker to combine these two algorithms. The proposed hybrid clonal selection and ant colony optimization (CSA-ACO) reasonably utilizes the superiorities of both algorithms and also overcomes their inherent disadvantages. Simulation results based on the traveling salesman problems have demonstrated the merit of the proposed algorithm over some traditional techniques.

  9. Automated selection of appropriate pheromone representations in ant colony optimization.

    PubMed

    Montgomery, James; Randall, Marcus; Hendtlass, Tim

    2005-01-01

    Ant colony optimization (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some representations, distinct solutions appear multiple times, increasing the effective size of the search space and potentially misleading ants as to the true learned value of those solutions. In this article, we present a novel system for automatically generating appropriate pheromone representations, based on the characteristics of the problem model that ensures unique pheromone representation of solutions. This is the first stage in the development of a generalized ACO system that could be applied to a wide range of problems with little or no modification. However, the system we propose may be used in the development of any problem-specific ACO algorithm.

  10. 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%.

  11. Rationality in collective decision-making by ant colonies.

    PubMed

    Edwards, Susan C; Pratt, Stephen C

    2009-10-22

    Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants' decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals.

  12. Random walk models of worker sorting in ant colonies.

    PubMed

    Sendova-Franks, Ana B; Van Lent, Jan

    2002-07-21

    Sorting can be an important mechanism for the transfer of information from one level of biological organization to another. Here we study the algorithm underlying worker sorting in Leptothorax ant colonies. Worker sorting is related to task allocation and therefore to the adaptive advantages associated with an efficient system for the division of labour in ant colonies. We considered four spatially explicit individual-based models founded on two-dimensional correlated random walk. Our aim was to establish whether sorting at the level of the worker population could occur with minimal assumptions about the behavioural algorithm of individual workers. The behaviour of an individual worker in the models could be summarized by the rule "move if you can, turn always". We assume that the turning angle of a worker is individually specific and negatively dependent on the magnitude of an internal parameter micro which could be regarded as a measure of individual experience or task specialization. All four models attained a level of worker sortedness that was compatible with results from experiments onLeptothorax ant colonies. We found that the presence of a sorting pivot, such as the nest wall or an attraction force towards the centre of the worker population, was crucial for sorting. We make a distinction between such pivots and templates and discuss the biological implications of their difference.

  13. Colony size predicts division of labour in attine ants

    PubMed Central

    Ferguson-Gow, Henry; Sumner, Seirian; Bourke, Andrew F. G.; Jones, Kate E.

    2014-01-01

    Division of labour is central to the ecological success of eusocial insects, yet the evolutionary factors driving increases in complexity in division of labour are little known. The size–complexity hypothesis proposes that, as larger colonies evolve, both non-reproductive and reproductive division of labour become more complex as workers and queens act to maximize inclusive fitness. Using a statistically robust phylogenetic comparative analysis of social and environmental traits of species within the ant tribe Attini, we show that colony size is positively related to both non-reproductive (worker size variation) and reproductive (queen–worker dimorphism) division of labour. The results also suggested that colony size acts on non-reproductive and reproductive division of labour in different ways. Environmental factors, including measures of variation in temperature and precipitation, had no significant effects on any division of labour measure or colony size. Overall, these results support the size–complexity hypothesis for the evolution of social complexity and division of labour in eusocial insects. Determining the evolutionary drivers of colony size may help contribute to our understanding of the evolution of social complexity. PMID:25165765

  14. Rationality in collective decision-making by ant colonies

    PubMed Central

    Edwards, Susan C.; Pratt, Stephen C.

    2009-01-01

    Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants’ decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals. PMID:19625319

  15. Colony disassociation following diet partitioning in a unicolonial ant

    NASA Astrophysics Data System (ADS)

    Silverman, J.; Liang, D.

    2001-01-01

    Discriminating nestmates from alien conspecifics via chemical cues is recognized as a critical element in maintaining the integrity of insect societies. We determined, in laboratory experiments, that nestmate recognition in an introduced population of the Argentine ant, Linepithema humile, is modified by hydrocarbons acquired from insect prey, and that workers from spatially isolated colony fragments, each provided with prey that possessed distinct cuticular hydrocarbons, displayed aggressive behavior towards their former nestmates. Isolation for 28 days or more between colony fragments fed different prey was sufficient to prevent re-establishment of inter-nest communication for at least an additional 28 days through the introduction of a bridge between the nests. Ants possessed intrinsic cuticular hydrocarbons plus only those hydrocarbons from the prey they received during the isolation period. Colony fragments which were isolated for less than 28 days reunited with workers possessing both prey hydrocarbons. Therefore, L. humile nestmate recognition may be dynamic, being in part dependent on the spatio-temporal distribution of prey, along with physical factors permitting or restricting access of subcolony units to those prey.

  16. 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.

  17. 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

  18. 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.

  19. Blind noisy image quality evaluation using a deformable ant colony algorithm

    NASA Astrophysics Data System (ADS)

    Chen, Li; Huang, Xiaotong; Tian, Jing; Fu, Xiaowei

    2014-04-01

    The objective of blind noisy image quality assessment is to evaluate the quality of the degraded noisy image without the knowledge of the ground truth image. Its performance relies on the accuracy of the noise statistics estimated from homogenous blocks. The major challenge of block-based approaches lies in the block size selection, as it affects the local noise derivation. To tackle this challenge, a deformable ant colony optimization (DACO) approach is proposed in this paper to adaptively adjust the ant size for image block selection. The proposed DACO approach considers that the size of the ant is adjustable during foraging. For the smooth image blocks, more pheromone is deposited, and then the size of ant is increased. Therefore, this strategy enables the ants to have dynamic food-search capability, leading to more accurate selection of homogeneous blocks. Furthermore, the regression analysis is used to obtain image quality score by exploiting the above-estimated noise statistics. Experimental results are provided to justify that the proposed approach outperforms conventional approaches to provide more accurate noise statistics estimation and achieve a consistent image quality evaluation performance for both the artificially generated and real-world noisy images.

  20. 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.

  1. Artificial bee colony in neuro - Symbolic integration

    NASA Astrophysics Data System (ADS)

    Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

    2017-08-01

    Swarm intelligence is a research area that models the population of the swarm based on natural computation. Artificial bee colony (ABC) algorithm is a swarm based metaheuristic algorithm introduced by Karaboga to optimize numerical problem. Pattern-SAT is a pattern reconstruction paradigm that utilized 2SAT logical rule in representing the behavior of the desired pattern. The information of the desired pattern in terms of 2SAT logic is embedded to Hopfield neural network (HNN-P2SAT) and the desired pattern is reconstructed during the retrieval phase. Since the performance of HNN-P2SAT in Pattern-SAT deteriorates when the number of 2SAT clause increased, newly improved ABC is used to reduce the computation burden during the learning phase of HNN-P2SAT (HNN-P2SATABC). The aim of this study is to investigate the performance of Pattern-SAT produced by ABC incorporated with HNN-P2SAT and compare it with conventional standalone HNN. The comparison is examined by using Microsoft Visual Basic C++ 2013 software. The detailed comparison in doing Pattern-SAT is discussed based on global Pattern-SAT, ratio of activated clauses and computation time. The result obtained from computer simulation indicates the beneficial features of HNN-P2SATABC in doing Pattern-SAT. This finding is expected to result in a significant implication on the choice of searching method used to do Pattern-SAT.

  2. Solving Integer Programming Problems by Using Artificial Bee Colony Algorithm

    NASA Astrophysics Data System (ADS)

    Akay, Bahriye; Karaboga, Dervis

    This paper presents a study that applies the Artificial Bee Colony algorithm to integer programming problems and compares its performance with those of Particle Swarm Optimization algorithm variants and Branch and Bound technique presented to the literature. In order to cope with integer programming problems, in neighbour solution production unit, solutions are truncated to the nearest integer values. The experimental results show that Artificial Bee Colony algorithm can handle integer programming problems efficiently and Artificial Bee Colony algorithm can be considered to be very robust by the statistics calculated such as mean, median, standard deviation.

  3. Dose response of red imported fire ant colonies treated with Solenopsis invicta virus 3

    USDA-ARS?s Scientific Manuscript database

    Baiting tests were conducted to evaluate the effect of increasing Solenopsis invicta virus 3 (SINV-3) doses on fire ant colonies. Actively growing, early stage, fire ant (Solenopsis invicta) laboratory colonies were pulse-exposed to six concentrations of SINV-3 in a 10% sucrose bait and monitored r...

  4. 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...

  5. Colony-structure variation and interspecific competitive ability in the invasive Argentine ant.

    PubMed

    Holway, David A; Suarez, Andrew V

    2004-01-01

    The success of some invasive species may depend on phenotypic changes that occur following introduction. In Argentine ants (Linepithema humile) introduced populations typically lack intraspecific aggression, but native populations display such behavior commonly. We employ three approaches to examine how this behavioral shift might influence interspecific competitive ability. In a laboratory experiment, we reared colonies of Forelius mccooki with pairs of Argentine ant colonies that either did or did not exhibit intraspecific aggression. F. mccooki reared with intraspecifically non-aggressive pairs of Argentine ants produced fewer eggs, foraged less actively, and supported fewer living workers than those reared with intraspecifically aggressive pairs. At natural contact zones between competing colonies of L. humile and F. mccooki, the introduction of experimental Argentine ant colonies that fought with conspecific field colonies caused L. humile to abandon baits in the presence of F. mccooki, whereas the introduction of colonies that did not fight with field colonies of Argentine ants resulted in L. humile retaining possession of baits. Additional evidence for the potential importance of colony- structure variation comes from the Argentine ant's native range. At a site along the Rio de la Plata in Argentina, we found an inverse relationship between ant richness and density of L. humile (apparently a function of local differences in colony structure) in two different years of sampling.

  6. Aircraft technology portfolio optimization using ant colony optimization

    NASA Astrophysics Data System (ADS)

    Villeneuve, Frederic J.; Mavris, Dimitri N.

    2012-11-01

    Technology portfolio selection is a combinatorial optimization problem often faced with a large number of combinations and technology incompatibilities. The main research question addressed in this article is to determine if Ant Colony Optimization (ACO) is better suited than Genetic Algorithms (GAs) and Simulated Annealing (SA) for technology portfolio optimization when incompatibility constraints between technologies are present. Convergence rate, capability to find optima, and efficiency in handling of incompatibilities are the three criteria of comparison. The application problem consists of finding the best technology portfolio from 29 aircraft technologies. The results show that ACO and GAs converge faster and find optima more easily than SA, and that ACO can optimize portfolios with technology incompatibilities without using penalty functions. This latter finding paves the way for more use of ACO when the number of constraints increases, such as in the technology and concept selection for complex engineering systems.

  7. Strong Combination of Ant Colony Optimization with Constraint Programming Optimization

    NASA Astrophysics Data System (ADS)

    Khichane, Madjid; Albert, Patrick; Solnon, Christine

    We introduce an approach which combines ACO (Ant Colony Optimization) and IBM ILOG CP Optimizer for solving COPs (Combinatorial Optimization Problems). The problem is modeled using the CP Optimizer modeling API. Then, it is solved in a generic way by a two-phase algorithm. The first phase aims at creating a hot start for the second: it samples the solution space and applies reinforcement learning techniques as implemented in ACO to create pheromone trails. During the second phase, CP Optimizer performs a complete tree search guided by the pheromone trails previously accumulated. The first experimental results on knapsack, quadratic assignment and maximum independent set problems show that this new algorithm enhances the performance of CP Optimizer alone.

  8. Simulation of an Ant Colony Optimization Technique in Continuous Space-Time

    NASA Astrophysics Data System (ADS)

    Vlachos, D. S.

    2008-11-01

    The ant colony optimization system is an algorithm inspired by the ants' foraging behavior. The good results obtained by this system on academic problems has made it appealing for applications in industrial settings, one of the current hot topics of the method is the application in continuous problems. In this work, a modified model is presented which is based on autonomous agents, the ants, which behave like the ants in the ant colony system. These agents communicate by the biological inspired pheromone mechanism in order to find sources of food which located near their nest (optimal solutions).

  9. Displacement back analysis for underground engineering based on immunized continuous ant colony optimization

    NASA Astrophysics Data System (ADS)

    Gao, Wei

    2016-05-01

    The objective function of displacement back analysis for rock parameters in underground engineering is a very complicated nonlinear multiple hump function. The global optimization method can solve this problem very well. However, many numerical simulations must be performed during the optimization process, which is very time consuming. Therefore, it is important to improve the computational efficiency of optimization back analysis. To improve optimization back analysis, a new global optimization, immunized continuous ant colony optimization, is proposed. This is an improved continuous ant colony optimization using the basic principles of an artificial immune system and evolutionary algorithm. Based on this new global optimization, a new displacement optimization back analysis for rock parameters is proposed. The computational performance of the new back analysis is verified through a numerical example and a real engineering example. The results show that this new method can be used to obtain suitable parameters of rock mass with higher accuracy and less effort than previous methods. Moreover, the new back analysis is very robust.

  10. Solving optimum operation of single pump unit problem with ant colony optimization (ACO) algorithm

    NASA Astrophysics Data System (ADS)

    Yuan, Y.; Liu, C.

    2012-11-01

    For pumping stations, the effective scheduling of daily pump operations from solutions to the optimum design operation problem is one of the greatest potential areas for energy cost-savings, there are some difficulties in solving this problem with traditional optimization methods due to the multimodality of the solution region. In this case, an ACO model for optimum operation of pumping unit is proposed and the solution method by ants searching is presented by rationally setting the object function and constrained conditions. A weighted directed graph was constructed and feasible solutions may be found by iteratively searching of artificial ants, and then the optimal solution can be obtained by applying the rule of state transition and the pheromone updating. An example calculation was conducted and the minimum cost was found as 4.9979. The result of ant colony algorithm was compared with the result from dynamic programming or evolutionary solving method in commercial software under the same discrete condition. The result of ACO is better and the computing time is shorter which indicates that ACO algorithm can provide a high application value to the field of optimal operation of pumping stations and related fields.

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

    PubMed

    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.

  12. 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

  13. 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.

  14. Colony variation in the collective regulation of foraging by harvester ants

    PubMed Central

    Guetz, Adam; Greene, Michael J.; Holmes, Susan

    2011-01-01

    This study investigates variation in collective behavior in a natural population of colonies of the harvester ant, Pogonomyrmex barbatus. Harvester ant colonies regulate foraging activity to adjust to current food availability; the rate at which inactive foragers leave the nest on the next trip depends on the rate at which successful foragers return with food. This study investigates differences among colonies in foraging activity and how these differences are associated with variation among colonies in the regulation of foraging. Colonies differ in the baseline rate at which patrollers leave the nest, without stimulation from returning ants. This baseline rate predicts a colony's foraging activity, suggesting there is a colony-specific activity level that influences how quickly any ant leaves the nest. When a colony's foraging activity is high, the colony is more likely to regulate foraging. Moreover, colonies differ in the propensity to adjust the rate of outgoing foragers to the rate of forager return. Naturally occurring variation in the regulation of foraging may lead to variation in colony survival and reproductive success. PMID:22479133

  15. A dynamic ant colony optimization for load balancing in MRN/MLN

    NASA Astrophysics Data System (ADS)

    Lu, Le; Huang, Shanguo; Gu, Wanyi

    2011-12-01

    Ant Colony Optimization (ACO) is a popular research field these years. Ants choose paths where pheromone concentration is higher and modify the environment they visited. However, in the context of multi-service in multi-level and multi-domain optical network, the capacity of inter-domain links is limited. Congestion may be occurred at inter-domain links. In this paper, ant colony optimization algorithm based on load balancing is proposed. Ants follow paths not just depend on pheromone alone, we also take available resources on the link as a factor too. Simulations show the proposed method could reduce the traffic blocking probability, and realize load balancing within the network.

  16. 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.

  17. 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.

  18. CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET

    PubMed Central

    Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel

    2016-01-01

    A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO. PMID:27149517

  19. CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET.

    PubMed

    Aadil, Farhan; Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel

    2016-01-01

    A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO.

  20. 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.

  1. 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).

  2. antaRNA: ant colony-based RNA sequence design

    PubMed Central

    Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

    2015-01-01

    Motivation: 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. Results: 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. Availability and implementation: http://www.bioinf.uni-freiburg.de/Software/antaRNA Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26023105

  3. Ant colony optimization-based firewall anomaly mitigation engine.

    PubMed

    Penmatsa, Ravi Kiran Varma; Vatsavayi, Valli Kumari; Samayamantula, Srinivas Kumar

    2016-01-01

    A firewall is the most essential component of network perimeter security. Due to human error and the involvement of multiple administrators in configuring firewall rules, there exist common anomalies in firewall rulesets such as Shadowing, Generalization, Correlation, and Redundancy. There is a need for research on efficient ways of resolving such anomalies. The challenge is also to see that the reordered or resolved ruleset conforms to the organization's framed security policy. This study proposes an ant colony optimization (ACO)-based anomaly resolution and reordering of firewall rules called ACO-based firewall anomaly mitigation engine. Modified strategies are also introduced to automatically detect these anomalies and to minimize manual intervention of the administrator. Furthermore, an adaptive reordering strategy is proposed to aid faster reordering when a new rule is appended. The proposed approach was tested with different firewall policy sets. The results were found to be promising in terms of the number of conflicts resolved, with minimal availability loss and marginal security risk. This work demonstrated the application of a metaheuristic search technique, ACO, in improving the performance of a packet-filter firewall with respect to mitigating anomalies in the rules, and at the same time demonstrated conformance to the security policy.

  4. 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

  5. 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.

  6. 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.

  7. Global energy gradients and size in colonial organisms: worker mass and worker number in ant colonies.

    PubMed

    Kaspari, Michael

    2005-04-05

    Body mass shapes processes from cell metabolism to community dynamics. Little is known, however, about how the average body mass of individuals varies among ecological communities. Ants alter colony mass by independently changing worker mass and/or worker number. In a survey of 49 ecosystems from tundra to tropical rainforest, average worker mass and worker number were uncorrelated (r(s) = 0.2, P > 0.14) and varied 100-fold. Data supported the hypothesis that higher mean monthly temperatures, T, reduce worker mass by increasing metabolic costs during worker development. In contrast, worker number was unimodal over a 1,000-fold gradient of net primary productivity (NPP, g of carbon per m2 per yr), a measure of organic carbon available to consumers. At the lowest levels of NPP colonies appeared to be carbon-limited; above 60 g of carbon per m2 per yr average worker number decreased to a global low. This decline in worker number with increasing NPP supports the hypothesis that abundant carbon ameliorates the Achilles heel of small taxa in competition with large taxa: their relatively high metabolic demands. Higher predation rates in resource-rich environments may also play a role in limiting worker number. In all, about half the global variation in worker mass and number was accounted for by gradients of NPP and T. Changes in global temperature and rainfall may thus mold gradients of ectotherm size, with consequences for the structure and function of the ecosystems.

  8. A Multiple Ant Colony Metahuristic for the Air Refueling Tanker Assignment Problem

    DTIC Science & Technology

    2002-03-01

    allocation for AMC in 1999. Written in Visual Basic for Applications ( VBA ) macros, the Quick Look Tool’s goal was to determine the number of tankers needed...4 `` A MULTIPLE ANT COLONY METAHEURISTIC FOR THE AIR REFUELING TANKER ASSIGNMENT PROBLEM THESIS RonJon Annaballi...to) July 2001 - March 2002 Title and Subtitle A Multiple Ant Colony Optimization Metahuristic for the Air Refueling Tanker Assignment Problem

  9. Application of ant colony optimization to optimal foragaing theory: comparison of simulation and field results

    USDA-ARS?s Scientific Manuscript database

    Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...

  10. Information cascade, Kirman's ant colony model, and kinetic Ising model

    NASA Astrophysics Data System (ADS)

    Hisakado, Masato; Mori, Shintaro

    2015-01-01

    In this paper, we discuss a voting model in which voters can obtain information from a finite number of previous voters. There exist three groups of voters: (i) digital herders and independent voters, (ii) analog herders and independent voters, and (iii) tanh-type herders. In our previous paper Hisakado and Mori (2011), we used the mean field approximation for case (i). In that study, if the reference number r is above three, phase transition occurs and the solution converges to one of the equilibria. However, the conclusion is different from mean field approximation. In this paper, we show that the solution oscillates between the two states. A good (bad) equilibrium is where a majority of r select the correct (wrong) candidate. In this paper, we show that there is no phase transition when r is finite. If the annealing schedule is adequately slow from finite r to infinite r, the voting rate converges only to the good equilibrium. In case (ii), the state of reference votes is equivalent to that of Kirman's ant colony model, and it follows beta binomial distribution. In case (iii), we show that the model is equivalent to the finite-size kinetic Ising model. If the voters are rational, a simple herding experiment of information cascade is conducted. Information cascade results from the quenching of the kinetic Ising model. As case (i) is the limit of case (iii) when tanh function becomes a step function, the phase transition can be observed in infinite size limit. We can confirm that there is no phase transition when the reference number r is finite.

  11. A Colony Architecture for an Artificial Creature

    DTIC Science & Technology

    1989-08-01

    ORGANIZATION NAME AND ADDRESS 10. PROGAM .LFMENT, nnj’cT. TASK AREA G WORK UNIT NUMBERS Artificial Intelligence Laboratory 545 Technology Square Cambridge... Technology 1989 All Rights Reserved I II Acknowledgements Thanks to Rod Brooks for establishing a fine research laboratory, generating interesting ideas...Philosophy in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in September 1989. This report

  12. Effects of juvenile hormone analogs on new reproductives and colony growth of Pharaoh ant (Hymenoptera: Formicidae).

    PubMed

    Lim, S P; Lee, C Y

    2005-12-01

    Two juvenile hormone analogs (JHAs), pyriproxyfen and S-methoprene, were impregnated into dried tuna fish and fed to colonies of Monomorium pharaonis (L.) at very low concentrations (1.0, 2.0, 3.0, 4.0, and 5.0 microg/ml). Its effects on the production of sexuals and colonial growth were observed. Colonies treated with pyriproxyfen yielded sexuals with physical abnormalities. Both female and male sexuals developed bulbous wings, decreased melanization, and died shortly after emergence. Sexuals emerged from colonies treated with S-methoprene did not possess anomalous characteristics. Both pyriproxyfen and S-methoprene did not have significant effects on colonial growth because of the low concentrations of the baits. A commercial bait containing 0.3% S-methoprene (Bioprene-BM) also was evaluated for its efficacy on Pharaoh's ant colonies. Results showed that Pharaoh's ant colonies succumbed to the lethal effects of S-methoprene. Colony members were reduced significantly. Production of queens also decreased significantly in treated colonies and treated queens were unable to lay eggs. JHAs are slow acting and eliminate ant colonies at a relatively slow rate. At low concentrations, pyriproxyfen recorded baffling results, i.e., bulbous wings and demelanized exoskeleton, and it is vital that further studies are initiated to solidify these findings.

  13. Ant Colony Optimization with Memory and Its Application to Traveling Salesman Problem

    NASA Astrophysics Data System (ADS)

    Wang, Rong-Long; Zhao, Li-Qing; Zhou, Xiao-Fan

    Ant Colony Optimization (ACO) is one of the most recent techniques for solving combinatorial optimization problems, and has been unexpectedly successful. Therefore, many improvements have been proposed to improve the performance of the ACO algorithm. In this paper an ant colony optimization with memory is proposed, which is applied to the classical traveling salesman problem (TSP). In the proposed algorithm, each ant searches the solution not only according to the pheromone and heuristic information but also based on the memory which is from the solution of the last iteration. A large number of simulation runs are performed, and simulation results illustrate that the proposed algorithm performs better than the compared algorithms.

  14. Colony fusion in Argentine ants is guided by worker and queen cuticular hydrocarbon profile similarity.

    PubMed

    Vásquez, Gissella M; Schal, Coby; Silverman, Jules

    2009-08-01

    Introduced populations of the Argentine ant, Linepithema humile, have experienced moderate to severe losses of genetic diversity, which may have affected nestmate recognition to various degrees. We hypothesized that cuticular hydrocarbons (CHC) serve as nestmate recognition cues, and facilitate colony fusion of unrelated L. humile colonies that share similar CHC profiles. In this study, we paired six southeastern U.S. L. humile colonies in a 6-month laboratory fusion assay, and determined if worker and queen CHC profile similarity between colonies was associated with colony fusion and intercolony genetic similarity. We also compared worker and queen CHC profiles between fused colony pairs and unpaired controls to determine if worker and queen chemical profiles changed after fusion. We found that colony fusion correlated with the CHC similarity of workers and queens, with the frequency of fusion increasing with greater CHC profile similarity between colonies. Worker and queen CHC profile similarity between colonies also was associated with genetic similarity between colonies. Queen CHC profiles in fused colonies appeared to be a mix of the two colony phenotypes. In contrast, when only one of the paired colonies survived, the CHC profile of the surviving queens did not diverge from that of the colony of origin. Similarly, workers in non-fused colonies maintained their colony-specific CHC, whereas in fused colonies the worker CHC profiles were intermediate between those of the two colonies. These results suggest a role for CHC in regulating interactions among mutually aggressive L. humile colonies, and demonstrate that colony fusion correlates with both genetic and CHC similarities. Further, changes in worker and queen chemical profiles in fused colonies suggest that CHC plasticity may sustain the cohesion of unrelated L. humile colonies that had fused.

  15. 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

  16. The rewards of restraint in the collective regulation of foraging by harvester ant colonies.

    PubMed

    Gordon, Deborah M

    2013-06-06

    Collective behaviour, arising from local interactions, allows groups to respond to changing conditions. Long-term studies have shown that the traits of individual mammals and birds are associated with their reproductive success, but little is known about the evolutionary ecology of collective behaviour in natural populations. An ant colony operates without central control, regulating its activity through a network of local interactions. This work shows that variation among harvester ant (Pogonomyrmex barbatus) colonies in collective response to changing conditions is related to variation in colony lifetime reproductive success in the production of offspring colonies. Desiccation costs are high for harvester ants foraging in the desert. More successful colonies tend to forage less when conditions are dry, and show relatively stable foraging activity when conditions are more humid. Restraint from foraging does not compromise a colony's long-term survival; colonies that fail to forage at all on many days survive as long, over the colony's 20-30-year lifespan, as those that forage more regularly. Sensitivity to conditions in which to reduce foraging activity may be transmissible from parent to offspring colony. These results indicate that natural selection is shaping the collective behaviour that regulates foraging activity, and that the selection pressure, related to climate, may grow stronger if the current drought in their habitat persists.

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

    PubMed

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

    2016-03-29

    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.

  18. Improved packing of protein side chains with parallel ant colonies

    PubMed Central

    2014-01-01

    Introduction The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. Methods We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. Results We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. Conclusions This parallel approach combines various sources of searching intelligence and energy

  19. Improved packing of protein side chains with parallel ant colonies.

    PubMed

    Quan, Lijun; Lü, Qiang; Li, Haiou; Xia, Xiaoyan; Wu, Hongjie

    2014-01-01

    The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains

  20. Parasitoids and competitors influence colony-level responses in the red imported fire ant, Solenopsis invicta

    NASA Astrophysics Data System (ADS)

    Mehdiabadi, Natasha J.; Kawazoe, Elizabeth A.; Gilbert, Lawrence E.

    2004-11-01

    Social insect colonies respond to challenges set by a variable environment by reallocating work among colony members. In many social insects, such colony-level task allocation strategies are achieved through individual decisions that produce a self-organized adapting group. We investigated colony responses to parasitoids and native ant competitors in the red imported fire ant (Solenopsis invicta). Parasitoid flies affected fire ants by decreasing the proportion of workers engaged in foraging. Competitors also altered colony-level behaviours by reducing the proportion of foraging ants and by increasing the proportion of roaming majors, whose role is colony defence. Interestingly, the presence of both parasitism and competition almost always had similar effects on task allocation in comparison to each of the biotic factors on its own. Thus, our study uniquely demonstrates that the interactive effect of both parasitism and competition is not necessarily additive, implying that these biotic factors alter colony behaviour in distinct ways. More generally, our work demonstrates the importance of studying the dynamics of species interactions in a broader context.

  1. 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.

  2. Ant colonies and foraging line dynamics: Modeling, experiments and computations

    NASA Astrophysics Data System (ADS)

    Rossi, Louis

    2005-11-01

    Ants are one of several types of insects that form robust and complex societies, and as such, provide rich theoretical ground for the exploration and understanding of collective dynamics and the behaviorial parameters that drive the dynamics. Many species of ants are nearly or completely blind, so they interact locally through behaviorial cues with nearby ants, and through pheromone trails left by other ants. Consistent with biological observation, two populations of ants are modeled, those seeking food and those returning to the nest with food. A simple constitutive model relating ant densities to pheromone concentrations yields a system of equations describing two interacting fluids and predicts left- and right-moving traveling waves. All the model parameters can be reduced to two Froude numbers describing the ratio between a chemical potential and the kinetic energy of the traveling ants. Laboratory experiments on Tetramorium caespitum (L) clearly indicate left and right-moving traveling density waves in agreement with the mathematical model. We focus on understanding the evolutionary utility of the traveling waves, and the optimality of the Froude numbers and other parameters.

  3. The Role of Non-Foraging Nests in Polydomous Wood Ant Colonies

    PubMed Central

    Ellis, Samuel; Robinson, Elva J. H.

    2015-01-01

    A colony of red wood ants can inhabit more than one spatially separated nest, in a strategy called polydomy. Some nests within these polydomous colonies have no foraging trails to aphid colonies in the canopy. In this study we identify and investigate the possible roles of non-foraging nests in polydomous colonies of the wood ant Formica lugubris. To investigate the role of non-foraging nests we: (i) monitored colonies for three years; (ii) observed the resources being transported between non-foraging nests and the rest of the colony; (iii) measured the amount of extra-nest activity around non-foraging and foraging nests. We used these datasets to investigate the extent to which non-foraging nests within polydomous colonies are acting as: part of the colony expansion process; hunting and scavenging specialists; brood-development specialists; seasonal foragers; or a selfish strategy exploiting the foraging effort of the rest of the colony. We found that, rather than having a specialised role, non-foraging nests are part of the process of colony expansion. Polydomous colonies expand by founding new nests in the area surrounding the existing nests. Nests founded near food begin foraging and become part of the colony; other nests are not founded near food sources and do not initially forage. Some of these non-foraging nests eventually begin foraging; others do not and are abandoned. This is a method of colony growth not available to colonies inhabiting a single nest, and may be an important advantage of the polydomous nesting strategy, allowing the colony to expand into profitable areas. PMID:26465750

  4. The Role of Non-Foraging Nests in Polydomous Wood Ant Colonies.

    PubMed

    Ellis, Samuel; Robinson, Elva J H

    2015-01-01

    A colony of red wood ants can inhabit more than one spatially separated nest, in a strategy called polydomy. Some nests within these polydomous colonies have no foraging trails to aphid colonies in the canopy. In this study we identify and investigate the possible roles of non-foraging nests in polydomous colonies of the wood ant Formica lugubris. To investigate the role of non-foraging nests we: (i) monitored colonies for three years; (ii) observed the resources being transported between non-foraging nests and the rest of the colony; (iii) measured the amount of extra-nest activity around non-foraging and foraging nests. We used these datasets to investigate the extent to which non-foraging nests within polydomous colonies are acting as: part of the colony expansion process; hunting and scavenging specialists; brood-development specialists; seasonal foragers; or a selfish strategy exploiting the foraging effort of the rest of the colony. We found that, rather than having a specialised role, non-foraging nests are part of the process of colony expansion. Polydomous colonies expand by founding new nests in the area surrounding the existing nests. Nests founded near food begin foraging and become part of the colony; other nests are not founded near food sources and do not initially forage. Some of these non-foraging nests eventually begin foraging; others do not and are abandoned. This is a method of colony growth not available to colonies inhabiting a single nest, and may be an important advantage of the polydomous nesting strategy, allowing the colony to expand into profitable areas.

  5. The scent of supercolonies: the discovery, synthesis and behavioural verification of ant colony recognition cues

    PubMed Central

    Brandt, Miriam; van Wilgenburg, Ellen; Sulc, Robert; Shea, Kenneth J; Tsutsui, Neil D

    2009-01-01

    Background Ants form highly social and cooperative colonies that compete, and often fight, against other such colonies, both intra- and interspecifically. Some invasive ants take sociality to an extreme, forming geographically massive 'supercolonies' across thousands of kilometres. The success of social insects generally, as well as invasive ants in particular, stems from the sophisticated mechanisms used to accurately and precisely distinguish colonymates from non-colonymates. Surprisingly, however, the specific chemicals used for this recognition are virtually undescribed. Results Here, we report the discovery, chemical synthesis and behavioural testing of the colonymate recognition cues used by the widespread and invasive Argentine ant (Linepithema humile). By synthesizing pure versions of these chemicals in the laboratory and testing them in behavioural assays, we show that these compounds trigger aggression among normally amicable nestmates, but control hydrocarbons do not. Furthermore, behavioural testing across multiple different supercolonies reveals that the reaction to individual compounds varies from colony to colony -- the expected reaction to true colony recognition labels. Our results also show that both quantitative and qualitative changes to cuticular hydrocarbon profiles can trigger aggression among nestmates. These data point the way for the development of new environmentally-friendly control strategies based on the species-specific manipulation of aggressive behaviour. Conclusion Overall, our findings reveal the identity of specific chemicals used for colonymate recognition by the invasive Argentine ants. Although the particular chemicals used by other ants may differ, the patterns reported here are likely to be true for ants generally. As almost all invasive ants display widespread unicoloniality in their introduced ranges, our findings are particularly relevant for our understanding of the biology of these damaging invaders. PMID:19863781

  6. Performance evaluation of ant colony optimization-based solution strategies on the mixed-model assembly line balancing problem

    NASA Astrophysics Data System (ADS)

    Akpinar, Sener; Mirac Bayhan, G.

    2014-06-01

    The aim of this article is to compare the performances of iterative ant colony optimization (ACO)-based solution strategies on a mixed-model assembly line balancing problem of type II (MMALBP-II) by addressing some particular features of real-world assembly line balancing problems such as parallel workstations and zoning constraints. To solve the problem, where the objective is to minimize the cycle time (i.e. maximize the production rate) for a predefined number of workstations in an existing assembly line, two ACO-based approaches which differ in the mission assigned to artificial ants are used. Furthermore, each ACO-based approach is conducted with two different pheromone release strategies: global and local pheromone updating rules. The four ACO-based approaches are used for solving 20 representative MMALBP-II to compare their performance in terms of computational time and solution quality. Detailed comparison results are presented.

  7. Eggs of Mallada desjardinsi (Neuroptera: Chrysopidae) are protected by ants: the role of egg stalks in ant-tended aphid colonies.

    PubMed

    Hayashi, Masayuki; Nomura, Masashi

    2014-08-01

    In ant-aphid mutualisms, ants usually attack and exclude enemies of aphids. However, larvae of the green lacewing Mallada desjardinsi (Navas) prey on ant-tended aphids without being excluded by ants; these larvae protect themselves from ants by carrying aphid carcasses on their backs. Eggs of M. desjardinsi laid at the tips of stalks have also been observed in ant-tended aphid colonies in the field. Here, we examined whether the egg stalks of M. desjardinsi protect the eggs from ants and predators. When exposed to ants, almost all eggs with intact stalks were untouched, whereas 50-80% of eggs in which stalks had been severed at their bases were destroyed by ants. In contrast, most eggs were preyed upon by larvae of the lacewing Chrysoperla nipponensis (Okamoto), an intraguild predator of M. desjardinsi, regardless of whether their stalks had been severed. These findings suggest that egg stalks provide protection from ants but not from C. nipponensis larvae. To test whether M. desjardinsi eggs are protected from predators by aphid-tending ants, we introduced C. nipponensis larvae onto plants colonized by ant-tended aphids. A significantly greater number of eggs survived in the presence of ants because aphid-tending ants excluded larvae of C. nipponensis. This finding indicates that M. desjardinsi eggs are indirectly protected from predators by ants in ant-tended aphid colonies.

  8. Chaotic Artificial Bee Colony Used for Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Yudong; Wu, Lenan; Wang, Shuihua; Huo, Yuankai

    A new approach based on artificial bee colony (ABC) with chaotic theory was proposed to solve the partitional clustering problem. We first investigate the optimization model including both the encoding strategy and the variance ratio criterion (VRC). Second, a chaotic ABC algorithm was developed based on the Rossler attractor. Experiments on three types of artificial data of different degrees of overlapping all demonstrate the CABC is superior to both genetic algorithm (GA) and combinatorial particle swarm optimization (CPSO) in terms of robustness and computation time.

  9. Dose response of red imported fire ant colonies to Solenopsis invicta virus 3.

    PubMed

    Valles, Steven M; Porter, Sanford D

    2015-10-01

    Baiting tests were conducted to evaluate the effect of increasing Solenopsis invicta virus 3 (SINV-3) dose on fire ant colonies. Actively growing early-stage fire ant (Solenopsis invicta Buren) laboratory colonies were pulse-exposed for 24 hours to six concentrations of SINV-3 (10(1), 10(3), 10(5), 10(7), 10(9) genome equivalents/μl) in 1 ml of a 10 % sucrose bait and monitored regularly for two months. SINV-3 concentration had a significant effect on colony health. Brood rating (proportion of brood to worker ants) began to depart from the control group at 19 days for the 10(9) concentration and 26 days for the 10(7) concentration. At 60 days, brood rating was significantly lower among colonies treated with 10(9), 10(7), and 10(5) SINV-3 concentrations. The intermediate concentration, 10(5), appeared to cause a chronic, low-level infection with one colony (n = 9) supporting virus replication. Newly synthesized virus was not detected in any fire ant colonies treated at the 10(1) concentration, indicating that active infections failed to be established at this level of exposure. The highest bait concentration chosen, 10(9), appeared most effective from a control aspect; mean colony brood rating at this concentration (1.1 ± 0.9 at the 60 day time point) indicated poor colony health with minimal brood production. No clear relationship was observed between the quantity of plus genome strand detected and brood rating. Conversely, there was a strong relationship between the presence of the replicative genome strand and declining brood rating, which may serve as a predictor of disease severity. Recommendations for field treatment levels to control fire ants with SINV-3 are discussed.

  10. 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

  11. Mechanisms of social regulation change across colony development in an ant

    PubMed Central

    2010-01-01

    Background Mutual policing is an important mechanism for reducing conflict in cooperative groups. In societies of ants, bees, and wasps, mutual policing of worker reproduction can evolve when workers are more closely related to the queen's sons than to the sons of workers or when the costs of worker reproduction lower the inclusive fitness of workers. During colony growth, relatedness within the colony remains the same, but the costs of worker reproduction may change. The costs of worker reproduction are predicted to be greatest in incipient colonies. If the costs associated with worker reproduction outweigh the individual direct benefits to workers, policing mechanisms as found in larger colonies may be absent in incipient colonies. Results We investigated policing behaviour across colony growth in the ant Camponotus floridanus. In large colonies of this species, worker reproduction is policed by the destruction of worker-laid eggs. We found workers from incipient colonies do not exhibit policing behaviour, and instead tolerate all conspecific eggs. The change in policing behaviour is consistent with changes in egg surface hydrocarbons, which provide the informational basis for policing; eggs laid by queens from incipient colonies lack the characteristic hydrocarbons on the surface of eggs laid by queens from large colonies, making them chemically indistinguishable from worker-laid eggs. We also tested the response to fertility information in the context of queen tolerance. Workers from incipient colonies attacked foreign queens from large colonies; whereas workers from large colonies tolerated such queens. Workers from both incipient and large colonies attacked foreign queens from incipient colonies. Conclusions Our results provide novel insights into the regulation of worker reproduction in social insects at both the proximate and ultimate levels. At the proximate level, our results show that mechanisms of social regulation, such as the response to fertility

  12. An ant colony based resilience approach to cascading failures in cluster supply network

    NASA Astrophysics Data System (ADS)

    Wang, Yingcong; Xiao, Renbin

    2016-11-01

    Cluster supply chain network is a typical complex network and easily suffers cascading failures under disruption events, which is caused by the under-load of enterprises. Improving network resilience can increase the ability of recovery from cascading failures. Social resilience is found in ant colony and comes from ant's spatial fidelity zones (SFZ). Starting from the under-load failures, this paper proposes a resilience method to cascading failures in cluster supply chain network by leveraging on social resilience of ant colony. First, the mapping between ant colony SFZ and cluster supply chain network SFZ is presented. Second, a new cascading model for cluster supply chain network is constructed based on under-load failures. Then, the SFZ-based resilience method and index to cascading failures are developed according to ant colony's social resilience. Finally, a numerical simulation and a case study are used to verify the validity of the cascading model and the resilience method. Experimental results show that, the cluster supply chain network becomes resilient to cascading failures under the SFZ-based resilience method, and the cluster supply chain network resilience can be enhanced by improving the ability of enterprises to recover and adjust.

  13. 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

  14. Colony fusion and worker reproduction after queen loss in army ants

    PubMed Central

    Kronauer, Daniel J. C.; Schöning, Caspar; d'Ettorre, Patrizia; Boomsma, Jacobus J.

    2010-01-01

    Theory predicts that altruism is only evolutionarily stable if it is preferentially directed towards relatives, so that any such behaviour towards seemingly unrelated individuals requires scrutiny. Queenless army ant colonies, which have anecdotally been reported to fuse with queenright foreign colonies, are such an enigmatic case. Here we combine experimental queen removal with population genetics and cuticular chemistry analyses to show that colonies of the African army ant Dorylus molestus frequently merge with neighbouring colonies after queen loss. Merging colonies often have no direct co-ancestry, but are on average probably distantly related because of overall population viscosity. The alternative of male production by orphaned workers appears to be so inefficient that residual inclusive fitness of orphaned workers might be maximized by indiscriminately merging with neighbouring colonies to increase their reproductive success. We show that worker chemical recognition profiles remain similar after queen loss, but rapidly change into a mixed colony Gestalt odour after fusion, consistent with indiscriminate acceptance of alien workers that are no longer aggressive. We hypothesize that colony fusion after queen loss might be more widespread, especially in spatially structured populations of social insects where worker reproduction is not profitable. PMID:19889701

  15. Characterizing the Collective Personality of Ant Societies: Aggressive Colonies Do Not Abandon Their Home

    PubMed Central

    Fries, Stephan; Tirard, Claire; Foitzik, Susanne

    2012-01-01

    Animal groups can show consistent behaviors or personalities just like solitary animals. We studied the collective behavior of Temnothorax nylanderi ant colonies, including consistency in behavior and correlations between different behavioral traits. We focused on four collective behaviors (aggression against intruders, nest relocation, removal of infected corpses and nest reconstruction) and also tested for links to the immune defense level of a colony and a fitness component (per-capita productivity). Behaviors leading to an increased exposure of ants to micro-parasites were expected to be positively associated with immune defense measures and indeed colonies that often relocated to other nest sites showed increased immune defense levels. Besides, colonies that responded with low aggression to intruders or failed to remove infected corpses, showed a higher likelihood to move to a new nest site. This resembles the trade-off between aggression and relocation often observed in solitary animals. Finally, one of the behaviors, nest reconstruction, was positively linked to per-capita productivity, whereas other colony-level behaviors, such as aggression against intruders, showed no association, albeit all behaviors were expected to be important for fitness under field conditions. In summary, our study shows that ant societies exhibit complex personalities that can be associated to the physiology and fitness of the colony. Some of these behaviors are linked in suites of correlated behaviors, similar to personalities of solitary animals. PMID:22457751

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

    PubMed

    Waters, James S; Ochs, Alison; Fewell, Jennifer H; Harrison, Jon F

    2017-02-22

    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.

  17. Modeling temperature-mediated fluctuation in colony size in the fire ant, Solenopsis invicta.

    PubMed

    Asano, Erika; Cassill, Deby L

    2012-07-21

    In the social insects, colony size is central to the survival of the queen. Two endogenous factors, worker longevity and queen's daily egg production, are known to determine maximum colony size. A third endogenous factor, duration of worker development from egg to adult, regulates the rate of colony growth. In this paper, we report findings from a simulation quantifying the effects of temperature on colony size in the fire ant, Solenopsis invicta. The monthly average temperature over a six year period for the panhandle of north Florida was interpolated to determine the effects of daily temperature on a queen's egg production, worker developmental time and worker longevity. Additional daily temperatures were simulated: 7°C higher and 7°C lower than daily temperatures for north Florida. As expected, colony size was the largest when annual temperatures were the highest across seasons, ranging from 57,000 to 187,000. Colony size at intermediate daily temperatures ranged from 14,000 to 103,000; small colonies recovered rapidly as temperatures warmed. Colony size at lower daily temperatures ranged from 14,000 to 21,000. Extended worker longevity at lower temperatures compensated for low egg production and longer developmental time. And vice versa, the queen's high rate of egg production and the shorter developmental time compensated for shorter worker longevity at high temperatures. Because the fire ant nest consists of a heat-collecting dome in which to incubate brood during cold weather, and deep chambers in which to cool workers during hot weather, colony size is likely to be higher and more stable than our simulation showed. The extended longevity of workers and queens at low temperatures, and perhaps their ability to hibernate below the permafrost, might explain the ability of ants to colonize habitats worldwide. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. 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

  19. 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.

  20. Adaptive Edge Detection Using Adjusted ANT Colony Optimization

    NASA Astrophysics Data System (ADS)

    Davoodianidaliki, M.; Abedini, A.; Shankayi, M.

    2013-09-01

    Edges contain important information in image and edge detection can be considered a low level process in image processing. Among different methods developed for this purpose traditional methods are simple and rather efficient. In Swarm Intelligent methods developed in last decade, ACO is more capable in this process. This paper uses traditional edge detection operators such as Sobel and Canny as input to ACO and turns overall process adaptive to application. Magnitude matrix or edge image can be used for initial pheromone and ant distribution. Image size reduction is proposed as an efficient smoothing method. A few parameters such as area and diameter of travelled path by ants are converted into rules in pheromone update process. All rules are normalized and final value is acquired by averaging.

  1. The Relationship between Canopy Cover and Colony Size of the Wood Ant Formica lugubris - Implications for the Thermal Effects on a Keystone Ant Species

    PubMed Central

    Chen, Yi-Huei; Robinson, Elva J. H.

    2014-01-01

    Climate change may affect ecosystems and biodiversity through the impacts of rising temperature on species’ body size. In terms of physiology and genetics, the colony is the unit of selection for ants so colony size can be considered the body size of a colony. For polydomous ant species, a colony is spread across several nests. This study aims to clarify how climate change may influence an ecologically significant ant species group by investigating thermal effects on wood ant colony size. The strong link between canopy cover and the local temperatures of wood ant’s nesting location provides a feasible approach for our study. Our results showed that nests were larger in shadier areas where the thermal environment was colder and more stable compared to open areas. Colonies (sum of nests in a polydomous colony) also tended to be larger in shadier areas than in open areas. In addition to temperature, our results supported that food resource availability may be an additional factor mediating the relationship between canopy cover and nest size. The effects of canopy cover on total colony size may act at the nest level because of the positive relationship between total colony size and mean nest size, rather than at the colony level due to lack of link between canopy cover and number of nests per colony. Causal relationships between the environment and the life-history characteristics may suggest possible future impacts of climate change on these species. PMID:25551636

  2. Social prophylaxis: group interaction promotes collective immunity in ant colonies.

    PubMed

    Ugelvig, Line V; Cremer, Sylvia

    2007-11-20

    Life in a social group increases the risk of disease transmission. To counteract this threat, social insects have evolved manifold antiparasite defenses, ranging from social exclusion of infected group members to intensive care. It is generally assumed that individuals performing hygienic behaviors risk infecting themselves, suggesting a high direct cost of helping. Our work instead indicates the opposite for garden ants. Social contact with individual workers, which were experimentally exposed to a fungal parasite, provided a clear survival benefit to nontreated, naive group members upon later challenge with the same parasite. This first demonstration of contact immunity in Social Hymenoptera and complementary results from other animal groups and plants suggest its general importance in both antiparasite and antiherbivore defense. In addition to this physiological prophylaxis of adult ants, infection of the brood was prevented in our experiment by behavioral changes of treated and naive workers. Parasite-treated ants stayed away from the brood chamber, whereas their naive nestmates increased brood-care activities. Our findings reveal a direct benefit for individuals to perform hygienic behaviors toward others, and this might explain the widely observed maintenance of social cohesion under parasite attack in insect societies.

  3. Colony growth of two species of Solenopsis fire ants(Hymenoptera: Formicidae) reared with crickets and beef liver

    USDA-ARS?s Scientific Manuscript database

    Most diets for rearing fire ants and other ants contain insects such as crickets or mealworms. Unfortunately, insect diets are expensive, especially for large rearing operations, and are not always easily available. This study was designed to examine colony growth of Solenopsis fire ants on beef liv...

  4. 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...

  5. Improved ant colony optimization for optimal crop and irrigation water allocation by incorporating domain knowledge

    USDA-ARS?s Scientific Manuscript database

    An improved ant colony optimization (ACO) formulation for the allocation of crops and water to different irrigation areas is developed. The formulation enables dynamic adjustment of decision variable options and makes use of visibility factors (VFs, the domain knowledge that can be used to identify ...

  6. Biomantling and Bioturbation by Colonies of the Florida Harvester Ant, Pogonomyrmex badius

    PubMed Central

    Tschinkel, Walter R.

    2015-01-01

    In much of the world, soil-nesting ants are among the leading agents of biomantling and bioturbation, depositing excavated soil on the surface or in underground chambers. Colonies of the Florida harvester ant, Pogonomyrmex badius excavate a new nest once a year on average, depositing 0.1 to 12 L (3 L average) of soil on the surface. Repeated surveys of a population of about 400 colonies yielded the frequency of moves (approximately once per year), the distance moved (mean 4 m), and the direction moved (random). The area of the soil disc correlated well with the volume and maximum depth of the nest, as determined by excavation and mapping of chambers. The population-wide frequency distribution of disc areas thus yielded the frequency distribution of nest volumes and maximum depths. For each surveyed colony, the volume of soil excavated from six specified depth ranges and deposited on the surface was estimated. These parameters were used in a simulation to estimate the amount of soil mantled over time by the observed population of P. badius colonies. Spread evenly, P. badius mantling would create a soil layer averaging 0.43 cm thick in a millennium, with 10–15% of the soil deriving from depths greater than 1 m. Biomantling by P. badius is discussed in the context of the ant community of which it is a part, and in relation to literature reports of ant biomantling. PMID:25794047

  7. Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

    PubMed Central

    Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

    2014-01-01

    A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

  8. Assessment Guidelines for Ant Colony Algorithms when Solving Quadratic Assignment Problems

    NASA Astrophysics Data System (ADS)

    See, Phen Chiak; Yew Wong, Kuan; Komarudin, Komarudin

    2009-08-01

    To date, no consensus exists on how to evaluate the performance of a new Ant Colony Optimization (ACO) algorithm when solving Quadratic Assignment Problems (QAPs). Different performance measures and problems sets are used by researchers to evaluate their algorithms. This paper is aimed to provide a recapitulation of the relevant issues and suggest some guidelines for assessing the performance of new ACO algorithms.

  9. Ant colony optimization analysis on overall stability of high arch dam basis of field monitoring.

    PubMed

    Lin, Peng; Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

    2014-01-01

    A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline.

  10. 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…

  11. 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…

  12. Study on Increasing the Accuracy of Classification Based on Ant Colony algorithm

    NASA Astrophysics Data System (ADS)

    Yu, M.; Chen, D.-W.; Dai, C.-Y.; Li, Z.-L.

    2013-05-01

    The application for GIS advances the ability of data analysis on remote sensing image. The classification and distill of remote sensing image is the primary information source for GIS in LUCC application. How to increase the accuracy of classification is an important content of remote sensing research. Adding features and researching new classification methods are the ways to improve accuracy of classification. Ant colony algorithm based on mode framework defined, agents of the algorithms in nature-inspired computation field can show a kind of uniform intelligent computation mode. It is applied in remote sensing image classification is a new method of preliminary swarm intelligence. Studying the applicability of ant colony algorithm based on more features and exploring the advantages and performance of ant colony algorithm are provided with very important significance. The study takes the outskirts of Fuzhou with complicated land use in Fujian Province as study area. The multi-source database which contains the integration of spectral information (TM1-5, TM7, NDVI, NDBI) and topography characters (DEM, Slope, Aspect) and textural information (Mean, Variance, Homogeneity, Contrast, Dissimilarity, Entropy, Second Moment, Correlation) were built. Classification rules based different characters are discovered from the samples through ant colony algorithm and the classification test is performed based on these rules. At the same time, we compare with traditional maximum likelihood method, C4.5 algorithm and rough sets classifications for checking over the accuracies. The study showed that the accuracy of classification based on the ant colony algorithm is higher than other methods. In addition, the land use and cover changes in Fuzhou for the near term is studied and display the figures by using remote sensing technology based on ant colony algorithm. In addition, the land use and cover changes in Fuzhou for the near term is studied and display the figures by using

  13. ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization.

    PubMed

    Sagban, Rafid; Ku-Mahamud, Ku Ruhana; Abu Bakar, Muhamad Shahbani

    2015-01-01

    A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acoustics of their ant hosts. The parasites' reaction results from their ability to indicate the state of penetration. The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance's matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied. The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms. Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation. The analytical results showed that the proposed indicator is more informative and more robust.

  14. ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization

    PubMed Central

    Sagban, Rafid; Ku-Mahamud, Ku Ruhana; Abu Bakar, Muhamad Shahbani

    2015-01-01

    A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acoustics of their ant hosts. The parasites' reaction results from their ability to indicate the state of penetration. The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance's matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied. The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms. Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation. The analytical results showed that the proposed indicator is more informative and more robust. PMID:25954768

  15. Harvester Ant Colony Variation in Foraging Activity and Response to Humidity

    PubMed Central

    Gordon, Deborah M.; Dektar, Katherine N.; Pinter-Wollman, Noa

    2013-01-01

    Collective behavior is produced by interactions among individuals. Differences among groups in individual response to interactions can lead to ecologically important variation among groups in collective behavior. Here we examine variation among colonies in the foraging behavior of the harvester ant, Pogonomyrmex barbatus. Previous work shows how colonies regulate foraging in response to food availability and desiccation costs: the rate at which outgoing foragers leave the nest depends on the rate at which foragers return with food. To examine how colonies vary in response to humidity and in foraging rate, we performed field experiments that manipulated forager return rate in 94 trials with 17 colonies over 3 years. We found that the effect of returning foragers on the rate of outgoing foragers increases with humidity. There are consistent differences among colonies in foraging activity that persist from year to year. PMID:23717415

  16. Harvester ant colony variation in foraging activity and response to humidity.

    PubMed

    Gordon, Deborah M; Dektar, Katherine N; Pinter-Wollman, Noa

    2013-01-01

    Collective behavior is produced by interactions among individuals. Differences among groups in individual response to interactions can lead to ecologically important variation among groups in collective behavior. Here we examine variation among colonies in the foraging behavior of the harvester ant, Pogonomyrmex barbatus. Previous work shows how colonies regulate foraging in response to food availability and desiccation costs: the rate at which outgoing foragers leave the nest depends on the rate at which foragers return with food. To examine how colonies vary in response to humidity and in foraging rate, we performed field experiments that manipulated forager return rate in 94 trials with 17 colonies over 3 years. We found that the effect of returning foragers on the rate of outgoing foragers increases with humidity. There are consistent differences among colonies in foraging activity that persist from year to year.

  17. Simulation Studies on Harnessing of Artificial Ecosystems in Space Colonies

    NASA Astrophysics Data System (ADS)

    Miyajima, Hiroyuki

    Space Colonies are an artificial habitation built in space, an idea first proposed by Gerard K. O'Neill in 1969. He suggested they be placed at Lagrange points which are points in space that balance out the gravitational attraction of the Earth and Moon. There are three types of space colonies proposed: Bernard, Cylinder, and Stanford Torus. The cylinder type, designed by Gerard K. O'Neill, is the most popular in concept at 6 km diameter and 30 km length, corresponding to about 845 cubic km, ten thousand people would potentially be able to reside these. The habitation area would be rotated to generate a quasi-gravitation by centrifugal force. It would be rotated at 0.55 rpm to generate a gravitation equivalent to that of the earth. In the space colony, there would be six areas axially, consisting of flooring and windows alternately. Mobile mirrors would be located outside the windows to reflect sun light toward the habitation areas and generate day, night, and seasons within the space colony. Thus an artificial ecosystem would be created allowing people live in much the same way as they do on the earth. According to my former research on micro ecosystems, it is very difficult to keep the environment balanced at all points due to the large volume of the habitation area and the thermal input of the mobile mirrors. It is predicted that there will be differences in the environment at each point of the cylinder due to the mirror angle. Although controlling the whole artificial ecosystem balance is important, local environment control at each point is also important for people to live and work comfortably. Therefore, it is needed to develop simulation models which can study the whole ecosystem as well as local environments at each point at the same time. This model has to be able to simulate dynamics of the whole system as well as the local environments. In this study, I have developed a new model to simulate the whole and local dynamics in a space colony by using a cell

  18. 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

  19. 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.

  20. Dynamics of an ant-ant Obligate Mutualism: Colony Growth, Density Dependence and Frequency Dependence

    USDA-ARS?s Scientific Manuscript database

    In insect societies, worker versus queen development (reproductive caste) is typically governed by environmental factors, but many Pogonomyrmex seed-harvester ants exhibit strict genetic caste determination, resulting in an obligate mutualism between two reproductively isolated lineages. Same-linea...

  1. Foraging pattern, colony distribution, and foraging range of the Florida harvester ant Pogonomyrmex badius

    SciTech Connect

    Harrison, J.S.; Gentry, J.B.

    1981-12-01

    This report describes the foraging pattern of the Florida harvester ant Pogonomyrmex badius in a high-density population of colonies. The foraging pattern has both promoted and been influenced by the colony distribution. Pogonomyrmex badius forages from short trails which extend into a surrounding foraging range. Direction of foraging trails is influenced by the location of a colony's near neighbors. Seasonal nest relocations always occur along a foraging trail, usually the main trail. Foraging ranges are not actively defended, but are used almost exclusively by foragers from a single colony. Foraging ranges will be extended into an area abondoned by neighboring foragers, indicating that forager presence may define each colony's range. Colony distribution has remained essentially the same for several years, despite seasonal nest relocations and addition of new colonies. Establishment of trails and exclusive foraging ranges by each colony minimizes encounters with neighboring foragers and guarantees access to available resources; this pattern also pomotes maintenance of the existing colony distribution and partitioning of resources.

  2. Foraging pattern, colony distribution, and foraging range of the Florida harvester ant, Pogonomyrmex badius

    SciTech Connect

    Harrison, J.S.; Gentry, J.B.; Aiken, S.C.

    1981-12-01

    This report describes the foraging pattern of the Florida harvester ant Pogonomyrmex badius in a high-density population of colonies. The foraging pattern has both promoted and been influenced by the colony distribution. Pogonomyrmex badius forages from short trails which extend into a surrounding foraging range. Direction of foraging trails is influenced by the location of a colony's near neighbors. Seasonal nest relocations always occur along a foraging trail, usually the main trail. Foraging ranges are not actively defended, but are used almost exclusively by foragers from a single colony. Foraging ranges will be extended into an area abandoned by neighboring foragers, indicating that forager presence may define each colony's range. Colony distribution has remained essentially the same for several years, despite seasonal nest relocations and addition of new colonies. Establishment of trails and exclusive foraging ranges by each colony minimizes encounters with neighboring foragers and guarantees access to available resources; this pattern also promotes maintenance of the existing colony distribution and partitioning of resources.

  3. 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

  4. 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.

  5. Mechanism of leaf-cutting ant colony suppression by fipronil used in attractive toxic baits.

    PubMed

    Gandra, Lailla C; Amaral, Karina D; Couceiro, Joel C; Della Lucia, Terezinha Mc; Guedes, Raul Nc

    2016-08-01

    Attractive toxic baits are the prevailing method for managing leaf-cutting ants in the eucalypt forests planted for the production of pulp, paper, timber and charcoal. For successful use in these baits, the insecticidal compounds need to circumvent the typical defences of the eusocial leaf-cutting ants. The challenge is to have an insecticide in the bait that will not directly harm and/or compromise foraging workers, but that will eventually suppress the colony. These underlying mechanisms are poorly known, and here the potential mechanism of fipronil activity in toxic baits for leaf-cutting ants was assessed using colonies of the representative Neotropical Acromyrmex subterraneus subterraneus (Forel, 1893). Although forager activity was not directly impaired by fipronil, the insecticide affected forager nestmate interactions (auto- and allogrooming) and waste removal and, more importantly, greatly affected the minor workers, impairing their activities of fungus garden cultivation and progeny handling. The fast decay of the fungus garden compromised the sustainability of the colonies, ultimately leading to their demise within 8 days. The behavioural effects of sublethal insecticide exposure towards minor workers are the main determinants of insecticide activity as ant baits and should be targeted in developing such compounds. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  6. Ant-cuckoo colony optimization for feature selection in digital mammogram.

    PubMed

    Jona, J B; Nagaveni, N

    2014-01-15

    Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

  7. Polymorphic growth in larvae of the butterfly Maculinea rebeli, a social parasite of Myrmica ant colonies

    PubMed Central

    Thomas, J. A.; Elmes, G. W.; Wardlaw, J. C.

    1998-01-01

    Caterpillars of Maculinea rebeli have two growth strategies for living underground as social parasites of Myrmica ant colonies. Laboratory experiments and field data show that 25% of caterpillars live ten months with ants before pupating, whereas 75% grow slowly, parasitizing their hosts for 22 months. Both types of caterpillar form apparently identical similar-sized pupae. This may be the first description in the animal kingdom of polymorphic growth rates spanning different years within the same population, yet without resulting (as in salmonid fish) in two morphologically distinct adult types with obvious differences in behaviour. We suggest that a balanced polymorphism has evolved in M. rebeli growth rates, representing the most efficient way of exploiting the limited, yet steady, daily supply of food available to cuckoo-feeding parasites of long-lived ant societies. Bet-hedging benefits would also accrue to adult butterflies producing a mixture of annual and biennial offspring. Despite ergonomic and other benefits, partial biennialism is unlikely to evolve unless slow-growing individuals have enhanced survival and can remain attached to their mobile hosts. We show that caterpillars become so closely protected by, and integrated with, their host colonies that slow growers experience no greater mortality over two years than fast growers over one, and are transported in preference to the ants' own larvae when the host colony moves nest site.

  8. The Role of Colony Size on Tunnel Branching Morphogenesis in Ant Nests

    PubMed Central

    Gautrais, Jacques; Buhl, Jérôme; Valverde, Sergi; Kuntz, Pascale; Theraulaz, Guy

    2014-01-01

    Many ant species excavate nests that are made up of chambers and interconnecting tunnels. There is a general trend of an increase in nest complexity with increasing population size. This complexity reflects a higher ramification and anastomosis of tunnels that can be estimated by the meshedness coefficient of the tunnelling networks. It has long been observed that meshedness increases with colony size within and across species, but no explanation has been provided so far. Since colony size is a strong factor controlling collective digging, a high value of the meshedness could simply be a side effect of a larger number of workers. To test this hypothesis, we study the digging dynamics in different group size of ants Messor sancta. We build a model of collective digging that is calibrated from the experimental data. Model's predictions successfully reproduce the topological properties of tunnelling networks observed in experiments, including the increase of the meshedness with group size. We then use the model to investigate situations in which collective digging progresses outward from a centre corresponding to the way tunnelling behaviour occurs in field conditions. Our model predicts that, when all other parameters are kept constant, an increase of the number of workers leads to a higher value of the meshedness and a transition from tree-like structures to highly meshed networks. Therefore we conclude that colony size is a key factor determining tunnelling network complexity in ant colonies. PMID:25330080

  9. 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

  10. Presence of multiparasite infections within individual colonies of leaf-cutter ants.

    PubMed

    Taerum, S J; Cafaro, M J; Currie, C R

    2010-02-01

    Host-parasite dynamics can be altered when a host is infected by multiple parasite genotypes. The different strains of parasite are expected to compete for the limited host resources, potentially affecting the survival and reproduction of the host as well as the infecting parasites. Fungus-growing ants, including the well-known leaf-cutters, are an emerging model system for studying the evolution and ecology of symbiosis and host-parasite dynamics. We examine whether the fungus gardens of leaf-cutter ants can be simultaneously infected by multiple strains of the fungal pathogen Escovopsis. Intensive sampling of Escovopsis was conducted from individual gardens, as well as between different garden chambers within individual colonies of leaf-cutting ants. Isolates obtained were genotyped by DNA sequencing. We found that, minimally, 67% of the individual colonies of the leaf-cutter ant genera Atta and Acromyrmex and 50% of the At. colombica garden chambers studied were simultaneously infected by multiple distinct Escovopsis strains. Experimental challenges showed that different Escovopsis strains do not exhibit obvious antagonism toward each other, suggesting that coinfecting strains of the parasite do not engage in interference competition, although interactions were not studied at the cellular level. Further research is needed to understand interparasite interactions between coinfecting Escovopsis strains and to understand the impact of multiparasite infections on the survival of leaf-cutter ant gardens.

  11. Foraging arena size and structural complexity affect the dynamics of food distribution in ant colonies.

    PubMed

    Buczkowski, Grzegorz; VanWeelden, Matthew

    2010-12-01

    Food acquisition by ant colonies is a complex process that starts with acquiring food at the source (i.e., foraging) and culminates with food exchange in or around the nest (i.e., feeding). While ant foraging behavior is relatively well understood, the process of food distribution has received little attention, largely because of the lack of methodology that allows for accurate monitoring of food flow. In this study, we used the odorous house ant, Tapinoma sessile (Say) to investigate the effect of foraging arena size and structural complexity on the rate and the extent of spread of liquid carbohydrate food (sucrose solution) throughout a colony. To track the movement of food, we used protein marking and double-antibody sandwich enzyme-linked immunosorbent assay, DAS-ELISA. Variation in arena size, in conjunction with different colony sizes, allowed us to test the effect of different worker densities on food distribution. Results demonstrate that both arena size and colony size have a significant effect on the spread of the food and the number of workers receiving food decreased as arena size and colony size increased. When colony size was kept constant and arena size increased, the percentage of workers testing positive for the marker decreased, most likely because of fewer trophallactic interactions resulting from lower worker density. When arena size was kept constant and colony size increased, the percentage of workers testing positive decreased. Nonrandom (clustered) worker dispersion and a limited supply of food may have contributed to this result. Overall, results suggest that food distribution is more complete is smaller colonies regardless of the size of the foraging arena and that colony size, rather than worker density, is the primary factor affecting food distribution. The structural complexity of foraging arenas ranged from simple, two-dimensional space (empty arenas) to complex, three-dimensional space (arenas filled with mulch). The structural

  12. 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.

  13. A colony-level response to disease control in a leaf-cutting ant

    NASA Astrophysics Data System (ADS)

    Hart, Adam; Bot, A. N. M.; Brown, Mark

    2002-03-01

    Parasites and pathogens often impose significant costs on their hosts. This is particularly true for social organisms, where the genetic structure of groups and the accumulation of contaminated waste facilitate disease transmission. In response, hosts have evolved many mechanisms of defence against parasites. Here we present evidence that Atta colombica, a leaf-cutting ant, may combat Escovopsis, a dangerous parasite of Atta's garden fungus, through a colony-level behavioural response. In A. colombica, garden waste is removed from within the colony and transported to the midden - an external waste dump - where it is processed by a group of midden workers. We found that colonies infected with Escovopsis have higher numbers of workers on the midden, where Escovopsis is deposited. Further, midden workers are highly effective in dispersing newly deposited waste away from the dumping site. Thus, the colony-level task allocation strategies of the Atta superorganism may change in response to the threat of disease to a third, essential party.

  14. Quantifying the Effect of Colony Size and Food Distribution on Harvester Ant Foraging

    PubMed Central

    Flanagan, Tatiana P.; Letendre, Kenneth; Burnside, William R.; Fricke, G. Matthew; Moses, Melanie E.

    2012-01-01

    Desert seed-harvester ants, genus Pogonomyrmex, are central place foragers that search for resources collectively. We quantify how seed harvesters exploit the spatial distribution of seeds to improve their rate of seed collection. We find that foraging rates are significantly influenced by the clumpiness of experimental seed baits. Colonies collected seeds from larger piles faster than randomly distributed seeds. We developed a method to compare foraging rates on clumped versus random seeds across three Pogonomyrmex species that differ substantially in forager population size. The increase in foraging rate when food was clumped in larger piles was indistinguishable across the three species, suggesting that species with larger colonies are no better than species with smaller colonies at collecting clumped seeds. These findings contradict the theoretical expectation that larger groups are more efficient at exploiting clumped resources, thus contributing to our understanding of the importance of the spatial distribution of food sources and colony size for communication and organization in social insects. PMID:22808035

  15. Quantifying the effect of colony size and food distribution on harvester ant foraging.

    PubMed

    Flanagan, Tatiana P; Letendre, Kenneth; Burnside, William R; Fricke, G Matthew; Moses, Melanie E

    2012-01-01

    Desert seed-harvester ants, genus Pogonomyrmex, are central place foragers that search for resources collectively. We quantify how seed harvesters exploit the spatial distribution of seeds to improve their rate of seed collection. We find that foraging rates are significantly influenced by the clumpiness of experimental seed baits. Colonies collected seeds from larger piles faster than randomly distributed seeds. We developed a method to compare foraging rates on clumped versus random seeds across three Pogonomyrmex species that differ substantially in forager population size. The increase in foraging rate when food was clumped in larger piles was indistinguishable across the three species, suggesting that species with larger colonies are no better than species with smaller colonies at collecting clumped seeds. These findings contradict the theoretical expectation that larger groups are more efficient at exploiting clumped resources, thus contributing to our understanding of the importance of the spatial distribution of food sources and colony size for communication and organization in social insects.

  16. High recombination frequency creates genotypic diversity in colonies of the leaf-cutting ant Acromyrmex echinatior.

    PubMed

    Sirviö, A; Gadau, J; Rueppell, O; Lamatsch, D; Boomsma, J J; Pamilo, P; Page, R E

    2006-09-01

    Honeybees are known to have genetically diverse colonies because queens mate with many males and the recombination rate is extremely high. Genetic diversity among social insect workers has been hypothesized to improve general performance of large and complex colonies, but this idea has not been tested in other social insects. Here, we present a linkage map and an estimate of the recombination rate for Acromyrmex echinatior, a leaf-cutting ant that resembles the honeybee in having multiple mating of queens and colonies of approximately the same size. A map of 145 AFLP markers in 22 linkage groups yielded a total recombinational size of 2076 cM and an inferred recombination rate of 161 kb cM(-1) (or 6.2 cM Mb(-1)). This estimate is lower than in the honeybee but, as far as the mapping criteria can be compared, higher than in any other insect mapped so far. Earlier studies on A. echinatior have demonstrated that variation in division of labour and pathogen resistance has a genetic component and that genotypic diversity among workers may thus give colonies of this leaf-cutting ant a functional advantage. The present result is therefore consistent with the hypothesis that complex social life can select for an increased recombination rate through effects on genotypic diversity and colony performance.

  17. Warring arthropod societies: Social spider colonies can delay annihilation by predatory ants via reduced apparency and increased group size.

    PubMed

    Keiser, Carl N; Wright, Colin M; Pruitt, Jonathan N

    2015-10-01

    Sociality provides individuals with benefits via collective foraging and anti-predator defense. One of the costs of living in large groups, however, is increased apparency to natural enemies. Here, we test how the individual-level and collective traits of spider societies can increase the risk of discovery and death by predatory ants. We transplanted colonies of the social spider Stegodyphus dumicola into a habitat dense with one of their top predators, the pugnacious ant Anoplolepis custodiens. With three different experiments, we test how colony-wide survivorship in a predator-dense habitat can be altered by colony apparency (i.e., the presence of a capture web), group size, and group composition (i.e., the proportion of bold and shy personality types present). We also test how spiders' social context (i.e., living solitarily vs. among conspecifics) modifies their behaviour toward ants in their capture web. Colonies with capture webs intact were discovered by predatory ants on average 25% faster than colonies with the capture web removed, and all discovered colonies eventually collapsed and succumbed to predation. However, the lag time from discovery by ants to colony collapse was greater for colonies containing more individuals. The composition of individual personality types in the group had no influence on survivorship. Spiders in a social group were more likely to approach ants caught in their web than were isolated spiders. Isolated spiders were more likely to attack a safe prey item (a moth) than they were to attack ants and were more likely to retreat from ants after contact than they were after contact with moths. Together, our data suggest that the physical structures produced by large animal societies can increase their apparency to natural enemies, though larger groups can facilitate a longer lag time between discovery and demise. Lastly, the interaction between spiders and predatory ants seems to depend on the social context in which spiders reside.

  18. On the problem of solving the optimization for continuous space based on information distribution function of ant colony algorithm

    NASA Astrophysics Data System (ADS)

    Min, Huang; Na, Cai

    2017-06-01

    These years, ant colony algorithm has been widely used in solving the domain of discrete space optimization, while the research on solving the continuous space optimization was relatively little. Based on the original optimization for continuous space, the article proposes the improved ant colony algorithm which is used to Solve the optimization for continuous space, so as to overcome the ant colony algorithm’s disadvantages of searching for a long time in continuous space. The article improves the solving way for the total amount of information of each interval and the due number of ants. The article also introduces a function of changes with the increase of the number of iterations in order to enhance the convergence rate of the improved ant colony algorithm. The simulation results show that compared with the result in literature[5], the suggested improved ant colony algorithm that based on the information distribution function has a better convergence performance. Thus, the article provides a new feasible and effective method for ant colony algorithm to solve this kind of problem.

  19. Detection Of Ventricular Late Potentials Using Wavelet Transform And ANT Colony Optimization

    NASA Astrophysics Data System (ADS)

    Subramanian, A. Sankara; Gurusamy, G.; Selvakumar, G.

    2010-10-01

    Ventricular late Potentials (VLPs) are low-level high frequency signals that are usually found with in the terminal part of the QRS complex from patients after Myocardial Infraction. Patients with VLPs are at risk of developing Ventricular Tachycardia, which is the major cause of death if patients suffering from heart disease. In this paper the Discrete Wavelet Transform was used to detect VLPs and then ANT colony optimization (ACO) was applied to classify subjects with and without VLPs. A set of Discrete Wavelet Transform (DWT) coefficients is selected from the wavelet decomposition. Three standard parameters of VLPs such as QRST, D40 and V40 are also established. After that a novel clustering algorithm based on Ant Colony Optimization is developed for classifying arrhythmia types. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.

  20. Application of the dynamic ant colony algorithm on the optimal operation of cascade reservoirs

    NASA Astrophysics Data System (ADS)

    Tong, X. X.; Xu, W. S.; Wang, Y. F.; Zhang, Y. W.; Zhang, P. C.

    2016-08-01

    Due to the lack of dynamic adjustments between global searches and local optimization, it is difficult to maintain high diversity and overcome local optimum problems for Ant Colony Algorithms (ACA). Therefore, this paper proposes an improved ACA, Dynamic Ant Colony Algorithm (DACA). DACA applies dynamic adjustments on heuristic factor changes to balance global searches and local optimization in ACA, which decreases cosines. At the same time, by utilizing the randomness and ergodicity of the chaotic search, DACA implements the chaos disturbance on the path found in each ACA iteration to improve the algorithm's ability to jump out of the local optimum and avoid premature convergence. We conducted a case study with DACA for optimal joint operation of the Dadu River cascade reservoirs. The simulation results were compared with the results of the gradual optimization method and the standard ACA, which demonstrated the advantages of DACA in speed and precision.

  1. Ant workers die young and colonies collapse when fed a high-protein diet

    PubMed Central

    Dussutour, A.; Simpson, S. J.

    2012-01-01

    A key determinant of the relationship between diet and longevity is the balance of protein and carbohydrate in the diet. Eating excess protein relative to carbohydrate shortens lifespan in solitary insects. Here, we investigated the link between high-protein diet and longevity, both at the level of individual ants and colonies in black garden ants, Lasius niger. We explored how lifespan was affected by the dietary protein-to-carbohydrate ratio and the duration of exposure to a high-protein diet. We show that (i) restriction to high-protein, low-carbohydrate diets decreased worker lifespan by up to 10-fold; (ii) reduction in lifespan on such diets was mainly due to elevated intake of protein rather than lack of carbohydrate; and (iii) only one day of exposure to a high-protein diet had dire consequences for workers and the colony, reducing population size by more than 20 per cent. PMID:22357267

  2. Multiple sequence alignment algorithm based on a dispersion graph and ant colony algorithm.

    PubMed

    Chen, Weiyang; Liao, Bo; Zhu, Wen; Xiang, Xuyu

    2009-10-01

    In this article, we describe a representation for the processes of multiple sequences alignment (MSA) and used it to solve the problem of MSA. By this representation, we took every possible aligning result into account by defining the representation of gap insertion, the value of heuristic information in every optional path and scoring rule. On the basis of the proposed multidimensional graph, we used the ant colony algorithm to find the better path that denotes a better aligning result. In our article, we proposed the instance of three-dimensional graph and four-dimensional graph and advanced a special ichnographic representation to analyze MSA. It is yet only an experimental software, and we gave an example for finding the best aligning result by three-dimensional graph and ant colony algorithm. Experimental results show that our method can improve the solution quality on MSA benchmarks. Copyright 2009 Wiley Periodicals, Inc.

  3. Routing in Wireless Sensor Networks Using an Ant Colony Optimization (ACO) Router Chip.

    PubMed

    Okdem, Selcuk; Karaboga, Dervis

    2009-01-01

    Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. A novel routing approach using an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks consisting of stable nodes. Illustrative examples, detailed descriptions and comparative performance test results of the proposed approach are included. The approach is also implemented to a small sized hardware component as a router chip. Simulation results show that proposed algorithm provides promising solutions allowing node designers to efficiently operate routing tasks.

  4. Routing in Wireless Sensor Networks Using an Ant Colony Optimization (ACO) Router Chip

    PubMed Central

    Okdem, Selcuk; Karaboga, Dervis

    2009-01-01

    Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. A novel routing approach using an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks consisting of stable nodes. Illustrative examples, detailed descriptions and comparative performance test results of the proposed approach are included. The approach is also implemented to a small sized hardware component as a router chip. Simulation results show that proposed algorithm provides promising solutions allowing node designers to efficiently operate routing tasks. PMID:22399947

  5. A graph-based ant colony optimization approach for process planning.

    PubMed

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach.

  6. 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.

  7. Multi-Robot Dynamic Task Allocation Using Modified Ant Colony System

    NASA Astrophysics Data System (ADS)

    Xu, Zhenzhen; Xia, Feng; Zhang, Xianchao

    This paper presents a dynamic task allocation algorithm for multiple robots to visit multiple targets. This algorithm is specifically designed for the environment where robots have dissimilar starting and ending locations. And the constraint of balancing the number of targets visited by each robot is considered. More importantly, this paper takes into account the dynamicity of multi-robot system and the obstacles in the environment. This problem is modeled as a constrained MTSP which can not be transformed to TSP and can not be solved by classical Ant Colony System (ACS). The Modified Ant Colony System (MACS) is presented to solve this problem and the unvisited targets are allocated to appropriate robots dynamically. The simulation results show that the output of the proposed algorithm can satisfy the constraints and dynamicity for the problem of multi-robot task allocation.

  8. [The queen technic for ant control. I. The effect of tepa on laboratory colonies of the pharaoh ant].

    PubMed

    Berndt, K P; Nitschmann, J

    1977-02-01

    The present paper discussed at the example of Tepa [Tris (1-aziridinyl) phosphine oxide] in which manner the control of pharaoh's ant in the sense of the "queen technique" with chemosterilants is possible; which points of view must be considered and which condition an acceptable substance should be fulfilled. The application of Tepa is ralized according to various techniques (e.g. dipping, baiting, tarsal contact), in the course of which the baiting technique is preferred. The influence of different concentrations in various baits on the brood, workers and queens are described. In baits with 1% of the substance a permanent sterilization could be achieved. In combination with other population depressing factors (larval and worker mortality) resulted in eradication of the colonies. The action extended also to the larvae of the sexuals, so that the queenless colonies failed in the production of new queens and males. Histological investigations showed in the females at higher concentrations distinct pathological alterations (pycnosis, vacuolizations, proliferation in the follicles epithelium); whereas the spermatogenesis in the males is decreased but not entirely suppressed. At lower concentrations only the fertility but not the fecundity was influenced. A handing-over of recessive lethal mutations to the progeny does not take place. The practical points of view for the use of chemosterilants in the control of pharaoh's ant are discussed. Whereas the low biological stability of Tepa does not exclude an introduction in the practice, the high mutagenic activity prevents an application in the field.

  9. 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,...

  10. Artificial bee colony algorithm for solving optimal power flow problem.

    PubMed

    Le Dinh, Luong; Vo Ngoc, Dieu; Vasant, Pandian

    2013-01-01

    This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem.

  11. Improved Artificial Bee Colony Algorithm Based Gravity Matching Navigation Method

    PubMed Central

    Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

    2014-01-01

    Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019

  12. Artificial bee colony algorithm with dynamic multi-population

    NASA Astrophysics Data System (ADS)

    Zhang, Ming; Ji, Zhicheng; Wang, Yan

    2017-07-01

    To improve the convergence rate and make a balance between the global search and local turning abilities, this paper proposes a decentralized form of artificial bee colony (ABC) algorithm with dynamic multi-populations by means of fuzzy C-means (FCM) clustering. Each subpopulation periodically enlarges with the same size during the search process, and the overlapping individuals among different subareas work for delivering information acting as exploring the search space with diffusion of solutions. Moreover, a Gaussian-based search equation with redefined local attractor is proposed to further accelerate the diffusion of the best solution and guide the search towards potential areas. Experimental results on a set of benchmarks demonstrate the competitive performance of our proposed approach.

  13. Improved artificial bee colony algorithm based gravity matching navigation method.

    PubMed

    Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

    2014-07-18

    Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

  14. An artificial bee colony algorithm for uncertain portfolio selection.

    PubMed

    Chen, Wei

    2014-01-01

    Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm.

  15. Modified artificial bee colony optimization with block perturbation strategy

    NASA Astrophysics Data System (ADS)

    Jia, Dongli; Duan, Xintao; Khurram Khan, Muhammad

    2015-05-01

    As a newly emerged swarm intelligence-based optimizer, the artificial bee colony (ABC) algorithm has attracted the interest of researchers in recent years owing to its ease of use and efficiency. In this article, a modified ABC algorithm with block perturbation strategy (BABC) is proposed. Unlike basic ABC, in the BABC algorithm, not one element but a block of elements from the parent solutions is changed while producing a new solution. The performance of the BABC algorithm is investigated and compared with that of the basic ABC, modified ABC, Brest's differential evolution, self-adaptive differential evolution and restart covariance matrix adaptation evolution strategy (IPOP-CMA-ES) over a set of widely used benchmark functions. The obtained results show that the performance of BABC is better than, or at least comparable to, that of the basic ABC, improved differential evolution variants and IPOP-CMA-ES in terms of convergence speed and final solution accuracy.

  16. An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection

    PubMed Central

    Chen, Wei

    2014-01-01

    Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm. PMID:25089292

  17. Ant Colony Optimization with Genetic Operation and Its Application to Traveling Salesman Problem

    NASA Astrophysics Data System (ADS)

    Wang, Rong-Long; Zhou, Xiao-Fan; Okazaki, Kozo

    Ant colony optimization (ACO) algorithms are a recently developed, population-based approach which has been successfully applied to optimization problems. However, in the ACO algorithms it is difficult to adjust the balance between intensification and diversification and thus the performance is not always very well. In this work, we propose an improved ACO algorithm in which some of ants can evolve by performing genetic operation, and the balance between intensification and diversification can be adjusted by numbers of ants which perform genetic operation. The proposed algorithm is tested by simulating the Traveling Salesman Problem (TSP). Experimental studies show that the proposed ACO algorithm with genetic operation has superior performance when compared to other existing ACO algorithms.

  18. ACC-FMD: ant colony clustering for functional module detection in protein-protein interaction networks.

    PubMed

    Ji, Junzhong; Liu, Hongxin; Zhang, Aidong; Liu, Zhijun; Liu, Chunnian

    2015-01-01

    Mining functional modules in Protein-Protein Interaction (PPI) networks is a very important research for revealing the structure-functionality relationships in biological processes. More recently, some swarm intelligence algorithms have been successfully applied in the field. This paper presents a new nature-inspired approach, ACC-FMD, which is based on ant colony clustering to detect functional modules. First, some proteins with the higher clustering coefficients are, respectively, selected as ant seed nodes. And then, the picking and dropping operations based on ant probabilistic models are developed and employed to assign proteins into the corresponding clusters represented by seeds. Finally, the best clustering result in each generation is used to perform the information transmission by updating the similarly function. Experimental results on some benchmarked datasets show that ACC-FMD outperforms the CFinder and MCODE algorithms and has comparative performance with the MINE, COACH, DPClus and Core algorithms in terms of the general evaluation metrics.

  19. Coupling ant colony optimization and the extended great deluge algorithm for the discrete facility layout problem

    NASA Astrophysics Data System (ADS)

    Nourelfath, M.; Nahas, N.; Montreuil, B.

    2007-12-01

    This article uses a hybrid optimization approach to solve the discrete facility layout problem (FLP), modelled as a quadratic assignment problem (QAP). The idea of this approach design is inspired by the ant colony meta-heuristic optimization method, combined with the extended great deluge (EGD) local search technique. Comparative computational experiments are carried out on benchmarks taken from the QAP-library and from real life problems. The performance of the proposed algorithm is compared to construction and improvement heuristics such as H63, HC63-66, CRAFT and Bubble Search, as well as other existing meta-heuristics developed in the literature based on simulated annealing (SA), tabu search and genetic algorithms (GAs). This algorithm is compared also to other ant colony implementations for QAP. The experimental results show that the proposed ant colony optimization/extended great deluge (ACO/EGD) performs significantly better than the existing construction and improvement algorithms. The experimental results indicate also that the ACO/EGD heuristic methodology offers advantages over other algorithms based on meta-heuristics in terms of solution quality.

  20. Efficacy of simulated barrier treatments against laboratory colonies of Pharaoh ant.

    PubMed

    Buczkowski, Grzegorz; Scharf, Michael E; Ratliff, Catina R; Bennett, Gary W

    2005-04-01

    Five selected insecticides were applied to four substrates and evaluated in laboratory studies for repellency and toxicity against the Pharaoh ant, Monomorium pharaonis (L.). We tested both repellent and nonrepellent formulations on outdoor (concrete and mulch) and indoor (ceramic and vinyl) substrates. Repellency was evaluated using a behavioral bioassay in which colonies were given a choice to leave the treated zone and move into empty nests provided in the untreated zone. We used a novel experimental design whereby ants walked on a Slinky coil suspended from a metal support frame, thus permitting a long foraging distance with a minimum use of space and resources. Cypermethrin, a repellent pyrethroid insecticide, resulted in colony budding, although the response was delayed. Toxicity of insecticides was evaluated as worker, queen, and brood mortality. The most effective treatment was fipronil, which provided 100% reduction in pretreatment activity by 2 d posttreatment on both concrete and mulch. Chlorfenapyr was highly effective on both outdoor and indoor substrates. Significant substrate effects were observed with insecticides applied to nonabsorbent substrates (ceramic tile), which performed better than insecticides applied to absorbent substrates (vinyl tile). Other highly absorbent materials (mulch and concrete), however, did not reduce insecticide efficacy. This is because ants relocated nests into and/or under these attractive nesting materials, thus increasing their exposure to toxic insecticide residues. Our results demonstrate efficacy of nonrepellent liquid insecticides as indoor treatments for the control of Pharaoh ants and possibly as exterior perimeter treatments.

  1. Monomorphic ants undergo within-colony morphological changes along the metal-pollution gradient.

    PubMed

    Grześ, Irena M; Okrutniak, Mateusz; Woch, Marcin W

    2015-04-01

    In ants, intra and inter-colony variation in body size can be considerable, even in monomorphic species. It has been previously shown that size-related parameters can be environmentally sensitive. The shape of the body size distribution curve is, however, rarely investigated. In this study, we measured head widthes of the black garden ant Lasius niger workers using digital methods. The ants were sampled from 51 colonies originating from 19 sites located along a metal pollution gradient, established in a former mining area in Poland. Total zinc concentrations in random samples of small invertebrates were used as a measure of site pollution levels. We found that the skewness of head size distribution grows significantly in line with the pollution level of the site, ranging from values slightly below zero (about -0.5) in the least polluted site up to a positive value (about 1.5) in the most polluted site. This result indicates that the frequency of small ants grows as pollution levels increase. The coefficient of variation, as well as the measures of central tendency, was not related to the pollution level. Four hypotheses explaining the obtained results are proposed. The bias towards the higher frequency of small workers may result from energy limitation and/or metal toxicity, but may also have an adaptive function.

  2. Training Spiking Neural Models Using Artificial Bee Colony

    PubMed Central

    Vazquez, Roberto A.; Garro, Beatriz A.

    2015-01-01

    Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

  3. Artificial Symmetry-Breaking for Morphogenetic Engineering Bacterial Colonies.

    PubMed

    Nuñez, Isaac N; Matute, Tamara F; Del Valle, Ilenne D; Kan, Anton; Choksi, Atri; Endy, Drew; Haseloff, Jim; Rudge, Timothy J; Federici, Fernan

    2017-02-17

    Morphogenetic engineering is an emerging field that explores the design and implementation of self-organized patterns, morphologies, and architectures in systems composed of multiple agents such as cells and swarm robots. Synthetic biology, on the other hand, aims to develop tools and formalisms that increase reproducibility, tractability, and efficiency in the engineering of biological systems. We seek to apply synthetic biology approaches to the engineering of morphologies in multicellular systems. Here, we describe the engineering of two mechanisms, symmetry-breaking and domain-specific cell regulation, as elementary functions for the prototyping of morphogenetic instructions in bacterial colonies. The former represents an artificial patterning mechanism based on plasmid segregation while the latter plays the role of artificial cell differentiation by spatial colocalization of ubiquitous and segregated components. This separation of patterning from actuation facilitates the design-build-test-improve engineering cycle. We created computational modules for CellModeller representing these basic functions and used it to guide the design process and explore the design space in silico. We applied these tools to encode spatially structured functions such as metabolic complementation, RNAPT7 gene expression, and CRISPRi/Cas9 regulation. Finally, as a proof of concept, we used CRISPRi/Cas technology to regulate cell growth by controlling methionine synthesis. These mechanisms start from single cells enabling the study of morphogenetic principles and the engineering of novel population scale structures from the bottom up.

  4. Blending of heritable recognition cues among ant nestmates creates distinct colony gestalt odours but prevents within-colony nepotism.

    PubMed

    van Zweden, J S; Brask, J B; Christensen, J H; Boomsma, J J; Linksvayer, T A; d'Ettorre, P

    2010-07-01

    The evolution of sociality is facilitated by the recognition of close kin, but if kin recognition is too accurate, nepotistic behaviour within societies can dissolve social cohesion. In social insects, cuticular hydrocarbons act as nestmate recognition cues and are usually mixed among colony members to create a Gestalt odour. Although earlier studies have established that hydrocarbon profiles are influenced by heritable factors, transfer among nestmates and additional environmental factors, no studies have quantified these relative contributions for separate compounds. Here, we use the ant Formica rufibarbis in a cross-fostering design to test the degree to which hydrocarbons are heritably synthesized by young workers and transferred by their foster workers. Bioassays show that nestmate recognition has a significant heritable component. Multivariate quantitative analyses based on 38 hydrocarbons reveal that a subset of branched alkanes are heritably synthesized, but that these are also extensively transferred among nestmates. In contrast, especially linear alkanes are less heritable and little transferred; these are therefore unlikely to act as cues that allow within-colony nepotistic discrimination or as nestmate recognition cues. These results indicate that heritable compounds are suitable for establishing a genetic Gestalt for efficient nestmate recognition, but that recognition cues within colonies are insufficiently distinct to allow nepotistic kin discrimination.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

    2016-06-01

    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.

  7. Discrete artificial bee colony algorithm for lot-streaming flowshop with total flowtime minimization

    NASA Astrophysics Data System (ADS)

    Sang, Hongyan; Gao, Liang; Pan, Quanke

    2012-09-01

    Unlike a traditional flowshop problem where a job is assumed to be indivisible, in the lot-streaming flowshop problem, a job is allowed to overlap its operations between successive machines by splitting it into a number of smaller sub-lots and moving the completed portion of the sub-lots to downstream machine. In this way, the production is accelerated. This paper presents a discrete artificial bee colony (DABC) algorithm for a lot-streaming flowshop scheduling problem with total flowtime criterion. Unlike the basic ABC algorithm, the proposed DABC algorithm represents a solution as a discrete job permutation. An efficient initialization scheme based on the extended Nawaz-Enscore-Ham heuristic is utilized to produce an initial population with a certain level of quality and diversity. Employed and onlooker bees generate new solutions in their neighborhood, whereas scout bees generate new solutions by performing insert operator and swap operator to the best solution found so far. Moreover, a simple but effective local search is embedded in the algorithm to enhance local exploitation capability. A comparative experiment is carried out with the existing discrete particle swarm optimization, hybrid genetic algorithm, threshold accepting, simulated annealing and ant colony optimization algorithms based on a total of 160 randomly generated instances. The experimental results show that the proposed DABC algorithm is quite effective for the lot-streaming flowshop with total flowtime criterion in terms of searching quality, robustness and effectiveness. This research provides the references to the optimization research on lot-streaming flowshop.

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

    PubMed

    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.

  9. 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

  10. Colony structure and spatial partitioning of cavity dwelling ant species in nuts of eastern US forest floors

    USDA-ARS?s Scientific Manuscript database

    Nut-bearing trees create islands of high efficiency, low cost housing opportunities for ant colonies. Fallen nuts in leaf litter from previous seasons provide ready-made nest sites for cavity dwelling ant species, as well as affording protection from the elements. Suitable nuts for nests require an ...

  11. 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

  12. 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.

  13. Sociogenomics of cooperation and conflict during colony founding in the fire ant Solenopsis invicta.

    PubMed

    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

  14. 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

  15. Experimental manipulation of queen number affects colony sex ratio investment in the highly polygynous ant Formica exsecta

    PubMed Central

    Kümmerli, Rolf; Helms, Ken R; Keller, Laurent

    2005-01-01

    In polygynous (multiple queens per nest) ants, queen dispersal is often limited with young queens being recruited within the parental colony. This mode of dispersal leads to local resource competition between nestmate queens and is frequently associated with extremely male-biased sex ratios at the population level. The queen-replenishment hypothesis has been recently proposed to explain colony sex ratio investment under such conditions. It predicts that colonies containing many queens (subject to high local resource competition) should only produce males, whereas colonies hosting few queens (reduced or no local resource competition) should produce new queens in addition to males. We experimentally tested this hypothesis in the ant Formica exsecta by manipulating queen number over three consecutive years in 120 colonies of a highly polygynous population. Queens were transferred from 40 colonies into another 40 colonies while queen number was not manipulated in 40 control colonies. Genetic analyses of worker offspring revealed that our treatment significantly changed the number of reproductive queens. The sex ratio of colonies was significantly different between treatments in the third breeding season following the experiment initiation. We found that, as predicted by the queen-replenishment hypothesis, queen removal resulted in a significant increase in the proportion of colonies that produced new queens. These results provide the first experimental evidence for the queen-replenishment hypothesis, which might account for sex ratio specialization in many highly polygynous ant species. PMID:16096090

  16. Long-term efficacy of two cricket and two liver diets for rearing laboratory fire ant colonies (Hymenoptera: Formicidae: Solenopsis Invicta)

    USDA-ARS?s Scientific Manuscript database

    Effective diets are necessary for many kinds of laboratory studies of ants. We conducted a year-long study of imported fire ant colonies reared on either chicken liver, beef liver, banded crickets, or domestic crickets all with a sugar water supplement. Fire ant colonies thrived on diets of sugar ...

  17. 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...

  18. Colony-Level Differences in the Scaling Rules Governing Wood Ant Compound Eye Structure

    PubMed Central

    Perl, Craig D.; Niven, Jeremy E.

    2016-01-01

    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. PMID:27068571

  19. Be meek or be bold? A colony-level behavioural syndrome in ants

    PubMed Central

    Bengston, S. E.; Dornhaus, A.

    2014-01-01

    Consistent individual variation in animal behaviour is nearly ubiquitous and has important ecological and evolutionary implications. Additionally, suites of behavioural traits are often correlated, forming behavioural syndromes in both humans and other species. Such syndromes are often described by testing for variation in traits across commonly described dimensions (e.g. aggression and neophobia), independent of whether this variation is ecologically relevant to the focal species. Here, we use a variety of ecologically relevant behavioural traits to test for a colony-level behavioural syndrome in rock ants (Temnothorax rugatulus). Specifically, we combine field and laboratory assays to measure foraging effort, how colonies respond to different types of resources, activity level, response to threat and aggression level. We find evidence for a colony level syndrome that suggests colonies consistently differ in coping style—some are more risk-prone, whereas others are more risk-averse. Additionally, by collecting data across the North American range of this species, we show that environmental variation may affect how different populations maintain consistent variation in colony behaviour. PMID:25100691

  20. Colony structure in a plant-ant: behavioural, chemical and genetic study of polydomy in Cataulacus mckeyi (Myrmicinae).

    PubMed

    Debout, Gabriel; Provost, Erick; Renucci, Marielle; Tirard, Alain; Schatz, Bertrand; McKey, Doyle

    2003-10-01

    Social organisation of colonies of obligate plant-ants can affect their interaction with myrmecophyte hosts and with other ants competing for the resources they offer. An important parameter of social organisation is whether nest sites of a colony include one or several host individuals. We determined colony boundaries in a plant-ant associated with the rainforest understorey tree Leonardoxa africana subsp. africana, found in coastal forests of Cameroon (Central Africa). This myrmecophyte is strictly associated with two ants, Petalomyrmex phylax and Cataulacus mckeyi. Plants provide food and nesting sites for P. phylax, which protects young leaves against insect herbivores. This mutualism is often parasitised by C. mckeyi, which uses but does not protect the host. The presence of C. mckeyi on a tree excludes the mutualistic ant. Because Petalomyrmex-occupied trees are better protected, their growth and survival are superior to those of Cataulacus-occupied trees, giving P. phylax an advantage in occupation of nest sites. C. mckeyi often colonises trees that have lost their initial associate P. phylax, as a result of injury to the tree caused by disturbance. Polydomy may allow C. mckeyi to occupy small clumps of trees, without the necessity of claustral colony foundation in each tree. Investigating both the proximate (behavioural repertoire, colony odour) and the ultimate factors (genetic structure) that may influence colony closure, we precisely defined colony boundaries. We show that colonies of C. mckeyi are monogynous and facultatively polydomous, i.e. a colony occupies one to several Leonardoxa trees. Workers do not produce males. Thus, the hypothesis that polydomy allows workers in queenless nests to evade queen control for their reproduction is not supported in this instance. This particular colony structure may confer on C. mckeyi an advantage in short-distance dispersal, and this could help explain its persistence within the dynamic Leonardoxa system.

  1. Flood risk zoning using a rule mining based on ant colony algorithm

    NASA Astrophysics Data System (ADS)

    Lai, Chengguang; Shao, Quanxi; Chen, Xiaohong; Wang, Zhaoli; Zhou, Xiaowen; Yang, Bing; Zhang, Lilan

    2016-11-01

    Risk assessment is a preliminary step in flood management and mitigation, and risk zoning provides a quantitative measure of flood risk. The difficulty in flood risk zoning is to deal with the complicated non-linear relationship among indices and risk levels. To solve this problem, the ant colony algorithm based on rule mining (Ant-Miner) is promoted in this paper to map the regional flood risk at grid scale. For the case study in the Dongjiang River Basin in Southern China, 11 and 14 indices (without and with the socio-economic indices considered) are respectively chosen to construct the zoning model based on Ant-Miner. The results show that Ant-Miner exhibits higher accuracy and more simple rules that can be used to generate flood risk zoning map quickly and easily than decision tree method (DT); compared to random forest (RF) and fuzzy comprehensive evaluation (FCE), Ant-Miner has significant advantages both in implementation step-reducing and computing time-saving. Although the comprehensive measure and natural hazard measure of flood risk distributed similarly over the entire region, the former one which considered the socio-economic indices is more reasonable in term of real impact to natural and socio-economy. The areas with high-risk level obtained in this paper matched well with the integrated risk zoning map and the inundation areas of historical floods, suggesting that the proposed Ant-Miner method is capable of zoning the flood risk at grid scale. This study shows the potential to provide a novel and successful approach to flood risk zoning. Evaluation results provide a reference for flood risk management, prevention, and reduction of natural disasters in the study basin.

  2. Lévy flight artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Sharma, Harish; Bansal, Jagdish Chand; Arya, K. V.; Yang, Xin-She

    2016-08-01

    Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.

  3. Artificial bee colony algorithm for single-trial electroencephalogram analysis.

    PubMed

    Hsu, Wei-Yen; Hu, Ya-Ping

    2015-04-01

    In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise removal, feature extraction, feature selection, and feature classification. First, the artifacts and background noise are removed automatically by means of independent component analysis and surface Laplacian filter, respectively. Several potential features, such as band power, autoregressive model, and coherence and phase-locking value, are then extracted for subsequent classification. Next, artificial bee colony (ABC) algorithm is used to select features from the aforementioned feature combination. Finally, selected subfeatures are classified by support vector machine. Comparing with and without artifact removal and feature selection, using a genetic algorithm on single-trial EEG data for 6 subjects, the results indicate that the proposed system is promising and suitable for brain-computer interface applications. © EEG and Clinical Neuroscience Society (ECNS) 2014.

  4. 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.

  5. 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).

  6. 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

  7. 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.

  8. Pharaoh ant (Hymenoptera: Formicidae) colony development after consumption of pyriproxyfen baits.

    PubMed

    Vail, K M; Williams, D F

    1995-12-01

    Pharaoh ant, Monomorium pharaonis (L.), colonies were effectively controlled following ingestion of pyriproxyfen formulated in peanut butter oil. Pyriproxyfen, a juvenile hormone analog, reduced egg production in the queens, decreased the amount of brood due to delayed death in the eggs and larvae, caused death of pupae about 3 wk after treatment, and decreased the number of workers due to attrition and toxic effects. Queens, which continued to produce a small amount of eggs, eventually died. Queen death may have been caused by lack of workers required to tend them, old age or toxic effects. At concentrations of 0.25, 0.5 and 1%, pyriproxyfen was more effective than the once commercially available bait, Pharorid (methoprene) for the control of the Pharaoh ant.

  9. Colony-level behavioral 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

    2017-09-13

    Among social insects, colony-level variation is likely to be widespread and have significant ecological consequences. Very few studies, however, have documented how genetic factors relate to behavior 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 behavior. 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 behavioral 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 versus working in the interior of the nest). These results provide insight into the genetic and physiological processes underlying collective differences in social behavior. Quantifying variation in expression of the foraging gene may provide an important tool for understanding and predicting the ecological consequences of colony-level behavioral variation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  10. 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...

  11. Social Transfer of Pathogenic Fungus Promotes Active Immunisation in Ant Colonies

    PubMed Central

    Konrad, Matthias; Vyleta, Meghan L.; Theis, Fabian J.; Stock, Miriam; Tragust, Simon; Klatt, Martina; Drescher, Verena; Marr, Carsten; Ugelvig, Line V.; Cremer, Sylvia

    2012-01-01

    Due to the omnipresent risk of epidemics, insect societies have evolved sophisticated disease defences at the individual and colony level. An intriguing yet little understood phenomenon is that social contact to pathogen-exposed individuals reduces susceptibility of previously naive nestmates to this pathogen. We tested whether such social immunisation in Lasius ants against the entomopathogenic fungus Metarhizium anisopliae is based on active upregulation of the immune system of nestmates following contact to an infectious individual or passive protection via transfer of immune effectors among group members—that is, active versus passive immunisation. We found no evidence for involvement of passive immunisation via transfer of antimicrobials among colony members. Instead, intensive allogrooming behaviour between naive and pathogen-exposed ants before fungal conidia firmly attached to their cuticle suggested passage of the pathogen from the exposed individuals to their nestmates. By tracing fluorescence-labelled conidia we indeed detected frequent pathogen transfer to the nestmates, where they caused low-level infections as revealed by growth of small numbers of fungal colony forming units from their dissected body content. These infections rarely led to death, but instead promoted an enhanced ability to inhibit fungal growth and an active upregulation of immune genes involved in antifungal defences (defensin and prophenoloxidase, PPO). Contrarily, there was no upregulation of the gene cathepsin L, which is associated with antibacterial and antiviral defences, and we found no increased antibacterial activity of nestmates of fungus-exposed ants. This indicates that social immunisation after fungal exposure is specific, similar to recent findings for individual-level immune priming in invertebrates. Epidemiological modeling further suggests that active social immunisation is adaptive, as it leads to faster elimination of the disease and lower death rates than

  12. 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.

  13. 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

  14. An Approach to Feature Selection Based on Ant Colony Optimization and Rough Set

    NASA Astrophysics Data System (ADS)

    Wu, Junyun; Qiu, Taorong; Wang, Lu; Huang, Haiquan

    Feature selection plays an important role in many fields. This paper proposes a method for feature selection which combined the rough set method and ant colony optimization algorithm. The algorithm used the attribute dependence and the attribute importance as the inspiration factor which applied to the transfer rules. For further, the quality of classification based on rough set method and the length of the feature subset were used to build the pheromone update strategy. Through the test of data set, results show that the proposed method is feasible.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. A colony-level response to disease control in a leaf-cutting ant.

    PubMed

    Hart, Adam G; Bot, A N M; Brown, Mark J F

    2002-06-01

    Parasites and pathogens often impose significant costs on their hosts. This is particularly true for social organisms, where the genetic structure of groups and the accumulation of contaminated waste facilitate disease transmission. In response, hosts have evolved many mechanisms of defence against parasites. Here we present evidence that Atta colombica, a leaf-cutting ant, may combat Escovopsis, a dangerous parasite of Atta's garden fungus, through a colony-level behavioural response. In A. colombica, garden waste is removed from within the colony and transported to the midden--an external waste dump--where it is processed by a group of midden workers. We found that colonies infected with Escovopsis have higher numbers of workers on the midden, where Escovopsis is deposited. Further, midden workers are highly effective in dispersing newly deposited waste away from the dumping site. Thus, the colony-level task allocation strategies of the Atta superorganism may change in response to the threat of disease to a third, essential party.

  20. Incomplete homogenization of chemical recognition labels between Formica sanguinea and Formica rufa ants (Hymenoptera: Formicidae) living in a mixed colony.

    PubMed

    Włodarczyk, Tomasz; Szczepaniak, Lech

    2014-01-01

    Formica sanguinea Latreille (Hymenoptera: Formicidae) is a slave-making species, i.e., it raids colonies of host species and pillages pupae, which are taken to develop into adult workers in a parasite colony. However, it has been unclear if the coexistence of F. sanguinea with slave workers requires uniformity of cuticular hydrocarbons (CHCs), among which those other than n-alkanes are believed to be the principal nestmate recognition cues utilized by ants. In this study, a mixed colony (MC) of F. sanguinea and Formica rufa L. as a slave species was used to test the hypothesis that CHCs are exchanged between the species. Chemical analysis of hexane extracts from ants' body surfaces provided evidence for interspecific exchange of alkenes and methyl-branched alkanes. This result was confirmed by behavioral tests during which ants exhibited hostility toward conspecific individuals from the MC but not toward ones from homospecific colonies of their own species. However, it seems that species-specific differences in chemical recognition labels were not eliminated completely because ants from the MC were treated differently depending on whether they were con- or allospecific to the individuals whose behavioral reactions were tested. These findings are discussed in the context of mechanisms of colony's odor formation and effective integration of slaves into parasite colony. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

  1. 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

  2. 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.

  3. 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

  4. An improved ant colony optimization approach for optimization of process planning.

    PubMed

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

  5. 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.

  6. 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.

  7. 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

  8. Effects of a juvenile hormone analogue pyriproxyfen on monogynous and polygynous colonies of the Pharaoh ant Monomorium pharaonis (Hymenoptera: Formicidae).

    PubMed

    Tay, J W; Lee, C Y

    2015-09-01

    To evaluate the effects of the juvenile hormone analogue pyriproxyfen on colonies of the Pharaoh ant Monomorium pharaonis (L.), peanut oil containing different concentrations (0.3, 0.6, or 0.9%) of pyriproxyfen was fed to monogynous (1 queen, 500 workers, and 0.1 g of brood) and polygynous (8 queens, 50 workers, and 0.1 g of brood) laboratory colonies of M. pharaonis. Due to its delayed activity, pyriproxyfen at all concentrations resulted in colony elimination. Significant reductions in brood volume were recorded at weeks 3 - 6, and complete brood mortality was observed at week 8 in all treated colonies. Brood mortality was attributed to the disruption of brood development and cessation of egg production by queens. All polygynous colonies exhibited significant reduction in the number of queens present at week 10 compared to week 1. Number of workers was significantly lower in all treated colonies compared to control colonies at week 8 due to old-age attrition of the workers without replacement. At least 98.67 ± 1.33% of workers were dead at week 10 in all treated colonies. Thus, treatment with slow acting pyriproxyfen at concentrations of 0.3 - 0.9% is an effective strategy for eliminating Pharaoh ant colonies.

  9. A New Method for Distinguishing Colony Social Forms of the Fire Ant, Solenopsis invicta

    PubMed Central

    Shoemaker, DeWayne; Ascunce, Marina S.

    2010-01-01

    Two distinct forms of colony social organization occur in the fire ant Solenopsis invicta Buren (Hymenoptera: Formicidae): 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 associated with genetic variation at a single gene (Gp-9) whereby all polygyne queens possess at least one b-like allele, while monogyne queens lack such b-like alleles and instead harbor B-like alleles only. Further, a recent study of native populations revealed that all b-like alleles in polygyne queens consistently contain three diagnostic amino acid residues: possession of only one or two of these critical residues is not sufficient for polygyny. TaqMan® allelic discrimination assays were developed to survey the variable nucleotide sites associated with these three critical amino acid residues. The assays were validated by surveying nests of known social form from the species' introduced in the USA and from native South American ranges, as well as by comparing the results to Gp-9 sequence data from a subset of samples. The results demonstrate these new molecular assays consistently and accurately identify the variable nucleotides at all three sites characteristic of the B-like and b-like Gp-9 allele classes, allowing for accurate determination of colony social form. PMID:20673191

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

    PubMed

    Shoemaker, DeWayne; Ascunce, Marina S

    2010-01-01

    Two distinct forms of colony social organization occur in the fire ant Solenopsis invicta Buren (Hymenoptera: Formicidae): 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 associated with genetic variation at a single gene (Gp-9) whereby all polygyne queens possess at least one b-like allele, while monogyne queens lack such b-like alleles and instead harbor B-like alleles only. Further, a recent study of native populations revealed that all b-like alleles in polygyne queens consistently contain three diagnostic amino acid residues: possession of only one or two of these critical residues is not sufficient for polygyny. TaqMan allelic discrimination assays were developed to survey the variable nucleotide sites associated with these three critical amino acid residues. The assays were validated by surveying nests of known social form from the species' introduced in the USA and from native South American ranges, as well as by comparing the results to Gp-9 sequence data from a subset of samples. The results demonstrate these new molecular assays consistently and accurately identify the variable nucleotides at all three sites characteristic of the B-like and b-like Gp-9 allele classes, allowing for accurate determination of colony social form.

  11. Friends and Foes from an Ant Brain's Point of View – Neuronal Correlates of Colony Odors in a Social Insect

    PubMed Central

    Brandstaetter, Andreas Simon; Rössler, Wolfgang; Kleineidam, Christoph Johannes

    2011-01-01

    Background Successful cooperation depends on reliable identification of friends and foes. Social insects discriminate colony members (nestmates/friends) from foreign workers (non-nestmates/foes) by colony-specific, multi-component colony odors. Traditionally, complex processing in the brain has been regarded as crucial for colony recognition. Odor information is represented as spatial patterns of activity and processed in the primary olfactory neuropile, the antennal lobe (AL) of insects, which is analogous to the vertebrate olfactory bulb. Correlative evidence indicates that the spatial activity patterns reflect odor-quality, i.e., how an odor is perceived. For colony odors, alternatively, a sensory filter in the peripheral nervous system was suggested, causing specific anosmia to nestmate colony odors. Here, we investigate neuronal correlates of colony odors in the brain of a social insect to directly test whether they are anosmic to nestmate colony odors and whether spatial activity patterns in the AL can predict how odor qualities like “friend” and “foe” are attributed to colony odors. Methodology/Principal Findings Using ant dummies that mimic natural conditions, we presented colony odors and investigated their neuronal representation in the ant Camponotus floridanus. Nestmate and non-nestmate colony odors elicited neuronal activity: In the periphery, we recorded sensory responses of olfactory receptor neurons (electroantennography), and in the brain, we measured colony odor specific spatial activity patterns in the AL (calcium imaging). Surprisingly, upon repeated stimulation with the same colony odor, spatial activity patterns were variable, and as variable as activity patterns elicited by different colony odors. Conclusions Ants are not anosmic to nestmate colony odors. However, spatial activity patterns in the AL alone do not provide sufficient information for colony odor discrimination and this finding challenges the current notion of how odor

  12. Combining support vector regression and ant colony optimization to reduce NOx emissions in coal-fired utility boilers

    SciTech Connect

    Ligang Zheng; Hao Zhou; Chunlin Wang; Kefa Cen

    2008-03-15

    Combustion optimization has recently demonstrated its potential to reduce NOx emissions in high capacity coal-fired utility boilers. In the present study, support vector regression (SVR), as well as artificial neural networks (ANN), was proposed to model the relationship between NOx emissions and operating parameters of a 300 MW coal-fired utility boiler. The predicted NOx emissions from the SVR model, by comparing with that of the ANN-based model, showed better agreement with the values obtained in the experimental tests on this boiler operated at different loads and various other operating parameters. The mean modeling error and the correlation factor were 1.58% and 0.94, respectively. Then, the combination of the SVR model with ant colony optimization (ACO) to reduce NOx emissions was presented in detail. The experimental results showed that the proposed approach can effectively reduce NOx emissions from the coal-fired utility boiler by about 18.69% (65 ppm). A time period of less than 6 min was required for NOx emissions modeling, and 2 min was required for a run of optimization under a PC system. The computing times are suitable for the online application of the proposed method to actual power plants. 37 refs., 8 figs., 3 tabs.

  13. Benefits of dispersed central-place foraging: an individual-based model of a polydomous ant colony.

    PubMed

    Schmolke, Amelie

    2009-06-01

    Colonies of many ant species are not confined to a single nest but inhabit several dispersed nests, a colony organization referred to as polydomy. The benefits of polydomy are not well understood. It has been proposed that increased foraging efficiency promotes polydomy. In a spatially explicit individual-based model, I compare the foraging success of monodomous and polydomous colonies in environments with varying food distributions. Multiple nests increased the colony's foraging success if food sources were randomly scattered in the environment. Monodomous and polydomous colonies did not differ in foraging success if food sources were clustered in one or three locations. These results support the hypothesis that foraging success serves as a driver for polydomous colony organization. Because transport may occur between the dispersed nests of a polydomous colony, I tested the efficiency of a simple mechanism of food exchange between nests. This mechanism, as introduced previously in the literature, proves insufficient to equalize the level of food between nests. While the importance of transport between nests remains unclear, the model results indicate that polydomy may increase the foraging success of ant colonies and that this effect may be robust across a range of food distributions.

  14. Ant colony optimization with selective evaluation for feature selection in character recognition

    NASA Astrophysics Data System (ADS)

    Oh, Il-Seok; Lee, Jin-Seon

    2010-01-01

    This paper analyzes the size characteristics of character recognition domain with the aim of developing a feature selection algorithm adequate for the domain. Based on the results, we further analyze the timing requirements of three popular feature selection algorithms, greedy algorithm, genetic algorithm, and ant colony optimization. For a rigorous timing analysis, we adopt the concept of atomic operation. We propose a novel scheme called selective evaluation to improve convergence of ACO. The scheme cut down the computational load by excluding the evaluation of unnecessary or less promising candidate solutions. The scheme is realizable in ACO due to the valuable information, pheromone trail which helps identify those solutions. Experimental results showed that the ACO with selective evaluation was promising both in timing requirement and recognition performance.

  15. A convenient and robust edge detection method based on ant colony optimization

    NASA Astrophysics Data System (ADS)

    Liu, Xiaochen; Fang, Suping

    2015-10-01

    Edge detection is usually used as a preprocessing operation in many machine vision industrial applications. Recently, ant colony optimization (ACO) as a relatively new meta-heuristic approach has been used to tackle the edge detection problem. In this work, a convenient and robust method for edge detection based on ACO is proposed, which employs a new heuristic function, adopts a user-defined threshold in pheromone update process and provides a group of suitable parameter values. Experimental results clearly demonstrated the effectiveness of the proposed method, and at the same time, in the presence of noise, the proposed approach outperforms other two ACO-based edge detection techniques and four conventional edge detectors.

  16. A Novel Method of Failure Sample Selection for Electrical Systems Using Ant Colony Optimization

    PubMed Central

    Tian, Shulin; Yang, Chenglin; Liu, Cheng

    2016-01-01

    The influence of failure propagation is ignored in failure sample selection based on traditional testability demonstration experiment method. Traditional failure sample selection generally causes the omission of some failures during the selection and this phenomenon could lead to some fearful risks of usage because these failures will lead to serious propagation failures. This paper proposes a new failure sample selection method to solve the problem. First, the method uses a directed graph and ant colony optimization (ACO) to obtain a subsequent failure propagation set (SFPS) based on failure propagation model and then we propose a new failure sample selection method on the basis of the number of SFPS. Compared with traditional sampling plan, this method is able to improve the coverage of testing failure samples, increase the capacity of diagnosis, and decrease the risk of using. PMID:27738424

  17. Designing Daily Patrol Routes for Policing Based on ANT Colony Algorithm

    NASA Astrophysics Data System (ADS)

    Chen, H.; Cheng, T.; Wise, S.

    2015-07-01

    In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone) is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy.

  18. 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.

  19. Virgin ant queens mate with their own sons to avoid failure at colony foundation

    NASA Astrophysics Data System (ADS)

    Schmidt, Christine Vanessa; Frohschammer, Sabine; Schrempf, Alexandra; Heinze, Jürgen

    2014-01-01

    Mother-son mating (oedipal mating) is practically non-existent in social Hymenoptera, as queens typically avoid inbreeding, mate only early in life and do not mate again after having begun to lay eggs. In the ant genus Cardiocondyla mating occurs among sib in the natal nests. Sex ratios are extremely female-biased and young queens face the risk of remaining without mating partners. Here, we show that virgin queens of Cardiocondyla argyrotricha produce sons from their own unfertilized eggs and later mate with them to produce female offspring from fertilized eggs. Oedipal mating may allow C. argyrotricha queens to found new colonies when no mating partners are available and thus maintains their unusual life history combining monogyny, mating in the nest, and low male production. Our result indicates that a trait that sporadically occurs in solitary haplodiploid animals may evolve also in social Hymenoptera under appropriate ecological and social conditions.

  20. 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.

  1. Strength in numbers: large and permanent colonies have higher queen oviposition rates in the invasive Argentine ant (Linepithema humile, Mayr).

    PubMed

    Abril, Sílvia; Gómez, Crisanto

    2014-03-01

    Polydomy associated with unicoloniality is a common trait of invasive species. In the invasive Argentine ant, colonies are seasonally polydomous. Most follow a seasonal fission-fussion pattern: they disperse in the spring and summer and aggregate in the fall and winter. However, a small proportion of colonies do not migrate; instead, they inhabit permanent nesting sites. These colonies are large and highly polydomous. The aim of this study was to (1) search for differences in the fecundity of queens between mother colonies (large and permanent) and satellite colonies (small and temporal), (2) determine if queens in mother and satellite colonies have different diets to clarify if colony size influences social organization and queen feeding, and (3) examine if colony location relative to the invasion front results in differences in the queen's diet. Our results indicate that queens from mother nests are more fertile than queens from satellite nests and that colony location does not affect queen oviposition rate. Ovarian dissections suggest that differences in ovarian morphology are not responsible for the higher queen oviposition rate in mother vs. satellite nests, since there were no differences in the number and length of ovarioles in queens from the two types of colonies. In contrast, the higher δ(15)N values of queens from mother nests imply that greater carnivorous source intake accounts for the higher oviposition rates. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Strict monandry in the ponerine army ant genus Simopelta suggests that colony size and complexity drive mating system evolution in social insects.

    PubMed

    Kronauer, Daniel J C; O'Donnell, Sean; Boomsma, Jacobus J; Pierce, Naomi E

    2011-01-01

    Altruism in social insects has evolved between closely related full-siblings. It is therefore of considerable interest why some groups have secondarily evolved low within-colony relatedness, which in turn affects the relatedness incentives of within-colony cooperation and conflict. The highest queen mating frequencies, and therefore among the lowest degrees of colony relatedness, occur in Apis honeybees and army ants of the subfamilies Aenictinae, Ecitoninae, and Dorylinae, suggesting that common life history features such as reproduction by colony fission and male biased numerical sex-ratios have convergently shaped these mating systems. Here we show that ponerine army ants of the genus Simopelta, which are distantly related but similar in general biology to other army ants, have strictly monandrous queens. Preliminary data suggest that workers reproduce in queenright colonies, which is in sharp contrast to other army ants. We hypothesize that differences in mature colony size and social complexity may explain these striking discrepancies. © 2010 Blackwell Publishing Ltd.

  3. A Novel Artificial Bee Colony Based Clustering Algorithm for Categorical Data

    PubMed Central

    2015-01-01

    Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data. PMID:25993469

  4. 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

  5. A queen pheromone induces workers to kill sexual larvae in colonies of the red imported fire ant (Solenopsis invicta)

    NASA Astrophysics Data System (ADS)

    Klobuchar, Emily; Deslippe, Richard

    2002-05-01

    We conducted five bioassays to study how queens control the execution of sexual larvae by workers in colonies of the red imported fire ant, Solenopsis invicta. In each assay, subset colonies were made from many large polygyne colonies, and the 20 sexual larvae they contained were monitored over time. Sexual larvae mostly survived in queenless colonies, but were mostly killed in colonies with a single dealated queen, regardless of whether or not the queen was fertilized. The larvae were also killed when fresh corpses of queens were added to queenless colonies. Whereas acetone extracts of queens did not produce a significant increase in killings, extracts in buffered saline induced workers to execute most sexual larvae, indicating successful extraction of an execution pheromone. We identified the probable storage location of the chemical as the poison sac, and found both fresh (1 day) and old (21 day) extracts of poison sacs to be equally effective in inducing executions. The pheromone is stable at room temperature, perhaps because venom alkaloids also present in the extracts keep the pheromone from degrading. It is apparently either proteinaceous or associated with a proteinaceous molecule, a novel finding, as no queen pheromone of a proteinaceous nature has been previously demonstrated in ants.

  6. Routing and spectrum assignment based on ant colony optimization of minimum consecutiveness loss in elastic optical networks

    NASA Astrophysics Data System (ADS)

    Wang, Fu; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Tian, Qinghua; Zhang, Qi; Rao, Lan; Tian, Feng; Luo, Biao; Liu, Yingjun; Tang, Bao

    2016-10-01

    Elastic Optical Networks are considered to be a promising technology for future high-speed network. In this paper, we propose a RSA algorithm based on the ant colony optimization of minimum consecutiveness loss (ACO-MCL). Based on the effect of the spectrum consecutiveness loss on the pheromone in the ant colony optimization, the path and spectrum of the minimal impact on the network are selected for the service request. When an ant arrives at the destination node from the source node along a path, we assume that this path is selected for the request. We calculate the consecutiveness loss of candidate-neighbor link pairs along this path after the routing and spectrum assignment. Then, the networks update the pheromone according to the value of the consecutiveness loss. We save the path with the smallest value. After multiple iterations of the ant colony optimization, the final selection of the path is assigned for the request. The algorithms are simulated in different networks. The results show that ACO-MCL algorithm performs better in blocking probability and spectrum efficiency than other algorithms. Moreover, the ACO-MCL algorithm can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness. Compared with other algorithms, the ACO-MCL algorithm can reduce the blocking rate by at least 5.9% in heavy load.

  7. The interplay between maze complexity, colony size, learning and memory in ants while solving a maze: A test at the colony level.

    PubMed

    Saar, Maya; Gilad, Tomer; Kilon-Kallner, Tal; Rosenfeld, Adar; Subach, Aziz; Scharf, Inon

    2017-01-01

    Central-place foragers need to explore their immediate habitat in order to reach food. We let colonies of the individually foraging desert ant Cataglyphis niger search for a food reward in a maze. We did so for three tests per day over two successive days and an additional test after a time interval of 4-20 days (seven tests in total). We examined whether the colonies reached the food reward faster, consumed more food and changed the number of workers searching over time, within and between days. Colonies' food-discovery time shortened within and between days, indicating that some workers learnt and became more efficient in moving through the maze. Such workers, however, also forgot and deteriorated in their food-discovery time, leveling off back to initial performance after about two weeks. We used mazes of increasing complexity levels, differing in the potential number of wrong turns. The number of workers searching increased with colony size. Food-discovery time also increased with colony size in complex mazes but not in simple ones, perhaps due to the more frequent interactions among workers in large colonies having to move through narrow routes. Finally, the motivation to solve the maze was probably not only the food reward, because food consumption did not change over time.

  8. Identifying robustness in the regulation of collective foraging of ant colonies using an interaction-based model with backward bifurcation.

    PubMed

    Udiani, Oyita; Pinter-Wollman, Noa; Kang, Yun

    2015-02-21

    Collective behaviors in social insect societies often emerge from simple local rules. However, little is known about how these behaviors are dynamically regulated in response to environmental changes. Here, we use a compartmental modeling approach to identify factors that allow harvester ant colonies to regulate collective foraging activity in response to their environment. We propose a set of differential equations describing the dynamics of: (1) available foragers inside the nest, (2) active foragers outside the nest, and (3) successful returning foragers, to understand how colony-specific parameters, such as baseline number of foragers, interactions among foragers, food discovery rates, successful forager return rates, and foraging duration might influence collective foraging dynamics, while maintaining functional robustness to perturbations. Our analysis indicates that the model can undergo a forward (transcritical) bifurcation or a backward bifurcation depending on colony-specific parameters. In the former case, foraging activity persists when the average number of recruits per successful returning forager is larger than one. In the latter case, the backward bifurcation creates a region of bistability in which the size and fate of foraging activity depends on the distribution of the foraging workforce among the model's compartments. We validate the model with experimental data from harvester ants (Pogonomyrmex barbatus) and perform sensitivity analysis. Our model provides insights on how simple, local interactions can achieve an emergent and robust regulatory system of collective foraging activity in ant colonies.

  9. Predation of artificial ground nests on white-tailed prairie dog colonies

    USGS Publications Warehouse

    Baker, B.W.; Stanley, T.R.; Sedgwick, J.A.

    1999-01-01

    Prairie dog (Cynomys spp.) colonies are unique to prairie and shrub-steppe landscapes. However, widespread eradication, habitat loss, and sylvatic plague (Yersinia pestis) have reduced their numbers by 98% since historical times. Birds associated with prairie dogs also are declining. Potential nest predators, such as coyotes (Canis latrans), swift foxes (Vulpes velox), and badgers (Taxidea taxus), may be attracted to colonies where a high concentration of prairie dogs serve as available prey. Increased abundance of small mammals, including prairie dogs, also may increase the risk of predation for birds nesting on colonies. Finally, because grazing by prairie dogs may decrease vegetation height and canopy cover, bird nests may be easier for predators to locate. In this study, we placed 1,444 artificial ground nests on and off 74 white-tailed prairie dog (C. leucurus) colonies to test the hypothesis that nest predation rates are higher on colonies than at nearby off sites (i.e., uncolonized habitat). We sampled colonies from 27 May to 16 July 1997 at the following 3 complexes: Coyote Basin, Utah and Colorado; Moxa Arch, Wyoming; and Shirley Basin, Wyoming. Differences in daily predation rates between colonies and paired off sites averaged 1.0% (P = 0.060). When converted to a typical 14-day incubation period, predation rates averaged 14% higher on colonies (57.7 ?? 2.7%; ?? ?? SE) than at off sites (50.4 ?? 3.1%). Comparisons of habitat variables on colonies to off sites showed percent canopy cover of vegetation was similar (P = 0.114), percent bare ground was higher on colonies (P 0.288). Although we found the risk of nest predation was higher on white-tailed prairie dog colonies than at off sites, fitness of birds nesting on colonies might depend on other factors that influence foraging success, reproductive success, or nestling survival.

  10. 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.

  11. 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.

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

    PubMed

    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.

  13. 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.

  14. 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.

  15. Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization.

    PubMed

    Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri

    2013-09-01

    Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors.

  16. Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization

    PubMed Central

    Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri

    2013-01-01

    Abstract Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871

  17. 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

  18. A Pareto Ant Colony Algorithm Applied to the Class Integration and Test Order Problem

    NASA Astrophysics Data System (ADS)

    da Veiga Cabral, Rafael; Pozo, Aurora; Vergilio, Silvia Regina

    In the context of Object-Oriented software, many works have investigated the Class Integration and Test Order (CITO) problem, proposing solutions to determine test orders for the integration test of the program classes. The existing approaches based on graphs can generate solutions that are sub-optimal, and do not consider the different factors and measures that can affect the stubbing process. To overcome this limitation, solutions based on Genetic Algorithms (GA) have presented promising results. However, the determination of a cost function, which is able to generate the best solutions, is not always a trivial task, mainly for complex systems with a great number of measures. Therefore, we introduce, in this paper, a multi-objective optimization approach to better represent the CITO problem. The approach generates a set of good solutions that achieve a balanced compromise between the different measures (objectives). It was implemented by a Pareto Ant Colony (P-ACO) algorithm, which is described in detail. The algorithm was used in a set of real programs and the obtained results are compared to the GA results. The results allow discussing the difference between single and multi-objective approaches especially for complex systems with a greater number of dependencies among the classes.

  19. A modified ant colony optimization to solve multi products inventory routing problem

    NASA Astrophysics Data System (ADS)

    Wong, Lily; Moin, Noor Hasnah

    2014-07-01

    This study considers a one-to-many inventory routing problem (IRP) network consisting of a manufacturer that produces multi products to be transported to many geographically dispersed customers. We consider a finite horizon where a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, transport products from the warehouse to meet the demand specified by the customers in each period. The demand for each product is deterministic and time varying and each customer requests a distinct product. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount on inventory and to construct a delivery schedule that minimizes both the total transportation and inventory holding costs 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 solution) for each problem considered. We propose a modified ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. ACO performs better on large instances compared to the upper bound.

  20. A multiple classifier system based on Ant-Colony Optimization for Hyperspectral image classification

    NASA Astrophysics Data System (ADS)

    Tang, Ke; Xie, Li; Li, Guangyao

    2017-01-01

    Hyperspectral images which hold a large quantity of land information enables image classification. Traditional classification methods usually works on multispectral images. However, the high dimensionality in feature space influences the accuracy while using these classification algorithms, such as statistical classifiers or decision trees. This paper proposes a multiple classifier system (MCS) based on ant colony optimization (ACO) algorithm to improve the classification ability. ACO method has been implemented on multispectral images in researches, but seldom to hyperspectral images. In order to overcome the limitation of ACO method on dealing with high dimensionality, MCS is introduced to combine the outputs of each single ACO classifier based on the credibility of rules. Mutual information is applied to discretizing features from the data set and provides the criterion of band selection and band grouping algorithms. The performance of the proposed method is validated with ROSIS Pavia data set, and compared to k-nearest neighbour (KNN) algorithm. Experimental results prove that the proposed method is feasible to classify hyperspectral images.

  1. 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.

  2. 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

  3. A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks

    PubMed Central

    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. PMID:22399890

  4. Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

    PubMed Central

    Ozekes, Serhat; Gultekin, Selahattin; Tarhan, Nevzat

    2014-01-01

    Objective Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new approach for feature subset selection. Methods Feature selection process using ant colony optimization (ACO) for 6 channel pre-treatment electroencephalogram (EEG) data from theta and delta frequency bands is combined with back propagation neural network (BPNN) classification method for 147 major depressive disorder (MDD) subjects. Results BPNN classified R subjects with 91.83% overall accuracy and 95.55% subjects detection sensitivity. Area under ROC curve (AUC) value after feature selection increased from 0.8531 to 0.911. The features selected by the optimization algorithm were Fp1, Fp2, F7, F8, F3 for theta frequency band and eliminated 7 features from 12 to 5 feature subset. Conclusion ACO feature selection algorithm improves the classification accuracy of BPNN. Using other feature selection algorithms or classifiers to compare the performance for each approach is important to underline the validity and versatility of the designed combination. PMID:25110496

  5. 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.

  6. A Star Recognition Method Based on the Adaptive Ant Colony Algorithm for Star Sensors

    PubMed Central

    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. PMID:22294908

  7. 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

  8. 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

  9. Semivariogram Estimation Using Ant Colony Optimization and Ensemble Kriging Accounting for Parameter Uncertainty

    NASA Astrophysics Data System (ADS)

    Cardiff, M. A.; Kitanidis, P. K.

    2005-12-01

    In this presentation we revisit the problem of semivariogram estimation and present a modular, reusable, and encapsulated set of MATLAB programs that use a hybrid Ant Colony Optimization (ACO) heuristic to solve the "optimal fit" problem. Though the ACO heuristic involves a stochastic component, advantages of the heuristic over traditional gradient-search methods, like the Gauss-Newton method, include the ability to estimate model semivariogram parameters accurately without initial guesses input by the user. The ACO heuristic is also superiorly suited for strongly nonlinear optimization over spaces that may contain several local minima. The presentation will focus on the application of ACO to existing weighted least squares and restricted maximum likelihood estimation methods with a comparison of results. The presentation will also discuss parameter uncertainty, particularly in the context of restricted maximum likelihood and Bayesian methods. We compare the local linearized parameter estimates (or Cramer-Rao lower bounds) with modern Monte Carlo methods, such as acceptance-rejection. Finally, we present ensemble kriging in which conditional realizations are generated in a way that uncertainty in semi-variogram parameters is fully accounted for. Results for a variety of sample problems will be presented along with a discussion of solution accuracy and computational efficiency.

  10. Applying genetic programming and ant colony optimisation to improve the geometric design of a reflector

    NASA Astrophysics Data System (ADS)

    Hsu, Chih-Ming

    2012-05-01

    The lighting performance of an LED (light-emitting diode) flash is significantly influenced by the geometric form of a reflector. Previously, design engineers have usually determined the geometric design of a reflector according to the principles of optics and their own experience. Some real reflectors have then been created to verify the feasibility and performance of a certain geometric design. This, however, is a costly and time-consuming procedure. Furthermore, the geometric design of a reflector cannot be proven to be actually optimal. This study proposes a systematic approach based on genetic programming (GP) and ant colony optimisation (ACO), called the GP-ACO procedure, to improve the geometric design of a reflector. A case study is used to demonstrate the feasibility and effectiveness of the proposed optimisation procedure. The results show that all the crucial quality characteristics of an LED flash fulfil the required specifications; thus, the optimal geometric parameter settings of the reflector obtained can be directly applied to mass production. Consequently, the proposed GP-ACO procedure can be considered an effective method for resolving general multi-response parameter design problems.

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

    SciTech Connect

    Ferrandi, Fabrizio; Lanzi, Pier Luca; Pilato, Christian; Sciuto, Donatella; Tumeo, Antonino

    2013-06-24

    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 the 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.

  12. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    NASA Astrophysics Data System (ADS)

    García-Pareja, S.; Vilches, M.; Lallena, A. M.

    2007-09-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the "hot" regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  13. A multiuser detector based on artificial bee colony algorithm for DS-UWB systems.

    PubMed

    Yin, Zhendong; Liu, Xiaohui; Wu, Zhilu

    2013-01-01

    Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD) is proposed and implemented in direct-sequence ultra-wideband (DS-UWB) systems under the additive white Gaussian noise (AWGN) channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD) while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity.

  14. A Multiuser Detector Based on Artificial Bee Colony Algorithm for DS-UWB Systems

    PubMed Central

    Liu, Xiaohui

    2013-01-01

    Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD) is proposed and implemented in direct-sequence ultra-wideband (DS-UWB) systems under the additive white Gaussian noise (AWGN) channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD) while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity. PMID:23983638

  15. Protein levels and colony development of Africanized and European honey bees fed natural and artificial diets.

    PubMed

    Morais, M M; Turcatto, A P; Pereira, R A; Francoy, T M; Guidugli-Lazzarini, K R; Gonçalves, L S; de Almeida, J M V; Ellis, J D; De Jong, D

    2013-12-19

    Pollen substitute diets are a valuable resource for maintaining strong and health honey bee colonies. Specific diets may be useful in one region or country and inadequate or economically unviable in others. We compared two artificial protein diets that had been formulated from locally-available ingredients in Brazil with bee bread and a non-protein sucrose diet. Groups of 100 newly-emerged, adult workers of Africanized honey bees in Brazil and European honey bees in the USA were confined in small cages and fed on one of four diets for seven days. The artificial diets included a high protein diet made of soy milk powder and albumin, and a lower protein level diet consisting of soy milk powder, brewer's yeast and rice bran. The initial protein levels in newly emerged bees were approximately 18-21 µg/µL hemolymph. After feeding on the diets for seven days, the protein levels in the hemolymph were similar among the protein diet groups (~37-49 µg/µL after seven days), although Africanized bees acquired higher protein levels, increasing 145 and 100% on diets D1 and D2, respectively, versus 83 and 60% in the European bees. All the protein diets resulted in significantly higher levels of protein than sucrose solution alone. In the field, the two pollen substitute diets were tested during periods of low pollen availability in the field in two regions of Brazil. Food consumption, population development, colony weight, and honey production were evaluated to determine the impact of the diets on colony strength parameters. The colonies fed artificial diets had a significant improvement in all parameters, while control colonies dwindled during the dearth period. We conclude that these two artificial protein diets have good potential as pollen substitutes during dearth periods and that Africanized bees more efficiently utilize artificial protein diets than do European honey bees.

  16. Putting the waste out: a proposed mechanism for transmission of the mycoparasite Escovopsis between leafcutter ant colonies

    PubMed Central

    Augustin, Juliana O.; Simões, Talitta G.; Dijksterhuis, Jan; Evans, Harry C.

    2017-01-01

    The attine ant system is a remarkable example of symbiosis. An antagonistic partner within this system is the fungal parasite Escovopsis, a genus specific to the fungal gardens of the Attini. Escovopsis parasitizes the Leucoagaricus symbiont that leaf-cutting ants (Acromyrmex, Atta) have been farming over the past 8–12 Myr. However, it has been a puzzle how Escovopsis reaches its host. During a seasonal survey of nests of Acromyrmex subterraneus subterraneus in Atlantic rainforest in Brazil, Escovopsis was detected in all the sampled fungal garden waste tips or middens (n = 111). Middens were built strategically; always below the nest entrances. Here, we report the first evidence of a putative mechanism for horizontal transmission of Escovopsis between attine colonies. It is posited that leaf-cutting ants pick up the spores from soil and litter during foraging and vector the mycoparasite between attine colonies. Field and laboratory experiments, using At. laevigata and Ac. subterraneus subterraneus, confirm that Escovopsis spores are phoretic, and have an inbuilt dormancy, broken by the presence of their Leucoagaricus host. However, in the coevolutionary arms race, Atta ants may lose out—despite most species in the genus investing in a more advanced waste disposal system—due to the insanitary habits of their Acromyrmex neighbours. PMID:28572992

  17. Recursive Ant Colony Global Optimization: a new technique for the inversion of geophysical data

    NASA Astrophysics Data System (ADS)

    Gupta, D. K.; Gupta, J. P.; Arora, Y.; Singh, U. K.

    2011-12-01

    We present a new method called Recursive Ant Colony Global Optimization (RACO) technique, a modified form of general ACO, which can be used to find the best solutions to inversion problems in geophysics. RACO simulates the social behaviour of ants to find the best path between the nest and the food source. A new term depth has been introduced, which controls the extent of recursion. A selective number of cities get qualified for the successive depth. The results of one depth are used to construct the models for the next depth and the range of values for each of the parameters is reduced without any change to the number of models. The three additional steps performed after each depth, are the pheromone tracking, pheromone updating and city selection. One of the advantages of RACO over ACO is that if a problem has multiple solutions, then pheromone accumulation will take place at more than one city thereby leading to formation of multiple nested ACO loops within the ACO loop of the previous depth. Also, while the convergence of ACO is almost linear, RACO shows exponential convergence and hence is faster than the ACO. RACO proves better over some other global optimization techniques, as it does not require any initial values to be assigned to the parameters function. The method has been tested on some mathematical functions, synthetic self-potential (SP) and synthetic gravity data. The obtained results reveal the efficiency and practicability of the method. The method is found to be efficient enough to solve the problems of SP and gravity anomalies due to a horizontal cylinder, a sphere, an inclined sheet and multiple idealized bodies buried inside the earth. These anomalies with and without noise were inverted using the RACO algorithm. The obtained results were compared with those obtained from the conventional methods and it was found that RACO results are more accurate. Finally this optimization technique was applied to real field data collected over the Surda

  18. Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem.

    PubMed

    Zamdborg, Leonid; Holloway, David M; Merelo, Juan J; Levchenko, Vladimir F; Spirov, Alexander V

    2015-06-10

    Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of "genomic parasites", such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators

  19. Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem

    PubMed Central

    Zamdborg, Leonid; Holloway, David M.; Merelo, Juan J.; Levchenko, Vladimir F.; Spirov, Alexander V.

    2015-01-01

    Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of “genomic parasites”, such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent

  20. 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.

  1. Seasonal variation and the co-occurence of four pathogens and a group of parasites among monogyne and polygyne fire ant colonies

    USDA-ARS?s Scientific Manuscript database

    A year-long survey of was conducted to determine the seasonality and co-occurrence of four pathogens and a group of parasites in colonies of the red imported fire ant, Solenopsis invicta, in north-central Florida. S. invicta colonies were sampled and examined for the presence of Pseudacteon spp. (P...

  2. Scaling of differentiation in networks: nervous systems, organisms, ant colonies, ecosystems, businesses, universities, cities, electronic circuits, and Legos.

    PubMed

    Changizi, M A; McDannald, M A; Widders, D

    2002-09-21

    Nodes in networks are often of different types, and in this sense networks are differentiated. Here we examine the relationship between network differentiation and network size in networks under economic or natural selective pressure, such as electronic circuits (networks of electronic components), Legos (networks of Lego pieces), businesses (networks of employees), universities (networks of faculty), organisms (networks of cells), ant colonies (networks of ants), and nervous systems (networks of neurons). For each of these we find that (i) differentiation increases with network size, and (ii) the relationship is consistent with a power law. These results are explained by a hypothesis that, because nodes are costly to build and maintain in such "selected networks", network size is optimized, and from this the power-law relationship may be derived. The scaling exponent depends on the particular kind of network, and is determined by the degree to which nodes are used in a combinatorial fashion to carry out network-level functions. We find that networks under natural selection (organisms, ant colonies, and nervous systems) have much higher combinatorial abilities than the networks for which human ingenuity is involved (electronic circuits, Legos, businesses, and universities). A distinct but related optimization hypothesis may be used to explain scaling of differentiation in competitive networks (networks where the nodes themselves, rather than the entire network, are under selective pressure) such as ecosystems (networks of organisms).

  3. 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.

  4. Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm.

    PubMed

    Ozturk, Celal; Karaboga, Dervis; Gorkemli, Beyza

    2011-01-01

    As the usage and development of wireless sensor networks are increasing, the problems related to these networks are being realized. Dynamic deployment is one of the main topics that directly affect the performance of the wireless sensor networks. In this paper, the artificial bee colony algorithm is applied to the dynamic deployment of stationary and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A probabilistic detection model is considered to obtain more realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the particle swarm optimization algorithm, which is also a swarm based optimization technique and formerly used in wireless sensor network deployment. Results show artificial bee colony algorithm can be preferable in the dynamic deployment of wireless sensor networks.

  5. Ant colonies outperform individuals when a sensory discrimination task is difficult but not when it is easy.

    PubMed

    Sasaki, Takao; Granovskiy, Boris; Mann, Richard P; Sumpter, David J T; Pratt, Stephen C

    2013-08-20

    "Collective intelligence" and "wisdom of crowds" refer to situations in which groups achieve more accurate perception and better decisions than solitary agents. Whether groups outperform individuals should depend on the kind of task and its difficulty, but the nature of this relationship remains unknown. Here we show that colonies of Temnothorax ants outperform individuals for a difficult perception task but that individuals do better than groups when the task is easy. Subjects were required to choose the better of two nest sites as the quality difference was varied. For small differences, colonies were more likely than isolated ants to choose the better site, but this relationship was reversed for large differences. We explain these results using a mathematical model, which shows that positive feedback between group members effectively integrates information and sharpens the discrimination of fine differences. When the task is easier the same positive feedback can lock the colony into a suboptimal choice. These results suggest the conditions under which crowds do or do not become wise.

  6. On the Effects of Artificial Feeding on Bee Colony Dynamics: A Mathematical Model

    PubMed Central

    Paiva, Juliana Pereira Lisboa Mohallem; Paiva, Henrique Mohallem; Esposito, Elisa; Morais, Michelle Manfrini

    2016-01-01

    This paper proposes a new mathematical model to evaluate the effects of artificial feeding on bee colony population dynamics. The proposed model is based on a classical framework and contains differential equations that describe the changes in the number of hive bees, forager bees, and brood cells, as a function of amounts of natural and artificial food. The model includes the following elements to characterize the artificial feeding scenario: a function to model the preference of the bees for natural food over artificial food; parameters to quantify the quality and palatability of artificial diets; a function to account for the efficiency of the foragers in gathering food under different environmental conditions; and a function to represent different approaches used by the beekeeper to feed the hive with artificial food. Simulated results are presented to illustrate the main characteristics of the model and its behavior under different scenarios. The model results are validated with experimental data from the literature involving four different artificial diets. A good match between simulated and experimental results was achieved. PMID:27875589

  7. On the Effects of Artificial Feeding on Bee Colony Dynamics: A Mathematical Model.

    PubMed

    Paiva, Juliana Pereira Lisboa Mohallem; Paiva, Henrique Mohallem; Esposito, Elisa; Morais, Michelle Manfrini

    2016-01-01

    This paper proposes a new mathematical model to evaluate the effects of artificial feeding on bee colony population dynamics. The proposed model is based on a classical framework and contains differential equations that describe the changes in the number of hive bees, forager bees, and brood cells, as a function of amounts of natural and artificial food. The model includes the following elements to characterize the artificial feeding scenario: a function to model the preference of the bees for natural food over artificial food; parameters to quantify the quality and palatability of artificial diets; a function to account for the efficiency of the foragers in gathering food under different environmental conditions; and a function to represent different approaches used by the beekeeper to feed the hive with artificial food. Simulated results are presented to illustrate the main characteristics of the model and its behavior under different scenarios. The model results are validated with experimental data from the literature involving four different artificial diets. A good match between simulated and experimental results was achieved.

  8. The Effect of Symbiotic Ant Colonies on Plant Growth: A Test Using an Azteca-Cecropia System

    PubMed Central

    Oliveira, Karla N.; Coley, Phyllis D.; Kursar, Thomas A.; Kaminski, Lucas A.; Moreira, Marcelo Z.; Campos, Ricardo I.

    2015-01-01

    In studies of ant-plant mutualisms, the role that ants play in increasing the growth rates of their plant partners is potentially a key beneficial service. In the field, we measured the growth of Cecropia glaziovii saplings and compared individuals that were naturally colonized by Azteca muelleri ants with uncolonized plants in different seasons (wet and dry). We also measured light availability as well as attributes that could be influenced by the presence of Azteca colonies, such as herbivory, leaf nutrients (total nitrogen and δ15N), and investments in defense (total phenolics and leaf mass per area). We found that colonized plants grew faster than uncolonized plants and experienced a lower level of herbivory in both the wet and dry seasons. Colonized plants had higher nitrogen content than uncolonized plants, although the δ15N, light environment, total phenolics and leaf mass per area, did not differ between colonized and uncolonized plants. Since colonized and uncolonized plants did not differ in the direct defenses that we evaluated, yet herbivory was lower in colonized plants, we conclude that biotic defenses were the most effective protection against herbivores in our system. This result supports the hypothesis that protection provided by ants is an important factor promoting plant growth. Since C. glaziovii is widely distributed among a variety of forests and ecotones, and since we demonstrated a strong relationship with their ant partners, this system can be useful for comparative studies of ant-plant interactions in different habitats. Also, given this study was carried out near the transition to the subtropics, these results help generalize the geographic distribution of this mutualism and may shed light on the persistence of the interactions in the face of climate change. PMID:25811369

  9. The effect of symbiotic ant colonies on plant growth: a test using an Azteca-Cecropia system.

    PubMed

    Oliveira, Karla N; Coley, Phyllis D; Kursar, Thomas A; Kaminski, Lucas A; Moreira, Marcelo Z; Campos, Ricardo I

    2015-01-01

    In studies of ant-plant mutualisms, the role that ants play in increasing the growth rates of their plant partners is potentially a key beneficial service. In the field, we measured the growth of Cecropia glaziovii saplings and compared individuals that were naturally colonized by Azteca muelleri ants with uncolonized plants in different seasons (wet and dry). We also measured light availability as well as attributes that could be influenced by the presence of Azteca colonies, such as herbivory, leaf nutrients (total nitrogen and δ(15)N), and investments in defense (total phenolics and leaf mass per area). We found that colonized plants grew faster than uncolonized plants and experienced a lower level of herbivory in both the wet and dry seasons. Colonized plants had higher nitrogen content than uncolonized plants, although the δ(15)N, light environment, total phenolics and leaf mass per area, did not differ between colonized and uncolonized plants. Since colonized and uncolonized plants did not differ in the direct defenses that we evaluated, yet herbivory was lower in colonized plants, we conclude that biotic defenses were the most effective protection against herbivores in our system. This result supports the hypothesis that protection provided by ants is an important factor promoting plant growth. Since C. glaziovii is widely distributed among a variety of forests and ecotones, and since we demonstrated a strong relationship with their ant partners, this system can be useful for comparative studies of ant-plant interactions in different habitats. Also, given this study was carried out near the transition to the subtropics, these results help generalize the geographic distribution of this mutualism and may shed light on the persistence of the interactions in the face of climate change.

  10. Worker lifespan is an adaptive trait during colony establishment in the long-lived ant Lasius niger.

    PubMed

    Kramer, Boris H; Schaible, Ralf; Scheuerlein, Alexander

    2016-12-01

    Eusociality has been recognized as a strong driver of lifespan evolution. While queens show extraordinary lifespans of 20years and more, worker lifespan is short and variable. A recent comparative study found that in eusocial species with larger average colony sizes the disparities in the lifespans of the queen and the worker are also greater, which suggests that lifespan might be an evolved trait. Here, we tested whether the same pattern holds during colony establishment: as colonies grow larger, worker lifespan should decrease. We studied the mortality of lab-reared Lasius niger workers from colonies at two different developmental stages (small and intermediate-sized) in a common garden experiment. Workers were kept in artificial cohorts that differed only with respect to the stage of the colony they were born in. We found that the stage of the birth colony affected the body size and the survival probability of the workers. The workers that had emerged from early stage colonies were smaller and had lower mortality during the first 400days of their life than the workers born in colonies at a later stage. Our results suggest that early stage colonies produce small workers with an increased survival probability. These workers are gradually augmented by larger workers with a decreased survival probability that serve as a redundant workforce with easily replaceable individuals. We doubt that the observed differences in lifespan are driven by differences in body size. Rather, we suspect that physiological mechanisms are the basis for the observed differences in lifespan. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Conserved Microsatellites in Ants Enable Population Genetic and Colony Pedigree Studies across a Wide Range of Species

    PubMed Central

    Butler, Ian A.; Siletti, Kimberly; Oxley, Peter R.; Kronauer, Daniel J. C.

    2014-01-01

    Broadly applicable polymorphic genetic markers are essential tools for population genetics, and different types of markers have been developed for this purpose. Microsatellites have been employed as particularly polymorphic markers for over 20 years. However, PCR primers for microsatellite loci are often not useful outside the species for which they were designed. This implies that a new set of loci has to be identified and primers developed for every new study species. To overcome this constraint, we identified 45 conserved microsatellite loci based on the eight currently available ant genomes and designed primers for PCR amplification. Among these loci, we chose 24 for in-depth study in six species covering six different ant subfamilies. On average, 11.16 of these 24 loci were polymorphic and in Hardy-Weinberg equilibrium in any given species. The average number of alleles for these polymorphic loci within single populations of the different species was 4.59. This set of genetic markers will thus be useful for population genetic and colony pedigree studies across a wide range of ant species, supplementing the markers available for previously studied species and greatly facilitating the study of the many ant species lacking genetic markers. Our study shows that it is possible to develop microsatellite loci that are both conserved over a broad range of taxa, yet polymorphic within species. This should encourage researchers to develop similar tools for other large taxonomic groups. PMID:25244681

  12. Conserved microsatellites in ants enable population genetic and colony pedigree studies across a wide range of species.

    PubMed

    Butler, Ian A; Siletti, Kimberly; Oxley, Peter R; Kronauer, Daniel J C

    2014-01-01

    Broadly applicable polymorphic genetic markers are essential tools for population genetics, and different types of markers have been developed for this purpose. Microsatellites have been employed as particularly polymorphic markers for over 20 years. However, PCR primers for microsatellite loci are often not useful outside the species for which they were designed. This implies that a new set of loci has to be identified and primers developed for every new study species. To overcome this constraint, we identified 45 conserved microsatellite loci based on the eight currently available ant genomes and designed primers for PCR amplification. Among these loci, we chose 24 for in-depth study in six species covering six different ant subfamilies. On average, 11.16 of these 24 loci were polymorphic and in Hardy-Weinberg equilibrium in any given species. The average number of alleles for these polymorphic loci within single populations of the different species was 4.59. This set of genetic markers will thus be useful for population genetic and colony pedigree studies across a wide range of ant species, supplementing the markers available for previously studied species and greatly facilitating the study of the many ant species lacking genetic markers. Our study shows that it is possible to develop microsatellite loci that are both conserved over a broad range of taxa, yet polymorphic within species. This should encourage researchers to develop similar tools for other large taxonomic groups.

  13. Artificial selection on ant female caste ratio uncovers a link between female-biased sex ratios and infection by Wolbachia endosymbionts.

    PubMed

    Pontieri, L; Schmidt, A M; Singh, R; Pedersen, J S; Linksvayer, T A

    2017-02-01

    Social insect sex and caste ratios are well-studied targets of evolutionary conflicts, but the heritable factors affecting these traits remain unknown. To elucidate these factors, we carried out a short-term artificial selection study on female caste ratio in the ant Monomorium pharaonis. Across three generations of bidirectional selection, we observed no response for caste ratio, but sex ratios rapidly became more female-biased in the two replicate high selection lines and less female-biased in the two replicate low selection lines. We hypothesized that this rapid divergence for sex ratio was caused by changes in the frequency of infection by the heritable bacterial endosymbiont Wolbachia, because the initial breeding stock varied for Wolbachia infection, and Wolbachia is known to cause female-biased sex ratios in other insects. Consistent with this hypothesis, the proportions of Wolbachia-infected colonies in the selection lines changed rapidly, mirroring the sex ratio changes. Moreover, the estimated effect of Wolbachia on sex ratio (~13% female bias) was similar in colonies before and during artificial selection, indicating that this Wolbachia effect is likely independent of the effects of artificial selection on other heritable factors. Our study provides evidence for the first case of endosymbiont sex ratio manipulation in a social insect.

  14. Tight knit under stress: colony resilience to the loss of tandem leaders during relocation in an Indian ant

    PubMed Central

    Kolay, Swetashree; Annagiri, Sumana

    2015-01-01

    The movement of colonies from one nest to another is a frequent event in the lives of many social insects and is important for their survival and propagation. This goal-oriented task is accomplished by means of tandem running in some ant species, such as Diacamma indicum. Tandem leaders are central to this process as they know the location of the new nest and lead colony members to it. Relocations involving targeted removal of leaders were compared with unmanipulated and random member removal relocations. Behavioural observations were integrated with network analysis to examine the differences in the pattern of task organization at the level of individuals and that of the colony. All colonies completed relocation successfully and leaders who substituted the removed tandem leaders conducted the task at a similar rate having redistributed the task in a less skewed manner. In terms of network structure, this resilience was due to significantly higher density and outcloseness indicating increased interaction between substitute leaders. By contrast, leader–follower interactions and random removal networks showed no discernible changes. Similar explorations of other goal-oriented tasks in other societies will possibly unveil new facets in the interplay between individuals that enable the group to respond effectively to stress. PMID:26473038

  15. Tight knit under stress: colony resilience to the loss of tandem leaders during relocation in an Indian ant.

    PubMed

    Kolay, Swetashree; Annagiri, Sumana

    2015-09-01

    The movement of colonies from one nest to another is a frequent event in the lives of many social insects and is important for their survival and propagation. This goal-oriented task is accomplished by means of tandem running in some ant species, such as Diacamma indicum. Tandem leaders are central to this process as they know the location of the new nest and lead colony members to it. Relocations involving targeted removal of leaders were compared with unmanipulated and random member removal relocations. Behavioural observations were integrated with network analysis to examine the differences in the pattern of task organization at the level of individuals and that of the colony. All colonies completed relocation successfully and leaders who substituted the removed tandem leaders conducted the task at a similar rate having redistributed the task in a less skewed manner. In terms of network structure, this resilience was due to significantly higher density and outcloseness indicating increased interaction between substitute leaders. By contrast, leader-follower interactions and random removal networks showed no discernible changes. Similar explorations of other goal-oriented tasks in other societies will possibly unveil new facets in the interplay between individuals that enable the group to respond effectively to stress.

  16. Research on remote sensing image segmentation based on ant colony algorithm: take the land cover classification of middle Qinling Mountains for example

    NASA Astrophysics Data System (ADS)

    Mei, Xin; Wang, Qian; Wang, Quanfang; Lin, Wenfang

    2009-10-01

    Remote sensing image based on the complexity of the background features, has a wealth of spatial information, how to extract huge amounts of data in the region of interest is a serious problem. Image segmentation refers to certain provisions in accordance with the characteristics of the image into different regions, and it is the key of remote sensing image recognition and information extraction. Reasonably fast image segmentation algorithm is the base of image processing; traditional segmentation methods have a lot of the limitations. Traditional threshold segmentation method in essence is an ergodic process, the low efficiency impacts on its application. The ant colony algorithm is a populationbased evolutionary algorithm heuristic biomimetic, since proposed, it has been successfully applied to the TSP, job-shop scheduling problem, network routing problem, vehicle routing problem, as well as other cluster analysis. Ant colony optimization algorithm is a fast heuristic optimization algorithm, easily integrates with other methods, and it is robust. Improved ant colony algorithm can greatly enhance the speed of image segmentation, while reducing the noise on the image. The research background of this paper is land cover classification experiments according to the SPOT images of Qinling area. The image segmentation based on ant colony algorithm is carried out and compared with traditional methods. Experimental results show that improved the ant colony algorithm can quickly and accurately segment target, and it is an effective method of image segmentation, it also has laid a good foundation of image classification for the follow-up work.

  17. 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.

  18. Application of Ant-Colony-Optimization algorithm for improved management of first flush effects in urban wastewater systems.

    PubMed

    Verdaguer, M; Clara, N; Gutiérrez, O; Poch, M

    2014-07-01

    The first flush effect in combined sewer systems during storm events often causes overflows and overloads of the sewage treatment, which reduces the efficiency of the sewage treatment and decreases the quality of the receiving waters due to the pollutants that are contributed. The use of retention tanks constitutes a widely used way to mitigate this effect. However, the management of the pollutant loads encounters difficulties when the retention tanks are emptied. A new approach is proposed to solve this problem by fulfilling the treatment requirements in real time, focussing on the characteristics of the wastewater. The method is based on the execution of an Ant Colony Optimisation algorithm to obtain a satisfactory sequence for the discharge of the retention tanks. The discharge sequence considers the volume of stormwater and its concentration of pollutants including Suspended Solids, Biological Oxygen Demand and Chemical Oxygen Demand, Total Nitrogen and Total Phosphorus. The Ant Colony Optimisation algorithm was applied successfully to a case study with overall reduction of pollutant loads stored in retention tanks. The algorithm can be adapted in a simple way to the different scenarios, infrastructures and controllers of sewer systems.

  19. Correlation between virulence and genetic structure of Escovopsis strains from leaf-cutting ant colonies in Costa Rica.

    PubMed

    Wallace, Diego E Elizondo; Asensio, Juan G Vargas; Tomás, Adrián A Pinto

    2014-08-01

    Leaf-cutting ants (genera Atta and Acromyrmex) cultivate a specialized fungus for food in underground chambers employing cut plant material as substrate. Parasitism occurs in this agricultural system and plays an important role in colony fitness. The microfungi Escovopsis, a specialized mycoparasite of the fungal cultivar, is highly prevalent among colonies. In this study, we tested the antagonistic activity of several Escovopsis strains from different geographical areas in Costa Rica. We employed a combination of laboratory tests to evaluate virulence, including pure culture challenges, toxicity to fungus garden pieces and subcolony bioassays. We also performed a phylogenetic analysis of these strains in order to correlate their virulence with the genetic structure of this population. The bioassays yielded results consistent between each other and showed significant differences in antagonistic activity among the parasites evaluated. However, no significant differences were found when comparing the results of the bioassays according to the source of the ants' fungal cultivar. The phylogenetic analyses were consistent with these results: whilst the fungal cultivar phylogeny showed a single clade with limited molecular variation, the Escovopsis phylogeny yielded several clades with the most virulent isolates grouping in the same well-supported clade. These results indicate that there are Escovopsis strains better suited to establish their antagonistic effect, whilst the genetic homogeneity of the fungal cultivars limits their ability to modulate Escovopsis antagonism. These findings should be taken into consideration when evaluating the potential of Escovopsis isolates as biocontrol agents for this important agricultural pest in the Neotropics.

  20. Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm.

    PubMed

    Beloufa, Fayssal; Chikh, M A

    2013-10-01

    In this study, diagnosis of diabetes disease, which is one of the most important diseases, is conducted with artificial intelligence techniques. We have proposed a novel Artificial Bee Colony (ABC) algorithm in which a mutation operator is added to an Artificial Bee Colony for improving its performance. When the current best solution cannot be updated, a blended crossover operator (BLX-α) of genetic algorithm is applied, in order to enhance the diversity of ABC, without compromising with the solution quality. This modified version of ABC is used as a new tool to create and optimize automatically the membership functions and rules base directly from data. We take the diabetes dataset used in our work from the UCI machine learning repository. The performances of the proposed method are evaluated through classification rate, sensitivity and specificity values using 10-fold cross-validation method. The obtained classification rate of our method is 84.21% and it is very promising when compared with the previous research in the literature for the same problem. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  1. Dynamic population artificial bee colony algorithm for multi-objective optimal power flow.

    PubMed

    Ding, Man; Chen, Hanning; Lin, Na; Jing, Shikai; Liu, Fang; Liang, Xiaodan; Liu, Wei

    2017-03-01

    This paper proposes a novel artificial bee colony algorithm with dynamic population (ABC-DP), which synergizes the idea of extended life-cycle evolving model to balance the exploration and exploitation tradeoff. The proposed ABC-DP 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. ABC-DP is then used for solving the optimal power flow (OPF) problem in power systems that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results, which are also compared to nondominated sorting genetic algorithm II (NSGAII) and multi-objective ABC (MOABC), are presented to illustrate the effectiveness and robustness of the proposed method.

  2. A Modified Artificial Bee Colony Algorithm for p-Center Problems

    PubMed Central

    Yurtkuran, Alkın

    2014-01-01

    The objective of the p-center problem is to locate p-centers on a network such that the maximum of the distances from each node to its nearest center is minimized. The artificial bee colony algorithm is a swarm-based meta-heuristic algorithm that mimics the foraging behavior of honey bee colonies. This study proposes a modified ABC algorithm that benefits from a variety of search strategies to balance exploration and exploitation. Moreover, random key-based coding schemes are used to solve the p-center problem effectively. The proposed algorithm is compared to state-of-the-art techniques using different benchmark problems, and computational results reveal that the proposed approach is very efficient. PMID:24616648

  3. Dynamic changes in host-virus interactions associated with colony founding and social environment in fire ant queens (Solenopsis invicta).

    PubMed

    Manfredini, Fabio; Shoemaker, DeWayne; Grozinger, Christina M

    2016-01-01

    The dynamics of host-parasite interactions can change dramatically over the course of a chronic infection as the internal (physiological) and external (environmental) conditions of the host change. When queens of social insects found a colony, they experience changes in both their physiological state (they develop their ovaries and begin laying eggs) and the social environment (they suddenly stop interacting with the other members of the mother colony), making this an excellent model system for examining how these factors interact with chronic infections. We investigated the dynamics of host-viral interactions in queens of Solenopsis invicta (fire ant) as they transition from mating to colony founding/brood rearing to the emergence of the first workers. We examined these dynamics in naturally infected queens in two different social environments, where queens either founded colonies as individuals or as pairs. We hypothesized that stress associated with colony founding plays an important role in the dynamics of host-parasite interactions. We also hypothesized that different viruses have different modalities of interaction with the host that can be quantified by physiological measures and genomic analysis of gene expression in the host. We found that the two most prevalent viruses, SINV-1 and SINV-2, are associated with different fitness costs that are mirrored by different patterns of gene expression in the host. In fact SINV-2, the virus that imposes the significant reduction of a queen's reproductive output is also associated with larger changes of global gene expression in the host. These results show the complexity of interactions between S. invicta and two viral parasites. Our findings also show that chronic infections by viral parasites in insects are dynamic processes that may pose different challenges in the host, laying the groundwork for interesting ecological and evolutionary considerations.

  4. Population genetics and colony structure of the Argentine ant (Linepithema humile) in its native and introduced ranges.

    PubMed

    Tsutsui, N D; Case, T J

    2001-05-01

    Introduced species often possess low levels of genetic diversity relative to source populations as a consequence of the small population sizes associated with founder events. Additionally, native and introduced populations of the same species can possess divergent genetic structuring at both large and small geographic scales. Thus, genetic systems that have evolved in the context of high diversity may function quite differently in genetically homogeneous introduced populations. Here we conduct a genetic analysis of native and introduced populations of the Argentine ant (Linepithema humile) in which we show that the population-level changes that have occurred during introduction have produced marked changes in the social structure of this species. Native populations of the Argentine ant are characterized by a pattern of genetic isolation by distance, whereas this pattern is absent in introduced populations. These differences appear to arise both from the effects of recent range expansion in the introduced range as well as from differences in gene flow within each range. Relatedness within nests and colonies is lower in the introduced range than in the native range as a consequence of the widespread genetic similarity that typifies introduced populations. In contrast, nestmates and colony-mates in the native range are more closely related, and local genetic differentiation is evident. Our results shed light on the problem posed for kin selection theory by the low levels of relatedness that are characteristic of many unicolonial species and suggest that the loss of genetic variation may be a common mechanism for the transition to a unicolonial colony structure.

  5. Partially constrained ant colony optimization algorithm for the solution of constrained optimization problems: Application to storm water network design

    NASA Astrophysics Data System (ADS)

    Afshar, M. H.

    2007-04-01

    This paper exploits the unique feature of the Ant Colony Optimization Algorithm (ACOA), namely incremental solution building mechanism, to develop partially constraint ACO algorithms for the solution of optimization problems with explicit constraints. The method is based on the provision of a tabu list for each ant at each decision point of the problem so that some constraints of the problem are satisfied. The application of the method to the problem of storm water network design is formulated and presented. The network nodes are considered as the decision points and the nodal elevations of the network are used as the decision variables of the optimization problem. Two partially constrained ACO algorithms are formulated and applied to a benchmark example of storm water network design and the results are compared with those of the original unconstrained algorithm and existing methods. In the first algorithm the positive slope constraints are satisfied explicitly and the rest are satisfied by using the penalty method while in the second one the satisfaction of constraints regarding the maximum ratio of flow depth to the diameter are also achieved explicitly via the tabu list. The method is shown to be very effective and efficient in locating the optimal solutions and in terms of the convergence characteristics of the resulting ACO algorithms. The proposed algorithms are also shown to be relatively insensitive to the initial colony used compared to the original algorithm. Furthermore, the method proves itself capable of finding an optimal or near-optimal solution, independent of the discretisation level and the size of the colony used.

  6. Research on WNN modeling for gold price forecasting based on improved artificial bee colony algorithm.

    PubMed

    Li, Bai

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme.

  7. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

  8. Improved artificial bee colony algorithm for vehicle routing problem with time windows.

    PubMed

    Yao, Baozhen; Yan, Qianqian; Zhang, Mengjie; Yang, Yunong

    2017-01-01

    This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificial bee colony (IABC) algorithm. The performance of this algorithm is improved by a local optimization based on a crossover operation and a scanning strategy. Finally, the effectiveness of the IABC is evaluated on some well-known benchmarks. The results demonstrate the power of IABC algorithm in solving the VRPTW.

  9. Comparative study of nest architecture and colony structure of the fungus-growing ants, Mycocepurus goeldii and M. smithii.

    PubMed

    Rabeling, C; Verhaagh, M; Engels, W

    2007-01-01

    Nest architecture and demography of the non leaf-cutting fungus-growing ant species Mycocepurus goeldii and M. smithii (Attini: Formicidae) were studied in an agroforest habitat near Manaus, Brazil during the excavation of 13 nests. Both species built their nests in two different ways. The first type possessed a "tree-like" architecture, in which a vertical tunnel led downwards and lateral tunnels branched off at 90 degrees angles from the main tunnel, with a chamber at the end of each side branch. Alternatively, other nests displayed a "necklace-like" architecture, where the main tunnel also led down vertically, but entered each chamber from the top and exited it at the bottom, resulting in an architecture where chambers appeared like pearls on a necklace. The nest systems of M. goeldii and M. smithii consisted of 1-21 or 1-15 chambers, respectively. Of 199 excavated chambers, 57 % contained fungus-gardens. Chambers not containing fungus gardens were filled with organic matter from decaying fungus gardens or earthworm feces. Only M. smithii workers deposited loose soil in abandoned chambers during the construction of new nest chambers. Workers of M. smithii constructed significantly smaller chambers than those of M. goeldii. In both species, fungus garden-containing chambers were larger than non-garden chambers and were homogenously distributed in the soil between 17 cm and 105 cm depth. Neither fungus gardens nor abandoned chambers were encountered more frequently in deeper or shallower soil strata indicating that ants of both species did not abandon shallower versus deeper chambers, or move the colony to deeper soil layers with increasing colony age. Fungus gardens were suspended from the ceiling of the subterranean chambers and originated as small mycelial tufts. Through continual addition of organic debris, the tufts first grew vertically to strands before they expanded laterally until most of the chamber volume was filled with fungus garden curtains. New

  10. 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...

  11. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps

    PubMed Central

    Mao, Wei; Li, Hao-ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426

  12. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.

    PubMed

    Mao, Wei; Lan, Heng-You; Li, Hao-Ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions.

  13. A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model.

    PubMed

    Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

    2014-09-01

    Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP.

  14. 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.

  15. 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.

  16. 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.

  17. Male fighting and ``territoriality'' within colonies of the ant Cardiocondyla venustula

    NASA Astrophysics Data System (ADS)

    Frohschammer, Sabine; Heinze, Jürgen

    2009-01-01

    The ant genus Cardiocondyla is characterized by a bizarre male polymorphism with wingless fighter males and winged disperser males. Winged males have been lost convergently in several clades, and in at least one of them, wingless males have evolved mutual tolerance. To better understand the evolutionary pathways of reproductive tactics, we investigated Cardiocondyla venustula, a species, which in a phylogenetic analysis clusters with species with fighting and species with mutually tolerant, wingless males. Wingless males of C. venustula use their strong mandibles to kill freshly eclosed rival males and also engage in short fights with other adult males, but in addition show a novel behavior hitherto not reported from social insect males: they spread out in the natal nest and defend “territories” against other males. Ant males therefore show a much larger variety of reproductive tactics than previously assumed.

  18. Three-Dimensional Path Planning and Guidance of Leg Vascular Based on Improved Ant Colony Algorithm in Augmented Reality.

    PubMed

    Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua

    2015-11-01

    Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.

  19. 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

  20. Effect of land cover, habitat fragmentation and ant colonies on the distribution and abundance of shrews in southern California

    USGS Publications Warehouse

    Laakkonen, Juha; Fisher, Robert N.; Case, Ted J.

    2001-01-01

    Because effects of habitat fragmentation and anthropogenic disturbance on native animals have been relatively little studied in arid areas and in insectivores, we investigated the roles of different land covers, habitat fragmentation and ant colonies on the distribution and abundance of shrews, Notiosorex crawfordi and Sorex ornatus, in southern California.Notiosorex crawfordi was the numerically dominant species (trap-success rate 0·52) occurring in 21 of the 22 study sites in 85% of the 286 pitfall arrays used in this study.Sorex ornatus was captured in 14 of the sites, in 52% of the arrays with a total trap-success rate of 0·2. Neither of the species was found in one of the sites.The population dynamics of the two shrew species were relatively synchronous during the 4–5-year study; the peak densities usually occurred during the spring. Precipitation had a significant positive effect, and maximum temperature a significant negative effect on the trap-success rate of S. ornatus.Occurrence and abundance of shrews varied significantly between sites and years but the size of the landscape or the study site had no effect on the abundance of shrews. The amount of urban edge had no significant effect on the captures of shrews but increased edge allows invasion of the Argentine ants, which had a highly significant negative impact on the abundance of N. crawfordi.At the trap array level, the percentage of coastal sage scrub flora had a significant positive, and the percentage of other flora had a significant negative effect on the abundance of N. crawfordi. The mean canopy height and the abundance of N. crawfordi had a significant positive effect on the occurrence of S. ornatus.Our study suggests that the loss of native coastal sage scrub flora and increasing presence of Argentine ant colonies may significantly effect the distribution and abundance of N. crawfordi. The very low overall population densities of both shrew species in most study sites make both species

  1. Application of Artificial Bee Colony algorithm in TEC seismo-ionospheric anomalies detection

    NASA Astrophysics Data System (ADS)

    Akhoondzadeh, M.

    2015-09-01

    In this study, the efficiency of Artificial Bee Colony (ABC) algorithm is investigated to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of some strong earthquakes including Chile (27 February 2010; 01 April 2014), Varzeghan (11 August 2012), Saravan (16 April 2013) and Papua New Guinea (29 March 2015). In comparison with other anomaly detection algorithms, ABC has a number of advantages which can be numerated as (1) detection of discord patterns in a large non linear data during a short time, (2) simplicity, (3) having less control parameters and (4) efficiently for solving multimodal and multidimensional optimization problems. Also the results of this study acknowledge the TEC time-series as a robust earthquake precursor.

  2. 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

  3. Efficient implementation and application of the artificial bee colony algorithm to low-dimensional optimization problems

    NASA Astrophysics Data System (ADS)

    von Rudorff, Guido Falk; Wehmeyer, Christoph; Sebastiani, Daniel

    2014-06-01

    We adapt a swarm-intelligence-based optimization method (the artificial bee colony algorithm, ABC) to enhance its parallel scaling properties and to improve the escaping behavior from deep local minima. Specifically, we apply the approach to the geometry optimization of Lennard-Jones clusters. We illustrate the performance and the scaling properties of the parallelization scheme for several system sizes (5-20 particles). Our main findings are specific recommendations for ranges of the parameters of the ABC algorithm which yield maximal performance for Lennard-Jones clusters and Morse clusters. The suggested parameter ranges for these different interaction potentials turn out to be very similar; thus, we believe that our reported values are fairly general for the ABC algorithm applied to chemical optimization problems.

  4. A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

    PubMed Central

    Ju, Chunhua

    2013-01-01

    Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods. PMID:24381525

  5. Weighted Global Artificial Bee Colony Algorithm Makes Gas Sensor Deployment Efficient

    PubMed Central

    Jiang, Ye; He, Ziqing; Li, Yanhai; Xu, Zhengyi; Wei, Jianming

    2016-01-01

    This paper proposes an improved artificial bee colony algorithm named Weighted Global ABC (WGABC) algorithm, which is designed to improve the convergence speed in the search stage of solution search equation. The new method not only considers the effect of global factors on the convergence speed in the search phase, but also provides the expression of global factor weights. Experiment on benchmark functions proved that the algorithm can improve the convergence speed greatly. We arrive at the gas diffusion concentration based on the theory of CFD and then simulate the gas diffusion model with the influence of buildings based on the algorithm. Simulation verified the effectiveness of the WGABC algorithm in improving the convergence speed in optimal deployment scheme of gas sensors. Finally, it is verified that the optimal deployment method based on WGABC algorithm can improve the monitoring efficiency of sensors greatly as compared with the conventional deployment methods. PMID:27322262

  6. A hybrid artificial bee colony optimization and quantum evolutionary algorithm for continuous optimization problems.

    PubMed

    Duan, Hai-Bin; Xu, Chun-Fang; Xing, Zhi-Hui

    2010-02-01

    In this paper, a novel hybrid Artificial Bee Colony (ABC) and Quantum Evolutionary Algorithm (QEA) is proposed for solving continuous optimization problems. ABC is adopted to increase the local search capacity as well as the randomness of the populations. In this way, the improved QEA can jump out of the premature convergence and find the optimal value. To show the performance of our proposed hybrid QEA with ABC, a number of experiments are carried out on a set of well-known Benchmark continuous optimization problems and the related results are compared with two other QEAs: the QEA with classical crossover operation, and the QEA with 2-crossover strategy. The experimental comparison results demonstrate that the proposed hybrid ABC and QEA approach is feasible and effective in solving complex continuous optimization problems.

  7. An Improved Artificial Bee Colony Algorithm for Solving Hybrid Flexible Flowshop With Dynamic Operation Skipping.

    PubMed

    Li, Jun-Qing; Pan, Quan-Ke; Duan, Pei-Yong

    2016-06-01

    In this paper, we propose an improved discrete artificial bee colony (DABC) algorithm to solve the hybrid flexible flowshop scheduling problem with dynamic operation skipping features in molten iron systems. First, each solution is represented by a two-vector-based solution representation, and a dynamic encoding mechanism is developed. Second, a flexible decoding strategy is designed. Next, a right-shift strategy considering the problem characteristics is developed, which can clearly improve the solution quality. In addition, several skipping and scheduling neighborhood structures are presented to balance the exploration and exploitation ability. Finally, an enhanced local search is embedded in the proposed algorithm to further improve the exploitation ability. The proposed algorithm is tested on sets of the instances that are generated based on the realistic production. Through comprehensive computational comparisons and statistical analysis, the highly effective performance of the proposed DABC algorithm is favorably compared against several presented algorithms, both in solution quality and efficiency.

  8. 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.

  9. A new collaborative recommendation approach based on users clustering using artificial bee colony algorithm.

    PubMed

    Ju, Chunhua; Xu, Chonghuan

    2013-01-01

    Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

  10. A self adaptive hybrid enhanced artificial bee colony algorithm for continuous optimization problems.

    PubMed

    Shan, Hai; Yasuda, Toshiyuki; Ohkura, Kazuhiro

    2015-06-01

    The artificial bee colony (ABC) algorithm is one of popular swarm intelligence algorithms that inspired by the foraging behavior of honeybee colonies. To improve the convergence ability, search speed of finding the best solution and control the balance between exploration and exploitation using this approach, we propose a self adaptive hybrid enhanced ABC algorithm in this paper. To evaluate the performance of standard ABC, best-so-far ABC (BsfABC), incremental ABC (IABC), and the proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation (CEC) 2014 test suite. Our experimental results show the comparative performance of standard ABC, BsfABC, IABC, and the proposed ABC algorithms. According to the results, we conclude that the proposed ABC algorithm is competitive to those state-of-the-art modified ABC algorithms such as BsfABC and IABC algorithms based on the benchmark problems defined by CEC 2014 test suite with dimension sizes of 10, 30, and 50, respectively. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  11. Preimaginal learning as a basis of colony-brood recognition in the ant Cataglyphis cursor

    PubMed Central

    Isingrini, Michel; Lenoir, Alain; Jaisson, Pierre

    1985-01-01

    In most circumstances, social insects recognize their nestmates. They can discriminate against alien adults and also against alien larvae. Results presented here indicate that the mechanism of colony-brood recognition is acquired in large part during larval life and persists through the metamorphosis into the adult stage. During the first days after emergence of the adult, a weaker form of learning can also occur. These phenomena are discussed in relation to kinship theory. It appears that kin recognition is determined not so much by genetic relatedness as by spatial proximity of the individuals during the early stages of life. PMID:16593637

  12. Preimaginal learning as a basis of colony-brood recognition in the ant Cataglyphis cursor.

    PubMed

    Isingrini, M; Lenoir, A; Jaisson, P

    1985-12-01

    In most circumstances, social insects recognize their nestmates. They can discriminate against alien adults and also against alien larvae. Results presented here indicate that the mechanism of colony-brood recognition is acquired in large part during larval life and persists through the metamorphosis into the adult stage. During the first days after emergence of the adult, a weaker form of learning can also occur. These phenomena are discussed in relation to kinship theory. It appears that kin recognition is determined not so much by genetic relatedness as by spatial proximity of the individuals during the early stages of life.

  13. Extrafloral nectar content alters foraging preferences of a predatory ant

    PubMed Central

    Wilder, Shawn M.; Eubanks, Micky D.

    2010-01-01

    We tested whether the carbohydrate and amino acid content of extrafloral nectar affected prey choice by a predatory ant. Fire ants, Solenopsis invicta, were provided with artificial nectar that varied in the presence of carbohydrates and amino acids and were then provided with two prey items that differed in nutritional content, female and male crickets. Colonies of fire ants provided with carbohydrate supplements consumed less of the female crickets and frequently did not consume the high-lipid ovaries of female crickets. Colonies of fire ants provided with amino acid supplements consumed less of the male crickets. While a number of studies have shown that the presence of extrafloral nectar or honeydew can affect ant foraging activity, these results suggest that the nutritional composition of extrafloral nectar is also important and can affect subsequent prey choice by predatory ants. Our results suggest that, by altering the composition of extrafloral nectar, plants could manipulate the prey preferences of ants foraging on them. PMID:19864270

  14. Extrafloral nectar content alters foraging preferences of a predatory ant.

    PubMed

    Wilder, Shawn M; Eubanks, Micky D

    2010-04-23

    We tested whether the carbohydrate and amino acid content of extrafloral nectar affected prey choice by a predatory ant. Fire ants, Solenopsis invicta, were provided with artificial nectar that varied in the presence of carbohydrates and amino acids and were then provided with two prey items that differed in nutritional content, female and male crickets. Colonies of fire ants provided with carbohydrate supplements consumed less of the female crickets and frequently did not consume the high-lipid ovaries of female crickets. Colonies of fire ants provided with amino acid supplements consumed less of the male crickets. While a number of studies have shown that the presence of extrafloral nectar or honeydew can affect ant foraging activity, these results suggest that the nutritional composition of extrafloral nectar is also important and can affect subsequent prey choice by predatory ants. Our results suggest that, by altering the composition of extrafloral nectar, plants could manipulate the prey preferences of ants foraging on them.

  15. Modeling discharge-sediment relationship using neural networks with artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Ozkan, Coskun; Akay, Bahriye

    2012-03-01

    SummaryEstimation of suspended sediment concentration carried by a river is very important for many water resources projects. The accuracy of artificial neural networks (ANN) with artificial bee colony (ABC) algorithm is investigated in this paper for modeling discharge-suspended sediment relationship. The ANN-ABC was compared with those of the neural differential evolution, adaptive neuro-fuzzy, neural networks and rating curve models. The daily stream flow and suspended sediment concentration data from two stations, Rio Valenciano Station and Quebrada Blanca Station, were used as case studies. For evaluating the ability of the models, mean square error and determination coefficient criteria were used. Comparison results showed that the ANN-ABC was able to produce better results than the neural differential evolution, neuro-fuzzy, neural networks and rating curve models. The logarithm transformed data were also used as input to the proposed ANN-ABC models. It was found that the logarithm transform significantly increased accuracy of the models in suspended sediment estimation.

  16. 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.

  17. Coming of age in an ant colony: cephalic muscle maturation accompanies behavioral development in Pheidole dentata

    NASA Astrophysics Data System (ADS)

    Muscedere, Mario L.; Traniello, James F. A.; Gronenberg, Wulfila

    2011-09-01

    Although several neurobiological and genetic correlates of aging and behavioral development have been identified in social insect workers, little is known about how other age-related physiological processes, such as muscle maturation, contribute to task performance. We examined post-eclosion growth of three major muscles of the head capsule in major and minor workers of the ant Pheidole dentata using workers of different ages with distinct task repertoires. Mandible closer muscle fibers, which provide bite force and are thus critical for the use of the mandibles for biting and load carrying, fill the posterio-lateral portions of the head capsule in mature, older workers of both subcastes. Mandible closer fibers of newly eclosed workers, in contrast, are significantly thinner in both subcastes and grow during at least the next 6 days in minor workers, suggesting this muscle has reduced functionality for a substantial period of adult life and thus constrains task performance capability. Fibers of the antennal muscles and the pharynx dilator, which control antennal movements and food intake, respectively, also increase significantly in thickness with age. However, these fibers are only slightly thinner in newly eclosed workers and attain their maximum thickness over a shorter time span in minors. The different growth rates of these functionally distinct muscles likely have consequences for how adult P. dentata workers, particularly minors, develop their full and diverse task repertoire as they age. Workers may be capable of feeding and interacting socially soon after eclosion, but require a longer period of development to effectively use their mandibles, which enable the efficient performance of tasks ranging from nursing to foraging and defense.

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

    PubMed

    Wang, John; Wurm, Yannick; Nipitwattanaphon, Mingkwan; Riba-Grognuz, Oksana; Huang, Yu-Ching; Shoemaker, DeWayne; Keller, Laurent

    2013-01-31

    Intraspecific variability in social organization is common, yet the underlying causes are rarely known. In the fire ant Solenopsis invicta, the existence of two divergent forms of social organization is under the control of a single Mendelian genomic element marked by two variants of an odorant-binding protein gene. Here we characterize the genomic region responsible for this important social polymorphism, and show that it is part of a pair of heteromorphic chromosomes that have many of the key properties of sex chromosomes. The two variants, hereafter referred to as the social B and social b (SB and Sb) chromosomes, are characterized by a large region of approximately 13 megabases (55% of the chromosome) in which recombination is completely suppressed between SB and Sb. Recombination seems to occur normally between the SB chromosomes but not between Sb chromosomes because Sb/Sb individuals are non-viable. Genomic comparisons revealed limited differentiation between SB and Sb, and the vast majority of the 616 genes identified in the non-recombining region are present in the two variants. The lack of recombination over more than half of the two heteromorphic social chromosomes can be explained by at least one large inversion of around 9 megabases, and this absence of recombination has led to the accumulation of deleterious mutations, including repetitive elements in the non-recombining region of Sb compared with the homologous region of SB. Importantly, most of the genes with demonstrated expression differences between individuals of the two social forms reside in the non-recombining region. These findings highlight how genomic rearrangements can maintain divergent adaptive social phenotypes involving many genes acting together by locally limiting recombination.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection

    PubMed Central

    Liu, Zhiwen; Guo, Wei; Tang, Zhangchun; Chen, Yongqiang

    2015-01-01

    Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM) based on an ant colony optimization algorithm (ACO-RVM) for gearboxes’ fault detection. RVM is a sparse probability model based on support vector machine (SVM). RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD) is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET) is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV). PMID:26334280

  4. 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.

  5. 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.

  6. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection.

    PubMed

    Liu, Zhiwen; Guo, Wei; Tang, Zhangchun; Chen, Yongqiang

    2015-08-31

    Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM) based on an ant colony optimization algorithm (ACO-RVM) for gearboxes' fault detection. RVM is a sparse probability model based on support vector machine (SVM). RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD) is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET) is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV).

  7. Technological approaches to optimize colonial resistance control for humans in artificial environment

    NASA Astrophysics Data System (ADS)

    Viacheslav, Ilyin; Skedina, Marina; Muokhamedieva, Lana; Gegenava, Anna; Mardanov, Robert

    microflora in spaceflight, which was comparable to data obtained by classic bacteriology methods. The testings results allow to recommend this technology for colonial resistance control for humans in artificial environment.

  8. The Ants Have It!

    ERIC Educational Resources Information Center

    Daugherty, Belinda

    2001-01-01

    Uses the GEMS guide, "Ants at Home Underground", to explore the life of ants and teach about them in a classroom setting. The activity applies students' knowledge of ants and students learn about ant colonies, what ants eat, and how they live. (SAH)

  9. The Ants Have It!

    ERIC Educational Resources Information Center

    Daugherty, Belinda

    2001-01-01

    Uses the GEMS guide, "Ants at Home Underground", to explore the life of ants and teach about them in a classroom setting. The activity applies students' knowledge of ants and students learn about ant colonies, what ants eat, and how they live. (SAH)

  10. The cavity-nest ant Temnothorax crassispinus prefers larger nests.

    PubMed

    Mitrus, S

    Colonies of the ant Temnothorax crassispinus inhabit mostly cavities in wood and hollow acorns. Typically in the field, nest sites that can be used by the ant are a limited resource. In a field experiment, it was investigated whether the ants prefer a specific size of nest, when different ones are available. In July 2011, a total of 160 artificial nests were placed in a beech-pine forest. Four artificial nests (pieces of wood with volume cavities, ca 415, 605, 730, and 980 mm(3), respectively) were located on each square meter of the experimental plot. One year later, shortly before the emergence of new sexuals, the nests were collected. In July 2012, colonies inhabited more frequently bigger nests. Among queenright colonies, the ones which inhabited bigger nests had more workers. However, there was no relationship between volume of nest and number of workers for queenless colonies. Queenright colonies from bigger nests produced more sexual individuals, but there was no correlation between number of workers and sex allocation ratio, or between volume of nest and sex allocation ratio. In a laboratory experiment where ant colonies were kept in 470 and 860 mm(3) nests, larger colonies allocated more energy to produce sexual individuals. The results of this study show the selectivity of T. crassispinus ants regarding the size of nest cavity, and that the nest volume has an impact on life history parameters.

  11. Propagule pressure and colony social organization are associated with the successful invasion and rapid range expansion of fire ants in China.

    PubMed

    Yang, Chin-Cheng; Ascunce, Marina S; Luo, Li-Zhi; Shao, Jing-Guo; Shih, Cheng-Jen; Shoemaker, DeWayne

    2012-02-01

    We characterized patterns of genetic variation in populations of the fire ant Solenopsis invicta in China using mitochondrial DNA sequences and nuclear microsatellite loci to test predictions as to how propagule pressure and subsequent dispersal following establishment jointly shape the invasion success of this ant in this recently invaded area. Fire ants in Wuchuan (Guangdong Province) are genetically differentiated from those found in other large infested areas of China. The immediate source of ants in Wuchuan appears to be somewhere near Texas, which ranks first among the southern USA infested states in the exportation of goods to China. Most colonies from spatially distant, outlying areas in China are genetically similar to one another and appear to share a common source (Wuchuan, Guangdong Province), suggesting that long-distance jump dispersal has been a prevalent means of recent spread of fire ants in China. Furthermore, most colonies at outlier sites are of the polygyne social form (featuring multiple egg-laying queens per nest), reinforcing the important role of this social form in the successful invasion of new areas and subsequent range expansion following invasion. Several analyses consistently revealed characteristic signatures of genetic bottlenecks for S. invicta populations in China. The results of this study highlight the invasive potential of this pest ant, suggest that the magnitude of international trade may serve as a predictor of propagule pressure and indicate that rates and patterns of subsequent range expansion are partly determined by the interplay between species traits and the trade and transportation networks. © Published 2011. This article is a U.S. Government work and is in the public domain in the USA.

  12. Improved artificial bee colony algorithm for wavefront sensor-less system in free space optical communication

    NASA Astrophysics Data System (ADS)

    Niu, Chaojun; Han, Xiang'e.

    2015-10-01

    Adaptive optics (AO) technology is an effective way to alleviate the effect of turbulence on free space optical communication (FSO). A new adaptive compensation method can be used without a wave-front sensor. Artificial bee colony algorithm (ABC) is a population-based heuristic evolutionary algorithm inspired by the intelligent foraging behaviour of the honeybee swarm with the advantage of simple, good convergence rate, robust and less parameter setting. In this paper, we simulate the application of the improved ABC to correct the distorted wavefront and proved its effectiveness. Then we simulate the application of ABC algorithm, differential evolution (DE) algorithm and stochastic parallel gradient descent (SPGD) algorithm to the FSO system and analyze the wavefront correction capabilities by comparison of the coupling efficiency, the error rate and the intensity fluctuation in different turbulence before and after the correction. The results show that the ABC algorithm has much faster correction speed than DE algorithm and better correct ability for strong turbulence than SPGD algorithm. Intensity fluctuation can be effectively reduced in strong turbulence, but not so effective in week turbulence.

  13. Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation

    NASA Astrophysics Data System (ADS)

    Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.

    In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.

  14. A novel artificial bee colony algorithm based on internal-feedback strategy for image template matching.

    PubMed

    Li, Bai; Gong, Li-Gang; Li, Ya

    2014-01-01

    Image template matching refers to the technique of locating a given reference image over a source image such that they are the most similar. It is a fundamental mission in the field of visual target recognition. In general, there are two critical aspects of a template matching scheme. One is similarity measurement and the other is best-match location search. In this work, we choose the well-known normalized cross correlation model as a similarity criterion. The searching procedure for the best-match location is carried out through an internal-feedback artificial bee colony (IF-ABC) algorithm. IF-ABC algorithm is highlighted by its effort to fight against premature convergence. This purpose is achieved through discarding the conventional roulette selection procedure in the ABC algorithm so as to provide each employed bee an equal chance to be followed by the onlooker bees in the local search phase. Besides that, we also suggest efficiently utilizing the internal convergence states as feedback guidance for searching intensity in the subsequent cycles of iteration. We have investigated four ideal template matching cases as well as four actual cases using different searching algorithms. Our simulation results show that the IF-ABC algorithm is more effective and robust for this template matching mission than the conventional ABC and two state-of-the-art modified ABC algorithms do.

  15. Modified artificial bee colony for the vehicle routing problems with time windows.

    PubMed

    Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana

    2016-01-01

    The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW.

  16. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch.

    PubMed

    Yurtkuran, Alkın; Emel, Erdal

    2016-01-01

    The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.

  17. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    NASA Astrophysics Data System (ADS)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  18. A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

    PubMed Central

    Xu, Gaochao; Hu, Liang; Fu, Xiaodong

    2013-01-01

    Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful. PMID:24385877

  19. A novel artificial bee colony approach of live virtual machine migration policy using Bayes theorem.

    PubMed

    Xu, Gaochao; Ding, Yan; Zhao, Jia; Hu, Liang; Fu, Xiaodong

    2013-01-01

    Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

  20. Hyperspectral image clustering method based on artificial bee colony algorithm and Markov random fields

    NASA Astrophysics Data System (ADS)

    Sun, Xu; Yang, Lina; Gao, Lianru; Zhang, Bing; Li, Shanshan; Li, Jun

    2015-01-01

    Center-oriented hyperspectral image clustering methods have been widely applied to hyperspectral remote sensing image processing; however, the drawbacks are obvious, including the over-simplicity of computing models and underutilized spatial information. In recent years, some studies have been conducted trying to improve this situation. We introduce the artificial bee colony (ABC) and Markov random field (MRF) algorithms to propose an ABC-MRF-cluster model to solve the problems mentioned above. In this model, a typical ABC algorithm framework is adopted in which cluster centers and iteration conditional model algorithm's results are considered as feasible solutions and objective functions separately, and MRF is modified to be capable of dealing with the clustering problem. Finally, four datasets and two indices are used to show that the application of ABC-cluster and ABC-MRF-cluster methods could help to obtain better image accuracy than conventional methods. Specifically, the ABC-cluster method is superior when used for a higher power of spectral discrimination, whereas the ABC-MRF-cluster method can provide better results when used for an adjusted random index. In experiments on simulated images with different signal-to-noise ratios, ABC-cluster and ABC-MRF-cluster showed good stability.

  1. A novel artificial bee colony algorithm based on modified search equation and orthogonal learning.

    PubMed

    Gao, Wei-feng; Liu, San-yang; Huang, Ling-ling

    2013-06-01

    The artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, ABC has an insufficiency regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose an improved ABC method called as CABC where a modified search equation is applied to generate a candidate solution to improve the search ability of ABC. Furthermore, we use the orthogonal experimental design (OED) to form an orthogonal learning (OL) strategy for variant ABCs to discover more useful information from the search experiences. Owing to OED's good character of sampling a small number of well representative combinations for testing, the OL strategy can construct a more promising and efficient candidate solution. In this paper, the OL strategy is applied to three versions of ABC, i.e., the standard ABC, global-best-guided ABC (GABC), and CABC, which yields OABC, OGABC, and OCABC, respectively. The experimental results on a set of 22 benchmark functions demonstrate the effectiveness and efficiency of the modified search equation and the OL strategy. The comparisons with some other ABCs and several state-of-the-art algorithms show that the proposed algorithms significantly improve the performance of ABC. Moreover, OCABC offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all the test functions.

  2. Enhanced probability-selection artificial bee colony algorithm for economic load dispatch: A comprehensive analysis

    NASA Astrophysics Data System (ADS)

    Ghani Abro, Abdul; Mohamad-Saleh, Junita

    2014-10-01

    The prime motive of economic load dispatch (ELD) is to optimize the production cost of electrical power generation through appropriate division of load demand among online generating units. Bio-inspired optimization algorithms have outperformed classical techniques for optimizing the production cost. Probability-selection artificial bee colony (PS-ABC) algorithm is a recently proposed variant of ABC optimization algorithm. PS-ABC generates optimal solutions using three different mutation equations simultaneously. The results show improved performance of PS-ABC over the ABC algorithm. Nevertheless, all the mutation equations of PS-ABC are excessively self-reinforced and, hence, PS-ABC is prone to premature convergence. Therefore, this research work has replaced the mutation equations and has improved the scout-bee stage of PS-ABC for enhancing the algorithm's performance. The proposed algorithm has been compared with many ABC variants and numerous other optimization algorithms on benchmark functions and ELD test cases. The adapted ELD test cases comprise of transmission losses, multiple-fuel effect, valve-point effect and toxic gases emission constraints. The results reveal that the proposed algorithm has the best capability to yield the optimal solution for the problem among the compared algorithms.

  3. A Novel Artificial Bee Colony Algorithm Based on Internal-Feedback Strategy for Image Template Matching

    PubMed Central

    Gong, Li-Gang

    2014-01-01

    Image template matching refers to the technique of locating a given reference image over a source image such that they are the most similar. It is a fundamental mission in the field of visual target recognition. In general, there are two critical aspects of a template matching scheme. One is similarity measurement and the other is best-match location search. In this work, we choose the well-known normalized cross correlation model as a similarity criterion. The searching procedure for the best-match location is carried out through an internal-feedback artificial bee colony (IF-ABC) algorithm. IF-ABC algorithm is highlighted by its effort to fight against premature convergence. This purpose is achieved through discarding the conventional roulette selection procedure in the ABC algorithm so as to provide each employed bee an equal chance to be followed by the onlooker bees in the local search phase. Besides that, we also suggest efficiently utilizing the internal convergence states as feedback guidance for searching intensity in the subsequent cycles of iteration. We have investigated four ideal template matching cases as well as four actual cases using different searching algorithms. Our simulation results show that the IF-ABC algorithm is more effective and robust for this template matching mission than the conventional ABC and two state-of-the-art modified ABC algorithms do. PMID:24892107

  4. 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

  5. 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.

  6. An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem

    PubMed Central

    Shmygelska, Alena; Hoos, Holger H

    2005-01-01

    Background The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model – the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model. Results We present an improvement of our previous ACO algorithm for the 2D HP model and its extension to the 3D HP model. We show that this new algorithm, dubbed ACO-HPPFP-3, performs better than previous state-of-the-art algorithms on sequences whose native conformations do not contain structural nuclei (parts of the native fold that predominantly consist of local interactions) at the ends, but rather in the middle of the sequence, and that it generally finds a more diverse set of native conformations. Conclusions The application of ACO to this bioinformatics problem compares favourably with specialised, state-of-the-art methods for the 2D and 3D HP protein folding problem; our empirical results indicate that our rather simple ACO algorithm scales worse with sequence length but usually finds a more diverse ensemble of native states. Therefore the development of ACO algorithms for more complex and realistic models of protein structure holds significant promise. PMID:15710037

  7. Feature selection using ant colony optimization with tandem-run recruitment to diagnose bronchitis from CT scan images.

    PubMed

    Sweetlin, J Dhalia; Nehemiah, H Khanna; Kannan, A

    2017-07-01

    Computer-aided diagnosis (CAD) plays a vital role in the routine clinical activity for the detection of lung disorders using computed tomography (CT) images. It serves as a source of second opinion that radiologists may consider in order to interpret CT images. In this work, the purpose of CAD is to improve the diagnostic accuracy of pulmonary bronchitis from CT images of the lung. Left and right lung fields are segmented using optimal thresholding from the lung CT images. Texture and shape features are extracted from the pathology bearing regions. A hybrid feature selection approach based on ant colony optimization (ACO) combining cosine similarity and support vector machine (SVM) classifier is used to select relevant features. Additionally, tandem run recruitment strategy is included in the selection activity to choose the promising features. The SVM classifier is trained using the selected features and the performance of the trained classifier is evaluated using trivial performance evaluation measures. The training and testing datasets used in building the classifier model are disjoint and contains 200 CT slices affected with bronchitis, 50 normal slices and 300 slices with cancer. Out of 100 features extracted from each CT slice, a subset of 60 features is used for classification. ACO with tandem run strategy yielded 81.66% of accuracy whereas ACO without tandem run yielded an accuracy of 77.52%. When all the features are used for classifier training without feature selection algorithm, an accuracy of 75.14% is achieved. From the results, it is inferred that identifying relevant features to train the classifier has a definite impact on the classifier performance. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Optimization of Spherical Roller Bearing Design Using Artificial Bee Colony Algorithm and Grid Search Method

    NASA Astrophysics Data System (ADS)

    Tiwari, Rajiv; Waghole, Vikas

    2015-07-01

    Bearing standards impose restrictions on the internal geometry of spherical roller bearings. Geometrical and strength constraints conditions have been formulated for the optimization of bearing design. The long fatigue life is one of the most important criteria in the optimum design of bearing. The life is directly proportional to the dynamic capacity; hence, the objective function has been chosen as the maximization of dynamic capacity. The effect of speed and static loads acting on the bearing are also taken into account. Design variables for the bearing include five geometrical parameters: the roller diameter, the roller length, the bearing pitch diameter, the number of rollers, and the contact angle. There are a few design constraint parameters which are also included in the optimization, the bounds of which are obtained by initial runs of the optimization. The optimization program is made to run for different values of these design constraint parameters and a range of the parameters is obtained for which the objective function has a higher value. The artificial bee colony algorithm (ABCA) has been used to solve the constrained optimized problem and the optimum design is compared with the one obtained from the grid search method (GSM), both operating independently. Both the ABCA and the GSM have been finally combined together to reach the global optimum point. A constraint violation study has also been carried out to give priority to the constraint having greater possibility of violations. Optimized bearing designs show a better performance parameter with those specified in bearing catalogs. The sensitivity analysis of bearing parameters has also been carried out to see the effect of manufacturing tolerance on the objective function.

  9. Colony density and activity times of the ant Camponotus semitestaceus (Hymenoptera: formicidae) in a shrub steppe community

    SciTech Connect

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (anti-x +/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites an

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. A World of Ants.

    ERIC Educational Resources Information Center

    Flannery, Maura C.

    1992-01-01

    Presents a discussion of interesting aspects of ants that was launched by the author's reading of "The Ants" by Holldobler and Wilson (1990). Describes how the study of the early history of ant taxonomy could be viewed as "entertaining." Their huge numbers and segregation into colonial social systems makes ants good research organisms. (PR)

  15. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators of use in cancer therapy

    NASA Astrophysics Data System (ADS)

    García-Pareja, S.; Vilches, M.; Lallena, A. M.

    2010-01-01

    The Monte Carlo simulation of clinical electron linear accelerators requires large computation times to achieve the level of uncertainty required for radiotherapy. In this context, variance reduction techniques play a fundamental role in the reduction of this computational time. Here we describe the use of the ant colony method to control the application of two variance reduction techniques: Splitting and Russian roulette. The approach can be applied to any accelerator in a straightforward way and permits the increasing of the efficiency of the simulation by a factor larger than 50.

  16. Nectar intake rate is modulated by changes in sucking pump activity according to colony starvation in carpenter ants.

    PubMed

    Falibene, Agustina; Josens, Roxana

    2008-05-01

    Dynamics of fluid feeding has been deeply studied in insects. However, the ability to vary the nectar-intake rate depending only on the carbohydrate deprivation has been clearly demonstrated only in Camponotus mus ants. When insect morphometry and fluid properties remain constant, changes in intake rate could only be attributed to variations in sucking pump activity. Previous records of the electrical activity generated during feeding in C. mus have revealed two different signal patterns: the regular (RP, frequencies: 2-5 Hz) and the irregular (IP, frequencies: 7-12 Hz). This work studies the mechanism underlying food intake-rate modulation in ants by analysing whether these patterns are involved. Behaviour and electrical activity generated by ants at different starvation levels were analysed during feeding on sucrose solutions. Ants were able to modulate the intake rate for a variety of sucrose concentrations (10, 40 and 60%w/w). The IP only occurred for 60% of solutions and its presence did not affect the intake rate. However, during the RP generated under the starved state, we found frequencies up to 7.5 Hz. RP frequencies positively correlated with the intake-rate for all sucrose concentrations. Hence, intake-rate modulation according to sugar deprivation is mainly achieved by the ant's ability to vary the pumping frequency.

  17. Identification of cultivated land using remote sensing images based on object-oriented artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Li, Nan; Zhu, Xiufang

    2017-04-01

    Cultivated land resources is the key to ensure food security. Timely and accurate access to cultivated land information is conducive to a scientific planning of food production and management policies. The GaoFen 1 (GF-1) images have high spatial resolution and abundant texture information and thus can be used to identify fragmentized cultivated land. In this paper, an object-oriented artificial bee colony algorithm was proposed for extracting cultivated land from GF-1 images. Firstly, the GF-1 image was segmented by eCognition software and some samples from the segments were manually identified into 2 types (cultivated land and non-cultivated land). Secondly, the artificial bee colony (ABC) algorithm was used to search for classification rules based on the spectral and texture information extracted from the image objects. Finally, the extracted classification rules were used to identify the cultivated land area on the image. The experiment was carried out in Hongze area, Jiangsu Province using wide field-of-view sensor on the GF-1 satellite image. The total precision of classification result was 94.95%, and the precision of cultivated land was 92.85%. The results show that the object-oriented ABC algorithm can overcome the defect of insufficient spectral information in GF-1 images and obtain high precision in cultivated identification.

  18. An Experimental Approach for Optimizing Coating Parameters of Electroless Ni-P-Cu Coating Using Artificial Bee Colony Algorithm.

    PubMed

    Roy, Supriyo; Sahoo, Prasanta

    2014-01-01

    This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively.

  19. An Experimental Approach for Optimizing Coating Parameters of Electroless Ni-P-Cu Coating Using Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively. PMID:27382630

  20. Context-dependent expression of the foraging gene in field colonies of ants: the interacting roles of age, environment and task

    PubMed Central

    Gordon, Deborah M.; Greene, Michael; Kahler, John; Peteru, Swetha

    2016-01-01

    Task allocation among social insect workers is an ideal framework for studying the molecular mechanisms underlying behavioural plasticity because workers of similar genotype adopt different behavioural phenotypes. Elegant laboratory studies have pioneered this effort, but field studies involving the genetic regulation of task allocation are rare. Here, we investigate the expression of the foraging gene in harvester ant workers from five age- and task-related groups in a natural population, and we experimentally test how exposure to light affects foraging expression in brood workers and foragers. Results from our field study show that the regulation of the foraging gene in harvester ants occurs at two time scales: levels of foraging mRNA are associated with ontogenetic changes over weeks in worker age, location and task, and there are significant daily oscillations in foraging expression in foragers. The temporal dissection of foraging expression reveals that gene expression changes in foragers occur across a scale of hours and the level of expression is predicted by activity rhythms: foragers have high levels of foraging mRNA during daylight hours when they are most active outside the nests. In the experimental study, we find complex interactions in foraging expression between task behaviour and light exposure. Oscillations occur in foragers following experimental exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar conditions. No significant differences were seen in foraging expression over time in either task in 24 h dark (DD) conditions. Interestingly, the expression of foraging in both undisturbed field and experimentally treated foragers is also significantly correlated with the expression of the circadian clock gene, cycle. Our results provide evidence that the regulation of this gene is context-dependent and associated with both ontogenetic and daily behavioural plasticity in field colonies of harvester ants. Our results underscore

  1. Context-dependent expression of the foraging gene in field colonies of ants: the interacting roles of age, environment and task.

    PubMed

    Ingram, Krista K; Gordon, Deborah M; Friedman, Daniel A; Greene, Michael; Kahler, John; Peteru, Swetha

    2016-08-31

    Task allocation among social insect workers is an ideal framework for studying the molecular mechanisms underlying behavioural plasticity because workers of similar genotype adopt different behavioural phenotypes. Elegant laboratory studies have pioneered this effort, but field studies involving the genetic regulation of task allocation are rare. Here, we investigate the expression of the foraging gene in harvester ant workers from five age- and task-related groups in a natural population, and we experimentally test how exposure to light affects foraging expression in brood workers and foragers. Results from our field study show that the regulation of the foraging gene in harvester ants occurs at two time scales: levels of foraging mRNA are associated with ontogenetic changes over weeks in worker age, location and task, and there are significant daily oscillations in foraging expression in foragers. The temporal dissection of foraging expression reveals that gene expression changes in foragers occur across a scale of hours and the level of expression is predicted by activity rhythms: foragers have high levels of foraging mRNA during daylight hours when they are most active outside the nests. In the experimental study, we find complex interactions in foraging expression between task behaviour and light exposure. Oscillations occur in foragers following experimental exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar conditions. No significant differences were seen in foraging expression over time in either task in 24 h dark (DD) conditions. Interestingly, the expression of foraging in both undisturbed field and experimentally treated foragers is also significantly correlated with the expression of the circadian clock gene, cycle Our results provide evidence that the regulation of this gene is context-dependent and associated with both ontogenetic and daily behavioural plasticity in field colonies of harvester ants. Our results underscore

  2. Foraging Habitat Quality Constrains Effectiveness of Artificial Nest-Site Provisioning in Reversing Population Declines in a Colonial Cavity Nester

    PubMed Central

    Catry, Inês; Franco, Aldina M. A.; Rocha, Pedro; Alcazar, Rita; Reis, Susana; Cordeiro, Ana; Ventim, Rita; Teodósio, Joaquim; Moreira, Francisco

    2013-01-01

    Among birds, breeding numbers are mainly limited by two resources of major importance: food supply and nest-site availability. Here, we investigated how differences in land-use and nest-site availability affected the foraging behaviour, breeding success and population trends of the colonial cavity-dependent lesser kestrel Falco naumanni inhabiting two protected areas. Both areas were provided with artificial nests to increase nest-site availability. The first area is a pseudo-steppe characterized by traditional extensive cereal cultivation, whereas the second area is a previous agricultural zone now abandoned or replaced by forested areas. In both areas, lesser kestrels selected extensive agricultural habitats, such as fallows and cereal fields, and avoided scrubland and forests. In the second area, tracked birds from one colony travelled significantly farther distances (6.2 km ±1.7 vs. 1.8 km ±0.4 and 1.9 km ±0.6) and had significant larger foraging-ranges (144 km2 vs. 18.8 and 14.8 km2) when compared to the birds of two colonies in the extensive agricultural area. Longer foraging trips were reflected in lower chick feeding rates, lower fledging success and reduced chick fitness. Availability and occupation of artificial nests was high in both areas but population followed opposite trends, with a positive increment recorded exclusively in the first area with a large proportion of agricultural areas. Progressive habitat loss around the studied colony in the second area (suitable habitat decreased from 32% in 1990 to only 7% in 2002) is likely the main driver of the recorded population decline and suggests that the effectiveness of bird species conservation based on nest-site provisioning is highly constrained by habitat quality in the surrounding areas. Therefore, the conservation of cavity-dependent species may be enhanced firstly by finding the best areas of remaining habitat and secondly by increasing the carrying capacity of high-quality habitat areas

  3. Foraging habitat quality constrains effectiveness of artificial nest-site provisioning in reversing population declines in a colonial cavity nester.

    PubMed

    Catry, Inês; Franco, Aldina M A; Rocha, Pedro; Alcazar, Rita; Reis, Susana; Cordeiro, Ana; Ventim, Rita; Teodósio, Joaquim; Moreira, Francisco

    2013-01-01

    Among birds, breeding numbers are mainly limited by two resources of major importance: food supply and nest-site availability. Here, we investigated how differences in land-use and nest-site availability affected the foraging behaviour, breeding success and population trends of the colonial cavity-dependent lesser kestrel Falco naumanni inhabiting two protected areas. Both areas were provided with artificial nests to increase nest-site availability. The first area is a pseudo-steppe characterized by traditional extensive cereal cultivation, whereas the second area is a previous agricultural zone now abandoned or replaced by forested areas. In both areas, lesser kestrels selected extensive agricultural habitats, such as fallows and cereal fields, and avoided scrubland and forests. In the second area, tracked birds from one colony travelled significantly farther distances (6.2 km ± 1.7 vs. 1.8 km ± 0.4 and 1.9 km ± 0.6) and had significant larger foraging-ranges (144 km(2) vs. 18.8 and 14.8 km(2)) when compared to the birds of two colonies in the extensive agricultural area. Longer foraging trips were reflected in lower chick feeding rates, lower fledging success and reduced chick fitness. Availability and occupation of artificial nests was high in both areas but population followed opposite trends, with a positive increment recorded exclusively in the first area with a large proportion of agricultural areas. Progressive habitat loss around the studied colony in the second area (suitable habitat decreased from 32% in 1990 to only 7% in 2002) is likely the main driver of the recorded population decline and suggests that the effectiveness of bird species conservation based on nest-site provisioning is highly constrained by habitat quality in the surrounding areas. Therefore, the conservation of cavity-dependent species may be enhanced firstly by finding the best areas of remaining habitat and secondly by increasing the carrying capacity of high-quality habitat areas

  4. A novel kernel extreme learning machine algorithm based on self-adaptive artificial bee colony optimisation strategy

    NASA Astrophysics Data System (ADS)

    Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Ji, Jin-Chao

    2016-04-01

    In this paper, we propose a novel learning algorithm, named SABC-MKELM, based on a kernel extreme learning machine (KELM) method for single-hidden-layer feedforward networks. In SABC-MKELM, the combination of Gaussian kernels is used as the activate function of KELM instead of simple fixed kernel learning, where the related parameters of kernels and the weights of kernels can be optimised by a novel self-adaptive artificial bee colony (SABC) approach simultaneously. SABC-MKELM outperforms six other state-of-the-art approaches in general, as it could effectively determine solution updating strategies and suitable parameters to produce a flexible kernel function involved in SABC. Simulations have demonstrated that the proposed algorithm not only self-adaptively determines suitable parameters and solution updating strategies learning from the previous experiences, but also achieves better generalisation performances than several related methods, and the results show good stability of the proposed algorithm.

  5. An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

    PubMed

    Li, Bai; Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

  6. An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

    PubMed Central

    Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555

  7. Comparative Study on Synthesizing Reconfigurable Time- Modulated Linear Arrays using Differential Evolution, Artificial Bee Colony and Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Mandal, S. K.; Singh, Harshavardhan; Mahanti, G. K.; Ghatak, Rowdra

    2014-10-01

    This paper presents a new technique based on optimization tools to design phase only, digitally controlled, reconfigurable antenna arrays through time modulation. In the proposed approach, the on-time durations of the time-modulated elements and the static amplitudes of the array elements are perturbed in such a way that the same on-time sequence and discrete values of static amplitudes for four bit digital attenuators produces either a pencil or a flat-top beam pattern, depending on the suitable discrete phase distributions of five bit digital phase shifters. In order to illustrate the technique, three optimization tools: differential evolution (DE), artificial bee colony (ABC), and particle swarm optimization (PSO) are employed and their performances are compared. The numerical results for a 20-element linear array are presented.

  8. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    PubMed Central

    Yilmaz, Nihat; Inan, Onur

    2013-01-01

    This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications. PMID:23983632

  9. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    PubMed

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  10. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    PubMed Central

    Mohamed, Ahmed F.; Elarini, Mahdi M.; Othman, Ahmed M.

    2013-01-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt. PMID:25685507

  11. Construction of recombinant Escherichia coli strains for secretory expression of artificial genes for human granulocyte-macrophage colony stimulating factor

    SciTech Connect

    Petrovskaya, L.E.; Ruzin, A.V.; Shingarova, L.N.; Korobko, V.G.

    1995-11-01

    A number of recombinant plasmids for expression of artificial genes encoding human granulocyte-macrophage colony stimulating factor (GM-CSF) were constructed. A hybrid gene was obtained that contains a sequence encoding the leader peptide and a tandem of two IgG-binding domains of protein A from Staphylococcus aureus coupled, through an enteropepdidase linker, to a synthetic gmcsf gene. The construction enables Escherichia coli to carry out biosynthesis of the hybrid protein and its subsequent transport into the periplasmic space of bacteria. Another hybrid gene, combining sequences for the signal peptide of the E. coli outer membrane protein OmpA and GM-CSF, was obtained using polymerase chain reaction. The localization of the mature protein produced by the hybrid gene was found to depend on the strength of the promoter used. 39 refs., 6 figs.

  12. 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.

  13. Maintenance of a laboratory colony of Cimex lectularius (Hemiptera: Cimicidae) using an artificial feeding technique.

    PubMed

    Montes, C; Cuadrillero, C; Vilella, D

    2002-07-01

    The in vitro maintenance technique described in this article has been used successfully to rear Cimex lectularius (L.) by feeding for >2 yr all nymphal stages and adults through parafilm "M" sealing film on different types of blood. Using this feeding technique, the subsequent egg production of female bedbugs was remarkably high. The blood was maintained at 37 degrees C to enhance the attachment of the bugs. The effect of anticoagulation methods for the blood meal was investigated, and heparinized blood was found the most suitable for feeding bugs. All stages of the bugs fed weekly on blood in the artificial feeding system remained attached for up to 0.5-1.0 h, until completion of their blood meals, and all reached engorged weights. More than 90% of the bugs fed artificially on whole blood, and they molted or laid eggs successfully.

  14. Colony density and activity times of the ant Camponotus semitestaceus (hymenoptera:formicidae) in a shrub steppe community

    SciTech Connect

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (x +/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites and 0.028 +/- 0.028 per m/sup 2/ on a burned site. Seventy-five percent of the nest entrances were located alongside the stems of sagebrush, indicating a preference for these microhabitats as nest locations. Above-ground activity times were determined by using time lapse photography. Activity commenced shortly after sunset, when light intensities dropped to 2.5 to 1.0 foot-candles (ca. 27 to 11 lux) and terminated just before sunrise. Light intensity appears to be the primary cue for controlling above-ground activity periods of this species, but temperature also appears to be an important factor. When soil surface temperatures drop to 1.7 to 3.9/sup 0/C, all above-ground activity ceases, irrespective of light intensity. 19 references, 3 figures, 2 tables.

  15. Colony density and activity times of the ant Camponotus semitestaceus (hymenoptera: Formicidae) in a shrub steppe community

    SciTech Connect

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (anti x=/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites and 0.028 +/- 0.028 per m/sup 2/ on a burned site. Seventy-five percent of the nest entrances were located alongside the stems of sagebrush, indicating a preference for these microhabitats as nest locations. Above-ground activity times were determined by using time lapse photography. Activity commenced shortly after sunset, when light intensities dropped to 2.5 to 1.0 foot-candles (ca. 27 to 11 lux) and terminated just before sunrise. Light intensity appears to be the primary cue for controlling above-ground activity periods of this species, but temperature also appears to be an important factor. When soil surface temperatures drop to 1.7 to 3.9/sup 0/C, all above-ground activity ceases, irrespective of light intensity.

  16. Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm.

    PubMed

    Li, Bai; Lin, Mu; Liu, Qiao; Li, Ya; Zhou, Changjun

    2015-10-01

    Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques.

  17. Ultrasound intima-media thickness measurement of the carotid artery using ant colony optimization combined with a curvelet-based orientation-selective filter.

    PubMed

    Li, Hao; Zhang, Shijie; Ma, Rui; Chen, Huiren; Xi, Shui; Zhang, Jue; Fang, Jing

    2016-04-01

    Automatic measurement of the intima-media thickness (IMT) from ultrasound carotid images is an important task in clinical diagnosis. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. However, the robustness of the algorithms would be influenced by the inherent speckle noise of ultrasound image. This paper proposed a curvelet guided ant colony optimization (CGACO) strategy that could achieve satisfied accuracy for IMT measurement with improved robustness to noise. The curvelet-based orientation-selective (CBOS) filter was first introduced for speckle removal and edge enhancement. Different from conventional methods, CBOS filter processes the curvelet coefficients by orientations rather than by magnitude. Then, a specially designed two-leg ant colony optimization technique, combined with Otsu thresholding and Sobel edge detector, was proposed as a novel segmentation method to extract the media-adventitia (MA) and the lumen-intima (LI) boundaries. Finally, a coupled snake model was employed to further smooth the contours of MA and LI. In addition to 224 carotid artery images acquired from 34 participants, simulated speckled images with nine levels of noise were also included in the database. The mean absolute distance errors of CGACO for LI interface tracings, MA interface tracings, and IMT measurements were 0.030 ± 0.027, 0.039 ± 0.036, and 0.041 ± 0.036 mm, respectively. Besides, CGACO had a correlation coefficient as high as 0.992 and a bias as low as -0.008. All these measures were comparable to or better than a previous technique and the manual segmentation. On the other hand, CGACO had the highest success rate of 98.7% in the segmentation of real data. It also maintained a much higher success rate in the segmentation of simulated images with different levels of speckle noise. The proposed technique showed accurate IMT measurement results. Furthermore, benefiting from the CBOS filter, the

  18. 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.

  19. 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.

  20. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    NASA Astrophysics Data System (ADS)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  1. Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

  2. A discrete artificial bee colony algorithm incorporating differential evolution for the flow-shop scheduling problem with blocking

    NASA Astrophysics Data System (ADS)

    Han, Yu-Yan; Gong, Dunwei; Sun, Xiaoyan

    2015-07-01

    A flow-shop scheduling problem with blocking has important applications in a variety of industrial systems but is underrepresented in the research literature. In this study, a novel discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE). The proposed algorithm (DE-ABC) contains three key operators. One is related to the employed bee operator (i.e. adopting mutation and crossover operators of discrete DE to generate solutions with good quality); the second is concerned with the onlooker bee operator, which modifies the selected solutions using insert or swap operators based on the self-adaptive strategy; and the last is for the local search, that is, the insert-neighbourhood-based local search with a small probability is adopted to improve the algorithm's capability in exploitation. The performance of the proposed DE-ABC algorithm is empirically evaluated by applying it to well-known benchmark problems. The experimental results show that the proposed algorithm is superior to the compared algorithms in minimizing the makespan criterion.

  3. Modeling design iteration in product design and development and its solution by a novel artificial bee colony algorithm.

    PubMed

    Chen, Tinggui; Xiao, Renbin

    2014-01-01

    Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.

  4. Small and Dim Target Detection via Lateral Inhibition Filtering and Artificial Bee Colony Based Selective Visual Attention

    PubMed Central

    Duan, Haibin; Deng, Yimin; Wang, Xiaohua; Xu, Chunfang

    2013-01-01

    This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus’ ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain the interested object to carry through the following recognition operation. In order to eliminate the camera motion influence, this paper adopted ABC algorithm, a new optimization method inspired by swarm intelligence, to calculate the motion salience map to integrate with conventional visual attention. To prove the feasibility and effectiveness of our method, several experiments were conducted. First the filtering results of lateral inhibition filter were shown to illustrate its noise reducing effect, then we applied the ABC algorithm to obtain the motion features of the image sequence. The ABC algorithm is proved to be more robust and effective through the comparison between ABC algorithm and popular Particle Swarm Optimization (PSO) algorithm. Except for the above results, we also compared the classic visual attention mechanism and our ABC algorithm based visual attention mechanism, and the experimental results of which further verified the effectiveness of our method. PMID:23991033

  5. 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.

  6. A hybrid of ant colony optimization and minimization of metabolic adjustment to improve the production of succinic acid in Escherichia coli.

    PubMed

    Chong, Shiue Kee; Mohamad, Mohd Saberi; Mohamed Salleh, Abdul Hakim; Choon, Yee Wen; Chong, Chuii Khim; Deris, Safaai

    2014-06-01

    This paper presents a study on gene knockout strategies to identify candidate genes to be knocked out for improving the production of succinic acid in Escherichia coli. Succinic acid is widely used as a precursor for many chemicals, for example production of antibiotics, therapeutic proteins and food. However, the chemical syntheses of succinic acid using the traditional methods usually result in the production that is far below their theoretical maximums. In silico gene knockout strategies are commonly implemented to delete the gene in E. coli to overcome this problem. In this paper, a hybrid of Ant Colony Optimization (ACO) and Minimization of Metabolic Adjustment (MoMA) is proposed to identify gene knockout strategies to improve the production of succinic acid in E. coli. As a result, the hybrid algorithm generated a list of knockout genes, succinic acid production rate and growth rate for E. coli after gene knockout. The results of the hybrid algorithm were compared with the previous methods, OptKnock and MOMAKnock. It was found that the hybrid algorithm performed better than OptKnock and MOMAKnock in terms of the production rate. The information from the results produced from the hybrid algorithm can be used in wet laboratory experiments to increase the production of succinic acid in E. coli. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. 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...

  8. [Chaotic artificial bee colony algorithm: a new approach to the problem of minimization of energy of the 3D protein structure].

    PubMed

    Wang, Y; Guo, G D; Chen, L F

    2013-01-01

    Frediction of the three-dimensional structure of a protein from its amino acid sequence can be considered as a global optimization problem. In this paper, the Chaotic Artificial Bee Colony (CABC) algorithm was introduced and applied to 3D protein structure prediction. Based on the 3D off-lattice AB model, the CABC algorithm combines global search and local search of the Artificial Bee Colony (ABC) algorithm with the Chaotic search algorithm to avoid the problem of premature convergence and easily trapping the local optimum solution. The experiments carried out with the popular Fibonacci sequences demonstrate that the proposed algorithm provides an effective and high-performance method for protein structure prediction.

  9. An adaptive ant colony optimization framework for scheduling environmental flow management alternatives under varied environmental water availability conditions

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    Human water use is increasing and, as such, water for the environment is limited and needs to be managed efficiently. One method for achieving this is the scheduling of environmental flow management alternatives (EFMAs) (e.g., releases, wetland regulators), with these schedules generally developed over a number of years. However, the availability of environmental water changes annually as a result of natural variability (e.g., drought, wet years). To incorporate this variation and schedule EFMAs in a operational setting, a previously formulated multiobjective optimization approach for EFMA schedule development used for long-term planning has been modified and incorporated into an adaptive framework. As part of this approach, optimal schedules are updated at regular intervals during the planning horizon based on environmental water allocation forecasts, which are obtained using artificial neural networks. In addition, the changes between current and updated schedules can be minimized to reduce any disruptions to long-term planning. The utility of the approach is assessed by applying it to an 89km section of the River Murray in South Australia. Results indicate that the approach is beneficial under a range of hydrological conditions and an improved ecological response is obtained in a operational setting compared with previous long-term approaches. Also, it successfully produces trade-offs between the number of disruptions to schedules and the ecological response, with results suggesting that ecological response increases with minimal alterations required to existing schedules. Overall, the results indicate that the information obtained using the proposed approach potentially aides managers in the efficient management of environmental water.

  10. A novel approach to speckle noise filtering based on Artificial Bee Colony algorithm: an ultrasound image application.

    PubMed

    Latifoğlu, Fatma

    2013-09-01

    In this study a novel approach based on 2D FIR filters is presented for denoising digital images. In this approach the filter coefficients of 2D FIR filters were optimized using the Artificial Bee Colony (ABC) algorithm. To obtain the best filter design, the filter coefficients were tested with different numbers (3×3, 5×5, 7×7, 11×11) and connection types (cascade and parallel) during optimization. First, the speckle noise with variances of 1, 0.6, 0.8 and 0.2 respectively was added to the synthetic test image. Later, these noisy images were denoised with both the proposed approach and other well-known filter types such as Gaussian, mean and average filters. For image quality determination metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) were used. Even in the case of noise having maximum variance (the most noisy), the proposed approach performed better than other filtering methods did on the noisy test images. In addition to test images, speckle noise with a variance of 1 was added to a fetal ultrasound image, and this noisy image was denoised with very high PSNR and SNR values. The performance of the proposed approach was also tested on several clinical ultrasound images such as those obtained from ovarian, abdomen and liver tissues. The results of this study showed that the 2D FIR filters designed based on ABC optimization can eliminate speckle noise quite well on noise added test images and intrinsically noisy ultrasound images. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  11. 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.

  12. Distributed nestmate recognition in ants

    PubMed Central

    Esponda, Fernando; Gordon, Deborah M.

    2015-01-01

    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. PMID:25833853

  13. Avoidance of plants unsuitable for the symbiotic fungus in leaf-cutting ants: Learning can take place entirely at the colony dump

    PubMed Central

    Roces, Flavio

    2017-01-01

    Plants initially accepted by foraging leaf-cutting ants are later avoided if they prove unsuitable for their symbiotic fungus. Plant avoidance is mediated by the waste produced in the fungus garden soon after the incorporation of the unsuitable leaves, as foragers can learn plant odors and cues from the damaged fungus that are both present in the recently produced waste particles. We asked whether avoidance learning of plants unsuitable for the symbiotic fungus can take place entirely at the colony dump. In order to investigate whether cues available in the waste chamber induce plant avoidance in naïve subcolonies, we exchanged the waste produced by subcolonies fed either fungicide-treated privet leaves or untreated leaves and measured the acceptance of untreated privet leaves before and after the exchange of waste. Second, we evaluated whether foragers could perceive the avoidance cues directly at the dump by quantifying the visits of labeled foragers to the waste chamber. Finally, we asked whether foragers learn to specifically avoid untreated leaves of a plant after a confinement over 3 hours in the dump of subcolonies that were previously fed fungicide-treated leaves of that species. After the exchange of the waste chambers, workers from subcolonies that had access to waste from fungicide-treated privet leaves learned to avoid that plant. One-third of the labeled foragers visited the dump. Furthermore, naïve foragers learned to avoid a specific, previously unsuitable plant if exposed solely to cues of the dump during confinement. We suggest that cues at the dump enable foragers to predict the unsuitable effects of plants even if they had never been experienced in the fungus garden. PMID:28273083

  14. Avoidance of plants unsuitable for the symbiotic fungus in leaf-cutting ants: Learning can take place entirely at the colony dump.

    PubMed

    Arenas, Andrés; Roces, Flavio

    2017-01-01

    Plants initially accepted by foraging leaf-cutting ants are later avoided if they prove unsuitable for their symbiotic fungus. Plant avoidance is mediated by the waste produced in the fungus garden soon after the incorporation of the unsuitable leaves, as foragers can learn plant odors and cues from the damaged fungus that are both present in the recently produced waste particles. We asked whether avoidance learning of plants unsuitable for the symbiotic fungus can take place entirely at the colony dump. In order to investigate whether cues available in the waste chamber induce plant avoidance in naïve subcolonies, we exchanged the waste produced by subcolonies fed either fungicide-treated privet leaves or untreated leaves and measured the acceptance of untreated privet leaves before and after the exchange of waste. Second, we evaluated whether foragers could perceive the avoidance cues directly at the dump by quantifying the visits of labeled foragers to the waste chamber. Finally, we asked whether foragers learn to specifically avoid untreated leaves of a plant after a confinement over 3 hours in the dump of subcolonies that were previously fed fungicide-treated leaves of that species. After the exchange of the waste chambers, workers from subcolonies that had access to waste from fungicide-treated privet leaves learned to avoid that plant. One-third of the labeled foragers visited the dump. Furthermore, naïve foragers learned to avoid a specific, previously unsuitable plant if exposed solely to cues of the dump during confinement. We suggest that cues at the dump enable foragers to predict the unsuitable effects of plants even if they had never been experienced in the fungus garden.

  15. Prediction of acute toxicity of emerging contaminants on the water flea Daphnia magna by Ant Colony Optimization-Support Vector Machine QSTR models.

    PubMed

    Aalizadeh, Reza; von der Ohe, Peter C; Thomaidis, Nikolaos S

    2017-03-22

    According to the European REACH Directive, the acute toxicity towards Daphnia magna should be assessed for any industrial chemical with a market volume of more than 1 t/a. Therefore, it is highly recommended to determine the toxicity at a certain confidence level, either experimentally or by applying reliable prediction models. To this end, a large dataset was compiled, with the experimental acute toxicity values (pLC50) of 1353 compounds in Daphnia magna after 48 h of exposure. A novel quantitative structure-toxicity relationship (QSTR) model was developed, using Ant Colony Optimization (ACO) to select the most relevant set of molecular descriptors, and Support Vector Machine (SVM) to correlate the selected descriptors with the toxicity data. The proposed model showed high performance (QLOO(2) = 0.695, Rfitting(2) = 0.920 and Rtest(2) = 0.831) with low root mean square errors of 0.498 and 0.707 for the training and test set, respectively. It was found that, in addition to hydrophobicity, polarizability and summation of solute-hydrogen bond basicity affected toxicity positively, while minimum atom-type E-state of -OH influenced toxicity values in Daphnia magna inversely. The applicability domain of the proposed model was carefully studied, considering the effect of chemical structure and prediction error in terms of leverage values and standardized residuals. In addition, a new method was proposed to define the chemical space failure for a compound with unknown toxicity to avoid using these prediction results. The resulting ACO-SVM model was successfully applied on an additional evaluation set and the prediction results were found to be very accurate for those compounds that fall inside the defined applicability domain. In fact, compounds commonly found to be difficult to predict, such as quaternary ammonium compounds or organotin compounds were outside the applicability domain, while five representative homologues of LAS (non-ionic surfactants) were, on average

  16. Tournaments and slavery in a desert ant.

    PubMed

    Hölldobler, B

    1976-05-28

    Many species of ants engage in physical fighting when territorial borders are challenged. In contrast, colonies of the honeypot ant species Myrmecocystus mimicus conduct ritualized tournaments, in which hundreds of ants perform highly stereotyped display fights. Opposing colonies summon their worker forces to the tournament area by means of an alarm-recruitment system. When one colony is considerably stronger than the other, the tournament quickly ends, and the weaker colony is raided and its ants "enslaved." This is the first example of intraspecific slavery recorded in ants.

  17. Visual cue learning and odometry in guiding the search behavior of desert ants, Melophorus bagoti, in artificial channels.

    PubMed

    Schwarz, Sebastian; Schultheiss, Patrick; Cheng, Ken

    2012-11-01

    Terrestrial panoramic cues, path integration and search behavior are the main navigational strategies used by ants to locate food and find their way back to the nest. Searching becomes important when the other navigational cues are either not available or cannot provide sufficient information to pinpoint the goal. When searching in one-dimensional channels Melophorus bagoti ants exhibit a systematic drift in the starting-point-to-goal direction as they turn back and forth, sometimes past the goal location (Narendra et al., 2008). Here we show that this drift in channels is not a stereotypical part of the search behavior in these ants. It rather depends on the conditions of training. In experiments in which the nest entrance is located not at the end but at the side of the channel, forward drift is not always part of the nest search. Experiments on food searches showed that with the food source at the end of the channel, ants performed a linear drift in the starting-point-to-food direction. With food at the side of the channel, they showed a less pronounced drift toward the food source. In this constrained environment, especially with the goal at the end of the channel, ants seem to learn a routine such as 'run along the channel', and mix this routine with their usual strategy of turning back and forth in search. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    PubMed Central

    2017-01-01

    Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

  19. 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

  20. Reactions by army ant workers to nestmates having had contact with sympatric ant species.

    PubMed

    Dejean, Alain; Corbara, Bruno

    2014-11-01

    It was recently shown that Pheidole megacephala colonies (an invasive species originating from Africa) counterattack when raided by the army ant, Eciton burchellii. The subsequent contact permits Pheidole cuticular compounds (that constitute the "colony odour") to be transferred onto the raiding Eciton, which are then not recognised by their colony-mates and killed. Using a simple method for transferring cuticular compounds, we tested if this phenomenon occurs for Neotropical ants. Eciton workers rubbed with ants from four sympatric species were released among their colony-mates. Individuals rubbed with Solenopsis saevissima or Camponotus blandus workers were attacked, but not those rubbed with Atta sexdens, Pheidole fallax or with colony-mates (control lot). So, the chemicals of certain sympatric ant species, but not others, trigger intra-colonial aggressiveness in Eciton. We conclude that prey-ant chemicals might have played a role in the evolution of army ant predatory behaviour, likely influencing prey specialization in certain cases.

  1. Revolutionizing Remote Exploration with ANTS

    NASA Astrophysics Data System (ADS)

    Clark, P. E.; Rilee, M. L.; Curtis, S.; Truszkowski, W.

    2002-05-01

    We are developing the Autonomous Nano-Technology Swarm (ANTS) architecture based on an insect colony analogue for the cost-effective, efficient, systematic survey of remote or inaccessible areas with multiple object targets, including planetary surface, marine, airborne, and space environments. The mission context is the exploration in the 2020s of the most compelling remaining targets in the solar system: main belt asteroids. Main belt asteroids harbor important clues to Solar System origins and evolution which are central to NASA's goals in Space Science. Asteroids are smaller than planets, but their number is far greater, and their combined surface area likely dwarfs the Earth's. An asteroid survey will dramatically increase our understanding of the local resources available for the Human Exploration and Development of Space. During the mission composition, shape, gravity, and orbit parameters could be returned to Earth for perhaps several thousand asteroids. A survey of this area will rival the great explorations that encircled this globe, opened up the New World, and laid the groundwork for the progress and challenges of the last centuries. The ANTS architecture for a main belt survey consists of a swarm of as many as a thousand or more highly specialized pico-spacecraft that form teams to survey as many as one hundred asteroids a month. Multi-level autonomy is critical for ANTS and the objective of the proposed study is to work through the implications and constraints this entails. ANTS couples biologically inspired autonomic control for basic functions to higher level artificial intelligence that together enable individual spacecraft to operate as specialized, cooperative, social agents. This revolutionary approach postulates highly advanced, but familiar, components integrated and operated in a way that uniquely transcends any evolutionary extrapolation of existing trends and enables thousand-spacecraft missions.

  2. 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.

  3. Do aphids actively search for ant partners?

    PubMed

    Fischer, Christophe Y; Vanderplanck, Maryse; Lognay, Georges C; Detrain, Claire; Verheggen, François J

    2015-04-01

    The aphid-ant mutualistic relationships are not necessarily obligate for neither partners but evidence is that such interactions provide them strong advantages in terms of global fitness. While it is largely assumed that ants actively search for their mutualistic partners namely using volatile cues; whether winged aphids (i.e., aphids' most mobile form) are able to select ant-frequented areas had not been investigated so far. Ant-frequented sites would indeed offer several advantages for these aphids including a lower predation pressure through ant presence and enhanced chances of establishing mutuaslistic interactions with neighbor ant colonies. In the field, aphid colonies are often observed in higher densities around ant nests, which is probably linked to a better survival ensured by ants' services. Nevertheless, this could also result from a preferential establishment of winged aphids in ant-frequented areas. We tested this last hypothesis through different ethological assays and show that the facultative myrmecophilous black bean aphid, Aphis fabae L., does not orientate its search for a host plant preferentially toward ant-frequented plants. However, our results suggest that ants reduce the number of winged aphids leaving the newly colonized plant. Thus, ants involved in facultative myrmecophilous interactions with aphids appear to contribute to structure aphid populations in the field by ensuring a better establishment and survival of newly established colonies rather than by inducing a deliberate plant selection by aphid partners based on the proximity of ant colonies.

  4. Thermal ecology of the neotropical army ant Eciton burchellii.

    PubMed

    Meisel, Joe E

    2006-06-01

    I explored the thermal ecology of Eciton burchellii, a New World army ant, in primary forest and forest fragments in the Atlantic lowlands of Costa Rica in 2002 and 2003. My primary objective was to determine whether high surface temperatures in pastures surrounding forest fragments posed a thermal barrier to ant colonies within those fragments; secondarily, I assessed whether thermal gradients within continuous moist forest were sufficient to elicit avoidance reactions from foraging colonies. E. burchellii colonies in forest fragments avoided entering open pasture in full sun (51.3 degrees C) on 100% of all edge interactions; however, edges were readily crossed where artificial shaded areas had previously been installed. Ant raids in primary forest avoided artificially established temperatures >43 degrees C but tolerated 45.5 degrees C in the presence of prey baits. Captive ants held at 43 degrees C survived 18.5 min; at temperatures of 51.3 degrees C survival time was only 2.8 min. Ants running on established foraging trails increased running velocity by 18% when substrate temperature was raised from 28.4 degrees to 38.0 degrees C, and they abandoned trails at temperatures >43 degrees C. The standard deviation (s) of temperatures on active raid trails in continuous forest was 2.13 degrees C, while nearby systematic sampling revealed a greater background standard deviation of 4.13 degrees C. E. burchellii colonies in this region appear to be living surprisingly near their upper limits of thermal tolerance. The heat of open pastures alone is sufficient to prevent their exiting forest fragments, or entering similarly hot areas within continuous forest. Shaded vegetative corridors are sufficient to permit mobility between isolated fragments, and their preservation should be encouraged. Despite views that tropical lowland moist forests have an essentially homogenous microclimate, army ants appear to avoid local hot spots on the forest floor, steering daily foraging

  5. A balance-evolution artificial bee colony algorithm for protein structure optimization based on a three-dimensional AB off-lattice model.

    PubMed

    Li, Bai; Chiong, Raymond; Lin, Mu

    2015-02-01

    Protein structure prediction is a fundamental issue in the field of computational molecular biology. In this paper, the AB off-lattice model is adopted to transform the original protein structure prediction scheme into a numerical optimization problem. We present a balance-evolution artificial bee colony (BE-ABC) algorithm to address the problem, with the aim of finding the structure for a given protein sequence with the minimal free-energy value. This is achieved through the use of convergence information during the optimization process to adaptively manipulate the search intensity. Besides that, an overall degradation procedure is introduced as part of the BE-ABC algorithm to prevent premature convergence. Comprehensive simulation experiments based on the well-known artificial Fibonacci sequence set and several real sequences from the database of Protein Data Bank have been carried out to compare the performance of BE-ABC against other algorithms. Our numerical results show that the BE-ABC algorithm is able to outperform many state-of-the-art approaches and can be effectively employed for protein structure optimization.

  6. A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

    PubMed

    Parmaksızoğlu, Selami; Alçı, Mustafa

    2011-01-01

    Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

  7. A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

    PubMed Central

    Parmaksızoğlu, Selami; Alçı, Mustafa

    2011-01-01

    Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

  8. 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.

  9. Ants defend aphids against lethal disease.

    PubMed

    Nielsen, Charlotte; Agrawal, Anurag A; Hajek, Ann E

    2010-04-23

    Social insects defend their own colonies and some species also protect their mutualist partners. In mutualisms with aphids, ants typically feed on honeydew produced by aphids and, in turn guard and shelter aphid colonies from insect natural enemies. Here we report that Formica podzolica ants tending milkweed aphids, Aphis asclepiadis, protect aphid colonies from lethal fungal infections caused by an obligate aphid pathogen, Pandora neoaphidis. In field experiments, bodies of fungal-killed aphids were quickly removed from ant-tended aphid colonies. Ant workers were also able to detect infective conidia on the cuticle of living aphids and responded by either removing or grooming these aphids. Our results extend the long-standing view of ants as mutualists and protectors of aphids by demonstrating focused sanitizing and quarantining behaviour that may lead to reduced disease transmission in aphid colonies.

  10. Ants defend aphids against lethal disease

    PubMed Central

    Nielsen, Charlotte; Agrawal, Anurag A.; Hajek, Ann E.

    2010-01-01

    Social insects defend their own colonies and some species also protect their mutualist partners. In mutualisms with aphids, ants typically feed on honeydew produced by aphids and, in turn guard and shelter aphid colonies from insect natural enemies. Here we report that Formica podzolica ants tending milkweed aphids, Aphis asclepiadis, protect aphid colonies from lethal fungal infections caused by an obligate aphid pathogen, Pandora neoaphidis. In field experiments, bodies of fungal-killed aphids were quickly removed from ant-tended aphid colonies. Ant workers were also able to detect infective conidia on the cuticle of living aphids and responded by either removing or grooming these aphids. Our results extend the long-standing view of ants as mutualists and protectors of aphids by demonstrating focused sanitizing and quarantining behaviour that may lead to reduced disease transmission in aphid colonies. PMID:19923138

  11. Exploitation and interference competition between the invasive Argentine ant, Linepithema humile, and native ant species.

    PubMed

    Human, Kathleen G; Gordon, Deborah M

    1996-02-01

    Interactions between the invasive Argentine ant, Linepithema humile, and native ant species were studied in a 450-ha biological reserve in northern California. Along the edges of the invasion, the presence of Argentine ants significantly reduced the foraging success of native ant species, and vice versa. Argentine ants were consistently better than native ants at exploiting food sources: Argentine ants found and recruited to bait more consistently and in higher numbers than native ant species, and they foraged for longer periods throughout the day. Native ants and Argentine ants frequently fought when they recruited to the same bait, and native ant species were displaced from bait during 60% of these encounters. In introduction experiments, Argentine ants interfered with the foraging of native ant species, and prevented the establishment of new colonies of native ant species by preying upon winged native ant queens. The Argentine ants' range within the preserve expanded by 12 ha between May 1993 and May 1994, and 13 between September 1993 and September 1994, with a corresponding reduction of the range of native ant species. Although some native ants persist locally at the edges of the invasion of Argentine ants, most eventually disappear from invaded areas. Both interference and exploitation competition appear to be important in the displacement of native ant species from areas invaded by Argentine ants.

  12. Rescue of newborn ants by older Cataglyphis cursor adult workers.

    PubMed

    Nowbahari, Elise; Amirault, Céline; Hollis, Karen L

    2016-05-01

    Cataglyphis cursor worker ants are capable of highly sophisticated rescue behaviour in which individuals are able to identify what has trapped a nestmate and to direct their behaviour towards that obstacle. Nonetheless, rescue behaviour is constrained by workers' subcaste: whereas foragers, the oldest workers, are able both to give and to receive the most help, the youngest workers, inactives, neither give nor receive any help whatsoever; nurses give and receive intermediate levels of aid, reflecting their intermediate age. Such differences in rescue behaviour across subcastes suggest that age and experience play a critical role. In this species, as in many others in which a sensitive period for nestmate recognition exists, newly enclosed ants, called callows, are adopted by ants belonging not only to different colonies but also to different species; foreign callows receive nearly the same special care provided to resident newborns. Because callows are younger than inactives, which are incapable of soliciting rescue, we wondered whether entrapped callows would receive such aid. In the present study, we artificially ensnared individual callows from their own colony (homocolonial), from a different colony (heterocolonial), and from a different species (heterospecific), and tested each one with groups of five potential C. cursor rescuers, either all foragers or all nurses. Our results show that all three types of callows are able to elicit rescue behaviour from both foragers and nurses. Nonetheless, nurse rescuers are better able to discriminate between the three types of callow victims than are foragers.

  13. Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

    PubMed

    Aydin, Alev Dilek; Caliskan Cavdar, Seyma

    2015-01-01

    The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method.

  14. Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting

    PubMed Central

    Aydin, Alev Dilek; Caliskan Cavdar, Seyma

    2015-01-01

    The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method. PMID:26550010

  15. Honey Ants.

    ERIC Educational Resources Information Center

    Conway, John R.

    1984-01-01

    Provides background information on honey ants. These ants are found in dry or desert regions of North America, Africa, and Australia. Also provides a list of activities using local species of ants. (JN)

  16. Honey Ants.

    ERIC Educational Resources Information Center

    Conway, John R.

    1984-01-01

    Provides background information on honey ants. These ants are found in dry or desert regions of North America, Africa, and Australia. Also provides a list of activities using local species of ants. (JN)

  17. Does exogenic food benefit both partners in an ant-plant mutualism? The case of Cecropia obtusa and its guest Azteca plant-ants.

    PubMed

    Dejean, Alain; Petitclerc, Frédéric; Roux, Olivier; Orivel, Jérôme; Leroy, Céline

    2012-03-01

    In the mutualisms involving the myrmecophyte Cecropia obtusa and Azteca ovaticeps or A. alfari, both predatory, the ants defend their host trees from enemies and provide them with nutrients (myrmecotrophy). A. ovaticeps provisioned with prey and then (15)N-enriched food produced more individuals than did control colonies (not artificially provisioned). This was not true for A. alfari colonies, possibly due to differences in the degree of maturity of the colonies for the chosen range of host tree sizes (less than 3m in height). Myrmecotrophy was demonstrated for both Azteca species as provisioning the ants with (15)N-enriched food translated into higher δ(15)N values in host plant tissues, indicating that nitrogen passed from the food to the plant. Thus, the predatory activity of their guest ants benefits the Cecropia trees not only because the ants protect them from defoliators since most prey are phytophagous insects but also because the plant absorbs nutrients. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  18. Diet-related modification of cuticular hydrocarbon profiles of the Argentine ant, Linepithema humile, diminishes intercolony aggression.

    PubMed

    Buczkowski, Grzegorz; Kumar, Ranjit; Suib, Steven L; Silverman, Jules

    2005-04-01

    Territorial boundaries between conspecific social insect colonies are maintained through a highly developed nestmate recognition system modulated by heritable and, in some instances, nonheritable cues. Argentine ants, Linepithema humile, use both genetic and environmentally derived cues to discriminate nestmates from nonnestmates. We explored the possibility that intraspecific aggression in the Argentine ant might diminish when colonies shared a common diet. After segregating recently field-collected colony pairs into high or moderate aggression categories, we examined the effect of one of three diets: two hydrocarbon-rich insect prey, Blattella germanica and Supella longipalpa, and an artificial (insect-free) diet, on the magnitude of aggression loss. Aggression diminished between colony pairs that were initially moderately aggressive. However, initially highly aggressive colony pairs maintained high levels of injurious aggression throughout the study, independent of diet type. Each diet altered the cuticular hydrocarbon profile by contributing unique, diet-specific cues. We suggest that acquisition of common exogenous nestmate recognition cues from shared food sources may diminish aggression and promote fusion in neighboring colonies of the Argentine ant.

  19. Introduced fire ants can exclude native ants from critical mutualist-provided resources.

    PubMed

    Wilder, Shawn M; Barnum, Thomas R; Holway, David A; Suarez, Andrew V; Eubanks, Micky D

    2013-05-01

    Animals frequently experience resource imbalances in nature. For ants, one resource that may be particularly valuable for both introduced and native species is high-carbohydrate honeydew from hemipteran mutualists. We conducted field and laboratory experiments: (1) to test if red imported fire ants (Solenopsis invicta) competed with native ants for access to mutualisms with aphids, and (2) to quantify the effects of aphid honeydew presence or absence on colony growth of native ants. We focused on native dolichoderine ants (Formicidae, Dolichoderinae) because they are abundant ants that have omnivorous diets that frequently include mutualist-provided carbohydrates. At two sites in the southeastern US, native dolichoderine ants were far less frequent, and fire ants more frequent, at carbohydrate baits than would be expected based on their frequency in pitfall traps. A field experiment confirmed that a native ant species, Dorymyrmex bureni, was only found tending aphids when populations of S. invicta were suppressed. In the laboratory, colonies of native dolichoderine ants with access to both honeydew and insect prey had twice as many workers and over twice as much brood compared to colonies fed only ad libitum insect prey. Our results provide the first experimental evidence that introduced ants compete for access to mutualist-provided carbohydrates with native ants and that these carbohydrates represent critical resources for both introduced and native ants. These results challenge traditional paradigms of arthropod and ant nutrition and contribute to growing evidence of the importance of nutrition in mediating ecological interactions.

  20. Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

    PubMed Central

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-01-01

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

  1. Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment.

    PubMed

    Tang, Phooi Wah; Choon, Yee Wen; Mohamad, Mohd Saberi; Deris, Safaai; Napis, Suhaimi

    2015-03-01

    Metabolic engineering is a research field that focuses on the design of models for metabolism, and uses computational procedures to suggest genetic manipulation. It aims to improve the yield of particular chemical or biochemical products. Several traditional metabolic engineering methods are commonly used to increase the production of a desired target, but the products are always far below their theoretical maximums. Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. The dataset used in this work was from the iJO1366 Escherichia coli metabolic network. The experimental results include the production rate, growth rate and a list of knockout genes. From the comparative analysis, ABCMOMA produced better results compared to previous works, showing potential for solving genetic engineering problems.

  2. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    PubMed

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  3. Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

    PubMed

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-10-22

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

  4. Army Ants as Research and Collection Tools

    PubMed Central

    Smith, Adrian A.; Haight, Kevin L.

    2008-01-01

    Ants that fall prey to the raids of army ants commonly respond by evacuating their nests. This documented behavior has been underexploited by researchers as an efficient research tool. This study focuses on the evacuation response of the southwestern desert ant Aphaenogaster cockerelli André (Hymenoptera: Formicidae) to the army ant Newamyrmex nigrescens Cresson. It is shown that army ants can be used to collect mature colonies of ants. The applicability of this tool to ecologically meaningful areas of research is discussed. PMID:20302457

  5. Are ant-aphid associations a tritrophic interaction? Oleander aphids and Argentine ants.

    PubMed

    Bristow, C M

    1991-09-01

    Oleander aphids, (Aphis nerii), which are sporadically tended by ants, were used as a moded system to examine whether host plant factors associated with feeding site influenced the formation of ant-aphid associations. Seasonal patterns of host plant utilization and association with attendant ants were examined through bi-weekly censuses of the aphid population feeding on thirty ornamental oleander plands (Nerium oleander) in northern California in 1985 and 1986. Colonies occurred on both developing and senescing plant terminals, including leaf tips, floral structures, and pods. Aphids preferentially colonized leaf terminals early in the season, but showed no preference for feeding site during later periods. Argentine ants (Iridomyrmex humilis) occasionally tended aphid colonies. Colonies on floral tips were three to four times more likely to attract ants than colonies on leaf tips, even though the latter frequently contained more aphids. Ants showed a positive recruitment response to colonies on floral tips, with a significant correlation between colony size and number of ants. There was no recruitment response to colonies on leaf tips. These patterns were reproducible over two years despite large fluctuations in both aphid population density and ant activity. In a laboratory bioassay of aphid palatability, the generalist predator,Hippodamia convergens, took significantly more aphids reared on floral tips compared to those reared on leaf tips. The patterns reported here support the hypothesis that tritrophic factors may be important in modifying higher level arthropod mutualisms.

  6. Routing Vehicles with Ants

    NASA Astrophysics Data System (ADS)

    Tan, Wen Fang; Lee, Lai Soon; Majid, Zanariah Abdul; Seow, Hsin Vonn

    Routing vehicles involve the design of an optimal set of routes for a fleet of vehicles to serve a number of customers with known demands. This research develops an Ant Colony Optimization for the vehicle routing with one central depot and identical vehicles. The procedure simulates the behavior of real ants that always find the shortest path between their nest and a food source through a form of communication, pheromone trail. Finally, preliminary results on the learning of the algorithm testing on benchmark data set will be presented in this paper.

  7. Improving the channeler ant model for lung CT analysis

    NASA Astrophysics Data System (ADS)

    Cerello, Piergiorgio; Lopez Torres, Ernesto; Fiorina, Elisa; Oppedisano, Chiara; Peroni, Cristiana; Arteche Diaz, Raul; Bellotti, Roberto; Bosco, Paolo; Camarlinghi, Niccolo; Massafra, Andrea

    2011-03-01

    The Channeler Ant Model (CAM) is an algorithm based on virtual ant colonies, conceived for the segmentation of complex structures with different shapes and intensity in a 3D environment. It exploits the natural capabilities of virtual ant colonies to modify the environment and communicate with each other by pheromone deposition. When applied to lung CTs, the CAM can be turned into a Computer Aided Detection (CAD) method for the identification of pulmonary nodules and the support to radiologists in the identification of early-stage pathological objects. The CAM has been validated with the segmentation of 3D artificial objects and it has already been successfully applied to the lung nodules detection in Computed Tomography images within the ANODE09 challenge. The model improvements for the segmentation of nodules attached to the pleura and to the vessel tree are discussed, as well as a method to enhance the detection of low-intensity nodules. The results on five datasets annotated with different criteria show that the analytical modules (i.e. up to the filtering stage) provide a sensitivity in the 80 - 90% range with a number of FP/scan of the order of 20. The classification module, although not yet optimised, keeps the sensitivity in the 70 - 85% range at about 10 FP/scan, in spite of the fact that the annotation criteria for the training and the validation samples are different.

  8. 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

  9. An ant's-eye view of an ant-plant protection mutualism.

    PubMed

    Lanan, M C; Bronstein, J L

    2013-07-01

    Ant protection of extrafloral nectar (EFN)-secreting 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 EFN-secreting cactus Ferocactus wislizeni (Englem) is not independent between plants up to 5 m apart. Colony territories of C. opuntiae are large, covering areas of up to 5,000 m(2), and workers visit between five and 34 EFN-secreting barrel cacti within the territories. These ants are highly polydomous, with up to 20 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.

  10. Improved ant algorithms for software testing cases generation.

    PubMed

    Yang, Shunkun; Man, Tianlong; Xu, Jiaqi

    2014-01-01

    Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to produce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations.

  11. Improved Ant Algorithms for Software Testing Cases Generation

    PubMed Central

    Yang, Shunkun; Xu, Jiaqi

    2014-01-01

    Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391

  12. 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.

  13. Ant Tower

    NASA Astrophysics Data System (ADS)

    Mlot, Nathan; Shinotsuka, Sho; Hu, David

    2010-11-01

    Ants walk via adhesive drops of fluid extruded by their feet. They also use these drops as mortar to build structures such as rafts, bridges and towers, each composed of thousands of ants linked together. We investigate experimentally the construction of triangular ant towers braced by hydrophobic walls. Particular attention is paid to the relationship between tower height and contact angle hysteresis of the wall. We rationalize tower height according to ant adhesion, and tower shape according to the constraints on a column of constant strength.

  14. 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.

  15. Dynamic Network Formation Using Ant Colony Optimization

    DTIC Science & Technology

    2009-03-01

    global solver into a distributed solver where each network node independently assigned their network links. 1.3 Methodology Previous research into...the solution to the network topology is generated at the node level 10 and then consolidated and evaluated at a global level to properly evaluate...application. The specific MILP tool was XPRESS -MP which employs the dual simplex, primal simplex, or the Newton Barrier method to solve the relaxed linear

  16. Spatiotemporal chemotactic model for ant foraging

    NASA Astrophysics Data System (ADS)

    Ramakrishnan, Subramanian; Laurent, Thomas; Kumar, Manish; Bertozzi, Andrea L.

    2014-12-01

    In this paper, we present a generic theoretical chemotactic model that accounts for certain emergent behaviors observed in ant foraging. The model does not have many of the constraints and limitations of existing models for ants colony dynamics and takes into account the distinctly different behaviors exhibited in nature by ant foragers in search of food and food ferrying ants. Numerical simulations based on the model show trail formation in foraging ant colonies to be an emergent phenomenon and, in particular, replicate behavior observed in experiments involving the species P. megacephala. The results have broader implications for the study of randomness in chemotactic models. Potential applications include the developments of novel algorithms for stochastic search in engineered complex systems such as robotic swarms.

  17. Ant-lepidopteran associations along African forest edges.

    PubMed

    Dejean, Alain; Azémar, Frédéric; Libert, Michel; Compin, Arthur; Hérault, Bruno; Orivel, Jérôme; Bouyer, Thierry; Corbara, Bruno

    2017-02-01

    Working along forest edges, we aimed to determine how some caterpillars can co-exist with territorially dominant arboreal ants (TDAAs) in tropical Africa. We recorded caterpillars from 22 lepidopteran species living in the presence of five TDAA species. Among the defoliator and/or nectarivorous caterpillars that live on tree foliage, the Pyralidae and Nymphalidae use their silk to protect themselves from ant attacks. The Notodontidae and lycaenid Polyommatinae and Theclinae live in direct contact with ants; the Theclinae even reward ants with abundant secretions from their Newcomer gland. Lichen feeders (lycaenid; Poritiinae), protected by long bristles, also live among ants. Some lycaenid Miletinae caterpillars feed on ant-attended membracids, including in the shelters where the ants attend them; Lachnocnema caterpillars use their forelegs to obtain trophallaxis from their host ants. Caterpillars from other species live inside weaver ant nests. Those of the genus Euliphyra (Miletinae) feed on ant prey and brood and can obtain trophallaxis, while those from an Eberidae species only prey on host ant eggs. Eublemma albifascia (Erebidae) caterpillars use their thoracic legs to obtain trophallaxis and trophic eggs from ants. Through transfer bioassays of last instars, we noted that herbivorous caterpillars living in contact with ants were always accepted by alien conspecific ants; this is likely due to an intrinsic appeasing odor. Yet, caterpillars living in ant shelters or ant nests probably acquire cues from their host colonies because they were considered aliens and killed. We conclude that co-evolution with ants occurred similarly in the Heterocera and Rhopalocera.

  18. Ant-lepidopteran associations along African forest edges

    NASA Astrophysics Data System (ADS)

    Dejean, Alain; Azémar, Frédéric; Libert, Michel; Compin, Arthur; Hérault, Bruno; Orivel, Jérôme; Bouyer, Thierry; Corbara, Bruno

    2017-02-01

    Working along forest edges, we aimed to determine how some caterpillars can co-exist with territorially dominant arboreal ants (TDAAs) in tropical Africa. We recorded caterpillars from 22 lepidopteran species living in the presence of five TDAA species. Among the defoliator and/or nectarivorous caterpillars that live on tree foliage, the Pyralidae and Nymphalidae use their silk to protect themselves from ant attacks. The Notodontidae and lycaenid Polyommatinae and Theclinae live in direct contact with ants; the Theclinae even reward ants with abundant secretions from their Newcomer gland. Lichen feeders (lycaenid; Poritiinae), protected by long bristles, also live among ants. Some lycaenid Miletinae caterpillars feed on ant-attended membracids, including in the shelters where the ants attend them; Lachnocnema caterpillars use their forelegs to obtain trophallaxis from their host ants. Caterpillars from other species live inside weaver ant nests. Those of the genus Euliphyra (Miletinae) feed on ant prey and brood and can obtain trophallaxis, while those from an Eberidae species only prey on host ant eggs. Eublemma albifascia (Erebidae) caterpillars use their thoracic legs to obtain trophallaxis and trophic eggs from ants. Through transfer bioassays of last instars, we noted that herbivorous caterpillars living in contact with ants were always accepted by alien conspecific ants; this is likely due to an intrinsic appeasing odor. Yet, caterpillars living in ant shelters or ant nests probably acquire cues from their host colonies because they were considered aliens and killed. We conclude that co-evolution with ants occurred similarly in the Heterocera and Rhopalocera.

  19. Variation in thermal tolerance of North American ants.

    PubMed

    Verble-Pearson, Robin M; Gifford, Matthew E; Yanoviak, Stephen P

    2015-02-01

    Changing climates are predicted to alter the distribution of thermal niches. Small ectotherms such as ants may be particularly vulnerable to heat injury and death. We quantified the critical thermal maxima of 92 ant colonies representing 14 common temperate ant species. The mean CTmax for all measured ants was 47.8 °C (±0.27; range=40.2-51.2 °C), and within-colony variation was lower than among-colony variation. Critical thermal maxima differed among species and were negatively correlated with body size. Results of this study illustrate the importance of accounting for mass, among and within colony variation, and interspecific differences in diel activity patterns, which are often neglected in studies of ant thermal physiology. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Signals Can Trump Rewards in Attracting Seed-Dispersing Ants

    PubMed Central

    Turner, Kyle M.; Frederickson, Megan E.

    2013-01-01

    Both rewards and signals are important in mutualisms. In myrmecochory, or seed dispersal by ants, the benefits to plants are relatively well studied, but less is known about why ants pick up and move seeds. We examined seed dispersal by the ant Aphaenogaster rudis of four co-occurring species of plants, and tested whether morphology, chemical signaling, or the nutritional quality of fatty seed appendages called elaiosomes influenced dispersal rates. In removal trials, ants quickly collected diaspores (seeds plus elaiosomes) of Asarum canadense, Trillium grandiflorum, and Sanguinaria canadensis, but largely neglected those of T. erectum. This discrepancy was not explained by differences in the bulk cost-benefit ratio, as assessed by the ratio of seed to elaiosome mass. We also provisioned colonies with diaspores from one of these four plant species or no diaspores as a control. Colonies performed best when fed S. canadensis diaspores, worst when fed T. grandiflorum, and intermediately when fed A. canadense, T. erectum, or no diaspores. Thus, the nutritional rewards in elaiosomes affected colony performance, but did not completely predict seed removal. Instead, high levels of oleic acid in T. grandiflorum elaiosomes may explain why ants disperse these diaspores even though they reduce ant colony performance. We show for the first time that different elaiosome-bearing plants provide rewards of different quality to ant colonies, but also that ants appear unable to accurately assess reward quality when encountering seeds. Instead, we suggest that signals can trump rewards as attractants of ants to seeds. PMID:23967257

  1. Signals can trump rewards in attracting seed-dispersing ants.

    PubMed

    Turner, Kyle M; Frederickson, Megan E

    2013-01-01

    Both rewards and signals are important in mutualisms. In myrmecochory, or seed dispersal by ants, the benefits to plants are relatively well studied, but less is known about why ants pick up and move seeds. We examined seed dispersal by the ant Aphaenogaster rudis of four co-occurring species of plants, and tested whether morphology, chemical signaling, or the nutritional quality of fatty seed appendages called elaiosomes influenced dispersal rates. In removal trials, ants quickly collected diaspores (seeds plus elaiosomes) of Asarum canadense, Trillium grandiflorum, and Sanguinaria canadensis, but largely neglected those of T. erectum. This discrepancy was not explained by differences in the bulk cost-benefit ratio, as assessed by the ratio of seed to elaiosome mass. We also provisioned colonies with diaspores from one of these four plant species or no diaspores as a control. Colonies performed best when fed S. canadensis diaspores, worst when fed T. grandiflorum, and intermediately when fed A. canadense, T. erectum, or no diaspores. Thus, the nutritional rewards in elaiosomes affected colony performance, but did not completely predict seed removal. Instead, high levels of oleic acid in T. grandiflorum elaiosomes may explain why ants disperse these diaspores even though they reduce ant colony performance. We show for the first time that different elaiosome-bearing plants provide rewards of different quality to ant colonies, but also that ants appear unable to accurately assess reward quality when encountering seeds. Instead, we suggest that signals can trump rewards as attractants of ants to seeds.

  2. Colonial America.

    ERIC Educational Resources Information Center

    Web Feet K-8, 2001

    2001-01-01

    Presents resources for grades K-8, on the subject of Colonial America. Describes Web sites; CD-ROMs and software; videos; books; audios; magazines; and professional resources. Includes two articles, "Native Americans in the Colonies," and "The Golden Age of Pirates," which also highlight resources. Presents a Web activity focusing on daily life in…

  3. Effects of aromatic cedar mulch on the Argentine ant and the odorous house ant (Hymenoptera: Formicidae).

    PubMed

    Meissner, H E; Silverman, J

    2001-12-01

    In laboratory studies, the Argentine ant, Linepithema humile (Mayr), and the odorous house ant, Tapinoma sessile (Say), avoided aromatic cedar mulch as a nesting substrate. Both ant species were killed when confined with fresh aromatic cedar mulch in sealed containers. However, when confined with cedar mulch that had been aged outdoors for up to 140 d, mortality of L. humile was complete regardless of mulch age, whereas T. sessile mortality declined significantly over the mulch-aging period. Argentine ant susceptibility to aromatic cedar mulch was also greater than that of the odorous house ant when colonies were restricted to mulch in open trays. In addition, commercial aromatic cedar oil was lethal to both ant species. Our results suggest that aromatic cedar mulch may serve as an effective component of a comprehensive urban ant management program.

  4. Stinging ants.

    PubMed

    Rhoades, R

    2001-08-01

    Ants belong to the order Hymenoptera, along with bees, wasps, yellow jackets, etc., they are the most successful animal genera in this world. It is their selfless social structure which accounts for their huge impact. Their effect on man ranges from the parasol ant, which makes plant cultivation untenable in certain parts of South America, to Solenopsis Invicta in the southeastern United States of America, which kill ground dwelling birds and small animals, harass livestock, and renders farmland unusable. With the exception of the Bulldog Ant of Australia (which is the size of a medium cockroach) direct toxic effects are not a lethal threat to man. Human fatalities and morbidity are related to secondary infections of excoriated stings or allergic anaphylaxis. This article reviews history and recent developments regarding stinging ants around the world.

  5. 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

  6. 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.

  7. Distribution, abundance and persistence of Orasema spp. (Hym:Eucharitidae) parasitic on fire ants in South America

    USDA-ARS?s Scientific Manuscript database

    Parasitoid wasps of the genus Orasema Cameron have been considered as potential candidates for biological control of imported fire ants in the United States. Surveys were conducted for their occurrence in fire ant colonies across southern South America. In Argentina, 443 ant colonies were excavated ...

  8. The evolution of multiple mating in army ants.

    PubMed

    Kronauer, Daniel J C; Johnson, Robert A; Boomsma, Jacobus J

    2007-02-01

    The evolution of mating systems in eusocial Hymenoptera is constrained because females mate only during a brief period early in life, whereas inseminated queens and their stored sperm may live for decades. Considerable research effort during recent years has firmly established that obligate multiple mating has evolved only a few times: in Apis honeybees, Vespula wasps, Pogonomyrmex harvester ants, Atta and Acromyrmex leaf-cutting ants, the ant Cataglyphis cursor, and in at least some army ants. Here we provide estimates of queen-mating frequency for New World Neivamyrmex and Old World Aenictus species, which, compared to other army ants, have relatively small colonies and little size polymorphism among workers. To provide the first overall comparative analysis of the evolution of army ant mating systems, we combine these new results with previous estimates for African Dorylus and New World Eciton army ants, which have very large colonies and considerable worker polymorphism. We show that queens of Neivamyrmex and Aenictus mate with the same high numbers of males (usually ca. 10-20) as do queens of army ant species with very large colony sizes. We infer that multiple queen mating is ancestral in army ants and has evolved over 100 million years ago as part of the army ant adaptive syndrome. A comparison of army ants and honeybees suggests that mating systems in these two distantly related groups may have been convergently shaped by strikingly similar selective pressures.

  9. 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

  10. Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

    SciTech Connect

    Hooper-Bui, L. M.; Kwok, E S.C.; Buchholz, B. A.; Rust, M. K.; Eastmond, D. A.; Vogel, J. S.

    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), but 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.

  11. Insecticide transfer efficiency and lethal load in Argentine ants

    NASA Astrophysics Data System (ADS)

    Hooper-Bui, L. M.; Kwok, E. S. C.; Buchholz, B. A.; Rust, M. K.; Eastmond, D. A.; Vogel, J. S.

    2015-10-01

    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), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). 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. 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.

  12. Insecticide Transfer Efficiency and Lethal Load in Argentine Ants

    PubMed Central

    Hooper-Bui, L.M.; Kwok, E.S.C.; Buchholz, B.A.; Rust, M.K.; Eastmond, D.A.; Vogel, J.S.

    2015-01-01

    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), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). 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. 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. PMID:26504258

  13. Insecticide Transfer Efficiency and Lethal Load in Argentine Ants.

    PubMed

    Hooper-Bui, L M; Kwok, E S C; Buchholz, B A; Rust, M K; Eastmond, D A; Vogel, J S

    2015-10-15

    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 (14)C-sucrose, (14)C-hydramethylnon, and (14)C-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), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). 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. 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.

  14. Aphid egg protection by ants: a novel aspect of the mutualism between the tree-feeding aphid Stomaphis hirukawai and its attendant ant Lasius productus

    NASA Astrophysics Data System (ADS)

    Matsuura, Kenji; Yashiro, Toshihisa

    2006-10-01

    Aphids often form mutualistic associations with ants, in which the aphids provide the ants with honeydew and the ants defend the aphids from predators. In this paper, we report aphid egg protection by ants as a novel aspect of the deeply interdependent relationship between a tree-feeding aphid and its attendant ant. The ant Lasius productus harbours oviparous females, males, and eggs of the hinoki cypress-feeding aphid Stomaphis hirukawai in its nests in winter. We investigated the behaviour of ants kept with aphid eggs in petri dishes to examine whether the ants recognise the aphid eggs and tend them or only provide a refuge for the aphids. Workers carried almost all of the aphid eggs into the nest within 24 h. The ants indiscriminately tended aphid eggs collected from their own colonies and those from other ant colonies. The ants cleaned the eggs and piled them up in the nest, and egg tending by ants dramatically increased aphid egg survival rates. Starving the ants showed no significant effect on aphid egg survivorship. Without ants, aphid eggs were rapidly killed by fungi. These results suggested that grooming by the ants protected the aphid eggs, at least, against pathogenic fungi. This hygienic service afforded by the ants seems indispensable for egg survival of these aphids in an environment rich in potentially pathogenic microorganisms.

  15. Ants (Formicidae): models for social complexity.

    PubMed

    Smith, Chris R; Dolezal, Adam; Eliyahu, Dorit; Holbrook, C Tate; Gadau, Jürgen

    2009-07-01

    The family Formicidae (ants) is composed of more than 12,000 described species that vary greatly in size, morphology, behavior, life history, ecology, and social organization. Ants occur in most terrestrial habitats and are the dominant animals in many of them. They have been used as models to address fundamental questions in ecology, evolution, behavior, and development. The literature on ants is extensive, and the natural history of many species is known in detail. Phylogenetic relationships for the family, as well as within many subfamilies, are known, enabling comparative studies. Their ease of sampling and ecological variation makes them attractive for studying populations and questions relating to communities. Their sociality and variation in social organization have contributed greatly to an understanding of complex systems, division of labor, and chemical communication. Ants occur in colonies composed of tens to millions of individuals that vary greatly in morphology, physiology, and behavior; this variation has been used to address proximate and ultimate mechanisms generating phenotypic plasticity. Relatedness asymmetries within colonies have been fundamental to the formulation and empirical testing of kin and group selection theories. Genomic resources have been developed for some species, and a whole-genome sequence for several species is likely to follow in the near future; comparative genomics in ants should provide new insights into the evolution of complexity and sociogenomics. Future studies using ants should help establish a more comprehensive understanding of social life, from molecules to colonies.

  16. Discriminatory abilities of facultative slave-making ants and their slaves.

    PubMed

    Włodarczyk, T

    2016-01-01

    Intra-colony odor variability can disturb ants' ability to discriminate against intruders. The evolutionary relevance of this phenomenon can be revealed by studies on colonies of slave-making ants in which the parasite, and not the host, is subject to selection pressures associated with living in a mixed colony. We examined how the European facultative slave-making species Formica sanguinea and its F. fusca slaves perform in discriminating ants from alien colonies. Results of behavioral assays showed that slave-maker ants respond with hostility to conspecific individuals from alien colonies but are relatively tolerant to alien slaves. Furthermore, the behavior of slaves indicated a limited ability to discriminate ants from alien parasitic colonies. The subdivision of colony fragments into mixed and species-separated groups demonstrated that contact with the parasite is necessary for F. fusca slaves to be re-accepted by former nestmates after a period of separation from the stock colony. The results presented in this paper are consistent with the following hypotheses: (1) F. sanguinea ants, as opposed to their slaves, are adapted to discriminate alien individuals in the conditions of odor variability found in a mixed-species colony, (2) the recognition of slaves by F. sanguinea ants involves a dedicated adaptive mechanism that prevents aggression toward them, (3) the odor of slaves is strongly influenced by the parasite with beneficial effect on the colony integrity.

  17. Ant-seed mutualisms: Can red imported fire ants sour the relationship?

    USGS Publications Warehouse

    Zettler, J.A.; Spira, T.P.; Allen, C.R.

    2001-01-01

    Invasion by the red imported fire ant, Solenopsis invicta, has had negative impacts on individual animal and plant species, but little is known about how S. invicta affects complex mutualistic relationships. In some eastern forests of North America, 30% of herbaceous species have ant-dispersed seeds. We conducted experiments to determine if fire ants are attracted to seeds of these plant species and assessed the amount of scarification or damage that results from handling by fire ants. Fire ants removed nearly 100% of seeds of the ant-dispersed plants Trillium undulatum, T. discolor, T. catesbaei, Viola rotundifolia, and Sanguinaria canadensis. In recovered seeds fed to ant colonies, fire ants scarified 80% of S. canadensis seeds and destroyed 86% of V. rotundifolia seeds. Our study is the first to document that red imported fire ants are attracted to and remove seeds of species adapted for ant dispersal. Moreover, fire ants might damage these seeds and discard them in sites unfavorable for germination and seedling establishment. ?? 2001 Elsevier Science Ltd. All rights reserved.

  18. Food webs in the litter: effects of food and nest addition on ant communities in coffee agroecosystems and forest.

    PubMed

    Murnen, Cody J; Gonthier, David J; Philpott, Stacy M

    2013-08-01

    Community assembly is driven by multiple factors, including resource availability and habitat requirements. Litter nesting ants respond to food and nest site availability, and adding food and nests may increase ant species richness and abundance. However, litter decomposers share food resources with ants, and increasing food availability may speed decomposition processes, eliminating twigs and seeds in which litter ants nest. We manipulated ant food and nest resources in three habitat types (forest, high-shade coffee, and low-shade coffee) to determine ant community responses after 1 and 2 mo. We examined changes in numbers of ant species, colonies, workers, brood, colony growth rate, and ant species composition. Habitat type strongly affected ant communities, influencing ant species richness, numbers of colonies and workers, and ant species composition. However, food addition and nest addition did not affect these community characteristics. Colony growth rate did not differ with food addition but was greater in forest and low-shade coffee compared with high-shade coffee. Habitat differences in colony growth may be because of presence of an aggressive species (Wasmannia auropunctata Roger) in high-shade coffee plots or naturally low arthropod densities during a time when ant colonization was low. Thus, in coffee landscapes, habitat type impacts litter nesting ant community structure, composition, and colony growth rate; however, food and nest addition had small impacts.

  19. Density-dependent benefits in ant-hemipteran mutualism? The case of the ghost ant Tapinoma melanocephalum (Hymenoptera: Formicidae) and the invasive mealybug Phenacoccus solenopsis (Hemiptera: Pseudococcidae).

    PubMed

    Zhou, Aiming; Kuang, Beiqing; Gao, Yingrui; Liang, Guangwen

    2015-01-01

    Although density-dependent benefits to hemipterans from ant tending have been measured many times, few studies have focused on integrated effects such as interactions between ant tending, natural enemy density, and hemipteran density. In this study, we tested whether the invasive mealybug Phenacoccus solenopsis is affected by tending by ghost ants (Tapinoma melanocephalum), the presence of parasitoids, mealybug density, parasitoid density and interactions among these factors. Our results showed that mealybug colony growth rate and percentage parasitism were significantly affected by ant tending, parasitoid presence, and initial mealybug density separately. However, there were no interactions among the independent factors. There were also no significant interactions between ant tending and parasitoid density on either mealybug colony growth rate or percentage parasitism. Mealybug colony growth rate showed a negative linear relationship with initial mealybug density but a positive linear relationship with the level of ant tending. These results suggest that benefits to mealybugs are density-independent and are affected by ant tending level.

  20. Fire disturbance disrupts an acacia ant-plant mutualism in favor of a subordinate ant species.

    PubMed

    Sensenig, Ryan L; Kimuyu, Duncan K; Ruiz Guajardo, Juan C; Veblen, Kari E; Riginos, Corinna; Young, Truman P

    2017-05-01

    Although disturbance theory has been recognized as a useful framework in examining the stability of ant-plant mutualisms, very few studies have examined the effects of fire disturbance on these mutualisms. In myrmecophyte-dominated savannas, fire and herbivory are key drivers that could influence ant-plant mutualisms by causing complete colony mortality and/or decreasing colony size, which potentially could alter dominance hierarchies if subordinate species are more fire resilient. We used a large-scale, replicated fire experiment to examine long-term effects of fire on acacia-ant community composition. To determine if fire shifted ant occupancy from a competitive dominant to a subordinate ant species, we surveyed the acacia-ant community in 6-7 yr old burn sites and examined how the spatial scale of these burns influenced ant community responses. We then used two short-term fire experiments to explore possible mechanisms for the shifts in community patterns observed. Because survival of ant colonies is largely dependent on their ability to detect and escape an approaching fire, we first tested the evacuation response of all four ant species when exposed to smoke (fire signal). Then to better understand how fire and its interaction with large mammal herbivory affect the density of ants per tree, we quantified ant worker density in small prescribed burns within herbivore exclusion plots. We found clear evidence suggesting that fire disturbance favored the subordinate ant Crematogaster nigriceps more than the dominant and strong mutualist ant C. mimosae, whereby C. nigriceps (1) was the only species to occupy a greater proportion of trees in 6-7 yr old burn sites compared to unburned sites, (2) had higher burn/unburn tree ratios with increasing burn size, and (3) evacuated significantly faster than C. mimosae in the presence of smoke. Fire and herbivory had opposite effects on ant density per meter of branch for both C. nigriceps and C. mimosae, with fire

  1. Visual navigation in the Neotropical ant Odontomachus hastatus (Formicidae, Ponerinae), a predominantly nocturnal, canopy-dwelling predator of the Atlantic rainforest.

    PubMed

    Rodrigues, Pedro A P; Oliveira, Paulo S

    2014-11-01

    The arboreal ant Odontomachus hastatus nests among roots of epiphytic bromeliads in the sandy forest at Cardoso Island (Brazil). Crepuscular and nocturnal foragers travel up to 8m to search for arthropod prey in the canopy, where silhouettes of leaves and branches potentially provide directional information. We investigated the relevance of visual cues (canopy, horizon patterns) during navigation in O. hastatus. Laboratory experiments using a captive ant colony and a round foraging arena revealed that an artificial canopy pattern above the ants and horizon visual marks are effective orientation cues for homing O. hastatus. On the other hand, foragers that were only given a tridimensional landmark (cylinder) or chemical marks were unable to home correctly. Navigation by visual cues in O. hastatus is in accordance with other diurnal arboreal ants. Nocturnal luminosity (moon, stars) is apparently sufficient to produce contrasting silhouettes from the canopy and surrounding vegetation, thus providing orientation cues. Contrary to the plain floor of the round arena, chemical cues may be important for marking bifurcated arboreal routes. This experimental demonstration of the use of visual cues by a predominantly nocturnal arboreal ant provides important information for comparative studies on the evolution of spatial orientation behavior in ants. "This article is part of a Special Issue entitled: Neotropical Behaviour".

  2. The agricultural pathology of ant fungus gardens

    PubMed Central

    Currie, Cameron R.; Mueller, Ulrich G.; Malloch, David

    1999-01-01

    Gardens of fungus-growing ants (Formicidae: Attini) traditionally have been thought to be free of microbial parasites, with the fungal mutualist maintained in nearly pure “monocultures.” We conducted extensive isolations of “alien” (nonmutualistic) fungi from ant gardens of a phylogenetically representative collection of attine ants. Contrary to the long-standing assumption that gardens are maintained free of microbial pathogens and parasites, they are in fact host to specialized parasites that are only known from attine gardens and that are found in most attine nests. These specialized garden parasites, belonging to the microfungus genus Escovopsis (Ascomycota: anamorphic Hypocreales), are horizontally transmitted between colonies. Consistent with theory of virulence evolution under this mode of pathogen transmission, Escovopsis is highly virulent and has the potential for rapid devastation of ant gardens, leading to colony mortality. The specialized parasite Escovopsis is more prevalent in gardens of the more derived ant lineages than in gardens of the more “primitive” (basal) ant lineages. Because fungal cultivars of derived attine lineages are asexual clones of apparently ancient origin whereas cultivars of primitive ant lineages were domesticated relatively recently from free-living sexual stocks, the increased virulence of pathogens associated with ancient asexual cultivars suggests an evolutionary cost to cultivar clonality, perhaps resulting from slower evolutionary rates of cultivars in the coevolutionary race with their pathogens. PMID:10393936

  3. Garden sharing and garden stealing in fungus-growing ants

    NASA Astrophysics Data System (ADS)

    Adams, Rachelle M. M.; Mueller, U. G.; Holloway, Alisha K.; Green, Abigail M.; Narozniak, Joanie

    Fungi cultivated by fungus-growing ants (Attini: Formicidae) are passed on between generations by transfer from maternal to offspring nest (vertical transmission within ant species). However, recent phylogenetic analyses revealed that cultivars are occasionally also transferred between attine species. The reasons for such lateral cultivar transfers are unknown. To investigate whether garden loss may induce ants to obtain a replacement cultivar from a neighboring colony (lateral cultivar transfer), pairs of queenright colonies of two Cyphomyrmex species were set up in two conjoined chambers; the garden of one colony was then removed to simulate the total crop loss that occurs naturally when pathogens devastate gardens. Garden-deprived colonies regained cultivars through one of three mechanisms: joining of a neighboring colony and cooperation in a common garden; stealing of a neighbor's garden; or aggressive usurpation of a neighbor's garden. Because pathogens frequently devastate attine gardens under natural conditions, garden joining, stealing and usurpation emerge as critical behavioral adaptations to survive garden catastrophes.

  4. The Florida Harvester Ant, Pogonomyrmex badius, Relies on Germination to Consume Large Seeds.

    PubMed

    Tschinkel, Walter R; Kwapich, Christina L

    2016-01-01

    The Florida harvester ant, Pogonomyrmex badius, is one of many ant species and genera that stores large numbers of seeds in damp, underground chambers for later consumption. A comparison of the sizes of seeds recovered from storage chambers with those of seed husks discarded following consumption revealed that the used seeds are far smaller than stored seeds. This difference in use-rate was confirmed in field and laboratory colonies by offering marked seeds of various sizes and monitoring the appearance of size-specific chaff. Because foragers collect a range of seed sizes but only open small seeds, large seeds accumulate, forming 70% or more of the weight of seed stores. Major workers increase the rates at which small and medium seeds are opened, but do not increase the size range of opened seeds. Experiments limiting ant access to portions of natural seed chambers showed that seeds germinate during storage, but that the ants rapidly remove them. When offered alongside non germinating seeds, germinating seeds were preferentially fed to larvae. The rate of germination during the annual cycle was determined by both burial in artificial chambers at various depths and under four laboratory temperatures. The germination rate depends upon the species of seed, the soil/laboratory temperature and/or the elapsed time. The seasonal soil temperature cycle generated germination patterns that vary with the mix of locally-available seeds. Taken together, exploitation of germination greatly increases the resources available to the ants in space and time. While the largest seeds may have the nutritional value of 15 small seeds, the inability of workers to open large seeds at will precludes them from rapid use during catastrophic events. The harvester ant's approach to seed harvesting is therefore two-pronged, with both immediate and delayed payoffs arising from the tendency to forage for a wide variety of seeds sizes.

  5. Positive effects of shade and shelter construction by ants on leafhopper-ant mutualism.

    PubMed

    Moya-Raygoza, Gustavo; Larsen, Kirk J

    2008-12-01

    The myrmecophilous five-spotted gamagrass leafhopper, Dalbulus quinquenotatus DeLong and Nault, and its tending ants on gamagrass Tripsacum dactyloides L. were examined to determine the influence of shade and ant-constructed shelters on the population sizes of D. quinquenotatus and ants. Gamagrass plants hosting ants and leafhoppers were exposed to 50, 30, or 0% artificially constructed shade. The greatest numbers of leafhoppers and ants were found on plants that received 50% shade. Shelters made by the ant Solenopsis geminata (F.) contained large numbers of leafhoppers and ants but were found only on T. dactyloides exposed to 50% shade in artificially constructed habitats. Additional sampling was conducted on wild gamagrass plants in the field to explore the presence of ants tending leafhoppers in shelters and to evaluate whether ant-constructed shelters protect leafhopper nymphs from parasitoid wasps. Large aggregations of S. geminata in shelters were also found in natural gamagrass habitats. Leafhopper nymphs living in shelters made by S. geminata may be protected against the dryinid wasp parasitoid Anteon ciudadi Olmi. No sheltered nymphs were parasitized by dryinids, whereas 24% of unsheltered nymphs had dryinid parasitism.

  6. ANTS AS BIOLOGICAL INDICATORS FOR MONITORING CHANGES IN ARID ENVIRONMENTS: LESSONS FOR MONITORING PROTECTED AREAS

    EPA Science Inventory

    The responses of ant communities to structural change (removal of an invasive were studied in a replicated experiment in a Chihuahuan Desert grassland. The results from sampling of ant communities by pit-fall trapping were validated by mapping ant colonies on the experimental plo...

  7. ANTS AS BIOLOGICAL INDICATORS FOR MONITORING CHANGES IN ARID ENVIRONMENTS: LESSONS FOR MONITORING PROTECTED AREAS

    EPA Science Inventory

    The responses of ant communities to structural change (removal of an invasive were studied in a replicated experiment in a Chihuahuan Desert grassland. The results from sampling of ant communities by pit-fall trapping were validated by mapping ant colonies on the experimental plo...

  8. ANTS AS BIOLOGICAL INDICATORS FOR MONITORING CHANGES IN ARID ENVIRONMENTS: LESSONS FOR MONITORING PROTECTED AREAS

    EPA Science Inventory

    The responses of ant communities to structural change (removal of an invasive
    were studied in a replicated experiment in a Chihuahuan Desert grassland. The
    results from sampling of ant communities by pit-fall trapping were validated by
    mapping ant colonies on the expe...

  9. ANTS AS BIOLOGICAL INDICATORS FOR MONITORING CHANGES IN ARID ENVIRONMENTS: LESSONS FOR MONITORING PROTECTED AREAS

    EPA Science Inventory

    The responses of ant communities to structural change (removal of an invasive
    were studied in a replicated experiment in a Chihuahuan Desert grassland. The
    results from sampling of ant communities by pit-fall trapping were validated by
    mapping ant colonies on the expe...

  10. Recognition of endophytic Trichoderma species by leaf-cutting ants and their potential in a Trojan-horse management strategy.

    PubMed

    Rocha, Silma L; Evans, Harry C; Jorge, Vanessa L; Cardoso, Lucimar A O; Pereira, Fernanda S T; Rocha, Fabiano B; Barreto, Robert W; Hart, Adam G; Elliot, Simon L

    2017-04-01

    Interactions between leaf-cutting ants, their fungal symbiont (Leucoagaricus) and the endophytic fungi within the vegetation they carry into their colonies are still poorly understood. If endophytes antagonistic to Leucoagaricus were found in plant material being carried by these ants, then this might indicate a potential mechanism for plants to defend themselves from leaf-cutter attack. In addition, it could offer possibilities for the management of these important Neotropical pests. Here, we show that, for Atta sexdens rubropilosa, there was a significantly greater incidence of Trichoderma species in the vegetation removed from the nests-and deposited around the