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Sample records for artificial ant colonies

  1. Variable selection for QSAR by artificial ant colony systems.

    PubMed

    Izrailev, S; Agrafiotis, D K

    2002-01-01

    Derivation of quantitative structure-activity relationships (QSAR) usually involves computational models that relate a set of input variables describing the structural properties of the molecules for which the activity has been measured to the output variable representing activity. Many of the input variables may be correlated, and it is therefore often desirable to select an optimal subset of the input variables that results in the most predictive model. In this paper we describe an optimization technique for variable selection based on artificial ant colony systems. The algorithm is inspired by the behavior of real ants, which are able to find the shortest path between a food source and their nest using deposits of pheromone as a communication agent. The underlying basic self-organizing principle is exploited for the construction of parsimonious QSAR models based on neural networks for several classical QSAR data sets. PMID:12184383

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  3. Abnormality detection in retinal images using ant colony optimization and artificial neural networks - biomed 2010.

    PubMed

    Kavitha, Ganesan; Ramakrishnan, Swaminathan

    2010-01-01

    Optic disc and retinal vasculature are important anatomical structures in the retina of the eye and any changes observed in these structures provide vital information on severity of various diseases. Digital retinal images are shown to provide a meaningful way of documenting and assessing some of the key elements inside the eye including the optic nerve and the tiny retinal blood vessels. In this work, an attempt has been made to detect and differentiate abnormalities of the retina using Digital image processing together with Optimization based segmentation and Artificial Neural Network methods. The retinal fundus images were recorded using standard protocols. Ant Colony Optimization is employed to extract the most significant objects namely the optic disc and blood vessel. The features related to these objects are obtained and corresponding indices are also derived. Further, these features are subjected to classification using Radial Basis Function Neural Networks and compared with conventional training algorithms. Results show that the Ant Colony Optimization is efficient in extracting useful information from retinal images. The features derived are effective for classification of normal and abnormal images using Radial basis function networks compared to other methods. As Optic disc and blood vessels are significant markers of abnormality in retinal images, the method proposed appears to be useful for mass screening. In this paper, the objectives of the study, methodology and significant observations are presented. PMID:20467104

  4. Evolutional Ant Colony Method Using PSO

    NASA Astrophysics Data System (ADS)

    Morii, Nobuto; Aiyoshi, Eitarou

    The ant colony method is one of heuristic methods capable of solving the traveling salesman problem (TSP), in which a good tour is generated by the artificial ant's probabilistic behavior. However, the generated tour length depends on the parameter describing the ant's behavior, and the best parameters corresponding to the problem to be solved is unknown. In this technical note, the evolutional strategy is presented to find the best parameter of the ant colony by using Particle Swarm Optimization (PSO) in the parameter space. Numerical simulations for benchmarks demonstrate effectiveness of the evolutional ant colony method.

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

    PubMed

    Greenfield, Gary; Machado, Penousal

    2015-01-01

    Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior. PMID:26280070

  6. Modeling the dynamics of ant colony optimization.

    PubMed

    Merkle, Daniel; Middendorf, Martin

    2002-01-01

    The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants that found good solutions. The behavior of ACO algorithms and the ACO model are analyzed for certain types of permutation problems. It is shown analytically that the decisions of an ant are influenced in an intriguing way by the use of the pheromone information and the properties of the pheromone matrix. This explains why ACO algorithms can show a complex dynamic behavior even when there is only one ant per iteration and no competition occurs. The ACO model is used to describe the algorithm behavior as a combination of situations with different degrees of competition between the ants. This helps to better understand the dynamics of the algorithm when there are several ants per iteration as is always the case when using ACO algorithms for optimization. Simulations are done to compare the behavior of the ACO model with the ACO algorithm. Results show that the deterministic model describes essential features of the dynamics of ACO algorithms quite accurately, while other aspects of the algorithms behavior cannot be found in the model. PMID:12227995

  7. 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.

  8. Spatial patterns in ant colonies.

    PubMed

    Theraulaz, Guy; Bonabeau, Eric; Nicolis, Stamatios C; Solé, Ricard V; Fourcassié, Vincent; Blanco, Stéphane; Fournier, Richard; Joly, Jean-Louis; Fernández, Pau; Grimal, Anne; Dalle, Patrice; Deneubourg, Jean-Louis

    2002-07-23

    The origins of large-scale spatial patterns in biology have been an important source of theoretical speculation since the pioneering work by Turing (1952) on the chemical basis of morphogenesis. Knowing how these patterns emerge and their functional role is important to our understanding of the evolution of biocomplexity and the role played by self organization. However, so far, conclusive evidence for local activation-long-range inhibition mechanisms in real biological systems has been elusive. Here a well-defined experimental and theoretical analysis of the pattern formation dynamics exhibited by clustering behavior in ant colonies is presented. These experiments and a simple mathematical model show that these colonies do indeed use this type of mechanism. All microscopic variables have been measured and provide the first evidence, to our knowledge, for this type of self-organized behavior in complex biological systems, supporting early conjectures about its role in the organization of insect societies. PMID:12114538

  9. 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

  10. Exploration adjustment by ant colonies.

    PubMed

    Doran, Carolina; Stumpe, Martin C; Sendova-Franks, Ana; Franks, Nigel R

    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

  11. Recruitment strategies and colony size in ants.

    PubMed

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

    2010-01-01

    Ants use a great variety of recruitment methods to forage for food or find new nests, including tandem running, group recruitment and scent trails. It has been known for some time that there is a loose correlation across many taxa between species-specific mature colony size and recruitment method. Very small colonies tend to use solitary foraging; small to medium sized colonies use tandem running or group recruitment whereas larger colonies use pheromone recruitment trails. Until now, explanations for this correlation have focused on the ants' ecology, such as food resource distribution. However, many species have colonies with a single queen and workforces that grow over several orders of magnitude, and little is known about how a colony's organization, including recruitment methods, may change during its growth. After all, recruitment involves interactions between ants, and hence the size of the colony itself may influence which recruitment method is used--even if the ants' behavioural repertoire remains unchanged. Here we show using mathematical models that the observed correlation can also be explained by recognizing that failure rates in recruitment depend differently on colony size in various recruitment strategies. Our models focus on the build up of recruiter numbers inside colonies and are not based on optimality arguments, such as maximizing food yield. We predict that ant colonies of a certain size should use only one recruitment method (and always the same one) rather than a mix of two or more. These results highlight the importance of the organization of recruitment and how it is affected by colony size. Hence these results should also expand our understanding of ant ecology. PMID:20694195

  12. Recruitment Strategies and Colony Size in Ants

    PubMed Central

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

    2010-01-01

    Ants use a great variety of recruitment methods to forage for food or find new nests, including tandem running, group recruitment and scent trails. It has been known for some time that there is a loose correlation across many taxa between species-specific mature colony size and recruitment method. Very small colonies tend to use solitary foraging; small to medium sized colonies use tandem running or group recruitment whereas larger colonies use pheromone recruitment trails. Until now, explanations for this correlation have focused on the ants' ecology, such as food resource distribution. However, many species have colonies with a single queen and workforces that grow over several orders of magnitude, and little is known about how a colony's organization, including recruitment methods, may change during its growth. After all, recruitment involves interactions between ants, and hence the size of the colony itself may influence which recruitment method is used—even if the ants' behavioural repertoire remains unchanged. Here we show using mathematical models that the observed correlation can also be explained by recognizing that failure rates in recruitment depend differently on colony size in various recruitment strategies. Our models focus on the build up of recruiter numbers inside colonies and are not based on optimality arguments, such as maximizing food yield. We predict that ant colonies of a certain size should use only one recruitment method (and always the same one) rather than a mix of two or more. These results highlight the importance of the organization of recruitment and how it is affected by colony size. Hence these results should also expand our understanding of ant ecology. PMID:20694195

  13. 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. PMID:23380232

  14. 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. PMID:24955402

  15. Collecting live ant specimens (colony sampling).

    PubMed

    Smith, Chris R; Tschinkel, Walter R

    2009-07-01

    Because of the great diversity of ants, it is difficult to give a single protocol for the collection of live specimens. Ant body size can be very small or extremely large; the ants can be hard or soft, sting or spray toxic chemicals, live in the open or in hard-to-reach places; and colony size can range from tens of individuals to millions. Thus, collection techniques must be tailored to each particular species. In particular, caution must always be taken when dealing with stinging species, and symptoms and basic first-aid measures, especially for the treatment of anaphylactic shock, should be reviewed before beginning fieldwork. Nonetheless, many species are collectable as whole colonies. This protocol reviews some basic techniques for collecting ground-nesting species and describes how to collect whole live colonies (with queens), which are necessary for long-term laboratory studies and addressing questions of social organization and ecology. PMID:20147204

  16. Microtubules viewed as molecular ant colonies.

    PubMed

    Tabony, James

    2006-10-01

    Populations of ants and other social insects self-organize and develop 'emergent' properties through stigmergy in which individual ants communicate with one another via chemical trails of pheromones that attract or repulse other ants. In this way, sophisticated properties and functions develop. Under appropriate conditions, in vitro microtubule preparations, initially comprised of only tubulin and GTP, behave in a similar manner. They self-organize and develop other higher-level emergent phenomena by a process where individual microtubules are coupled together by the chemical trails they produce by their own reactive growing and shrinking. This behaviour is described and compared with the behaviour of ant colonies. Viewing microtubules as populations of molecular ants may provide new insights as to how the cytoskeleton may spontaneously develop high-level functions. It is plausible that such processes occur during the early stages of embryogenesis and in cells. PMID:16968217

  17. Ant colony optimization and stochastic gradient descent.

    PubMed

    Meuleau, Nicolas; Dorigo, Marco

    2002-01-01

    In this article, we study the relationship between the two techniques known as ant colony optimization (ACO) and stochastic gradient descent. More precisely, we show that some empirical ACO algorithms approximate stochastic gradient descent in the space of pheromones, and we propose an implementation of stochastic gradient descent that belongs to the family of ACO algorithms. We then use this insight to explore the mutual contributions of the two techniques. PMID:12171633

  18. 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.

  19. 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. PMID:24334742

  20. 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.

  1. 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.

  2. 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.

  3. 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. PMID:26839533

  4. 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

  5. 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

  6. Nest- and colony-mate recognition in polydomous colonies of meat ants ( Iridomyrmex purpureus)

    NASA Astrophysics Data System (ADS)

    van Wilgenburg, E.; Ryan, D.; Morrison, P.; Marriott, P. J.; Elgar, M. A.

    2006-07-01

    Workers of polydomous colonies of social insects must recognize not only colony-mates residing in the same nest but also those living in other nests. We investigated the impact of a decentralized colony structure on colony- and nestmate recognition in the polydomous Australian meat ant ( Iridomyrmex purpureus). Field experiments showed that ants of colonies with many nests were less aggressive toward alien conspecifics than those of colonies with few nests. In addition, while meat ants were almost never aggressive toward nestmates, they were frequently aggressive when confronted with an individual from a different nest within the same colony. Our chemical analysis of the cuticular hydrocarbons of workers using a novel comprehensive two-dimensional gas chromatography technique that increases the number of quantifiable compounds revealed both colony- and nest-specific patterns. Combined, these data indicate an incomplete transfer of colony odor between the nests of polydomous meat ant colonies.

  7. 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.

  8. The hyper-cube framework for ant colony optimization.

    PubMed

    Blum, Christian; Dorigo, Marco

    2004-04-01

    Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way of implementing ant colony optimization algorithms, this framework limits the pheromone values to the interval [0,1]. This is obtained by introducing changes in the pheromone value update rule. These changes can in general be applied to any pheromone value update rule used in ant colony optimization. We discuss the benefits coming with this new framework. The benefits are twofold. On the theoretical side, the new framework allows us to prove that in Ant System, the ancestor of all ant colony optimization algorithms, the average quality of the solutions produced increases in expectation over time when applied to unconstrained problems. On the practical side, the new framework automatically handles the scaling of the objective function values. We experimentally show that this leads on average to a more robust behavior of ant colony optimization algorithms. PMID:15376861

  9. A binary ant colony optimization classifier for molecular activities.

    PubMed

    Hammann, Felix; Suenderhauf, Claudia; Huwyler, Jörg

    2011-10-24

    Chemical fingerprints encode the presence or absence of molecular features and are available in many large databases. Using a variation of the Ant Colony Optimization (ACO) paradigm, we describe a binary classifier based on feature selection from fingerprints. We discuss the algorithm and possible cross-validation procedures. As a real-world example, we use our algorithm to analyze a Plasmodium falciparum inhibition assay and contrast its performance with other machine learning paradigms in use today (decision tree induction, random forests, support vector machines, artificial neural networks). Our algorithm matches established paradigms in predictive power, yet supplies the medicinal chemist and basic researcher with easily interpretable results. Furthermore, models generated with our paradigm are easy to implement and can complement virtual screenings by additionally exploiting the precalculated fingerprint information. PMID:21854036

  10. Robustness of Ant Colony Optimization to Noise.

    PubMed

    Friedrich, Tobias; Kötzing, Timo; Krejca, Martin S; Sutton, Andrew M

    2016-01-01

    Recently, ant colony optimization (ACO) algorithms have proven to be efficient in uncertain environments, such as noisy or dynamically changing fitness functions. Most of these analyses have focused on combinatorial problems such as path finding. We rigorously analyze an ACO algorithm optimizing linear pseudo-Boolean functions under additive posterior noise. We study noise distributions whose tails decay exponentially fast, including the classical case of additive Gaussian noise. Without noise, the classical [Formula: see text] EA outperforms any ACO algorithm, with smaller [Formula: see text] being better; however, in the case of large noise, the [Formula: see text] EA fails, even for high values of [Formula: see text] (which are known to help against small noise). In this article, we show that ACO is able to deal with arbitrarily large noise in a graceful manner; that is, as long as the evaporation factor [Formula: see text] is small enough, dependent on the variance [Formula: see text] of the noise and the dimension n of the search space, optimization will be successful. We also briefly consider the case of prior noise and prove that ACO can also efficiently optimize linear functions under this noise model. PMID:26928850

  11. 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. PMID:24407312

  12. Harvester ants (Hymenoptera: Formicidae) discriminate among artificial seeds with different protein contents

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Workers of colonies of the western harvester ant, Pogonomyrmex occidentalis, were recruited to patches of artificial seed of the same caloric value but different protein content. Rates of forager returns with artificial seeds containing five percent protein were nearly twice those of zero percent pr...

  13. 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

  14. 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. PMID:25372856

  15. An ant colony approach for image texture classification

    NASA Astrophysics Data System (ADS)

    Ye, Zhiwei; Zheng, Zhaobao; Ning, Xiaogang; Yu, Xin

    2005-10-01

    Ant colonies, and more generally social insect societies, are distributed systems that show a highly structured social organization in spite of the simplicity of their individuals. As a result of this swarm intelligence, ant colonies can accomplish complex tasks that far exceed the individual capacities of a single ant. As is well known that aerial image texture classification is a long-term difficult problem, which hasn't been fully solved. This paper presents an ant colony optimization methodology for image texture classification, which assigns N images into K type of clusters as clustering is viewed as a combinatorial optimization problem in the article. The algorithm has been tested on some real images and performance of this algorithm is superior to k-means algorithm. Computational simulations reveal very encouraging results in terms of the quality of solution found.

  16. 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. PMID:25505534

  17. 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.

  18. 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

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

    PubMed

    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

  20. 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

  1. 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. PMID:10985038

  2. 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.

  3. 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

  4. 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. PMID:26383861

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

    PubMed Central

    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. PMID:26383861

  6. 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.

  7. 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.

  8. Response Ant Colony Optimization of end milling surface roughness.

    PubMed

    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

  9. Ant Colony Optimization With Combining Gaussian Eliminations for Matrix Multiplication.

    PubMed

    Zhou, Yuren; Lai, Xinsheng; Li, Yuanxiang; Dong, Wenyong

    2013-02-01

    One of the main unsolved problems in computer algebra is to determine the minimal number of multiplications which is necessary to compute the product of two matrices. For practical value, the small format is of special interest. This leads to a combinatorial optimization problem which is unlikely solved in polynomial time. In this paper, we present a method called combining Gaussian eliminations to reduce the number of variables in this optimization problem and use heuristic ant colony algorithm to solve the problem. The results of experiments on 2 × 2 case show that our algorithm achieves significant performance gains. Extending this algorithm from 2 × 2 case to 3 × 3 case is also discussed. Index Terms—Ant colony optimization (ACO), evolutionary algorithms, Gaussian eliminations, matrix multiplication, multiplicative complexity, Strassen's algorithm. PMID:22835561

  10. 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.

  11. 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

  12. Advances on image interpolation based on ant colony algorithm.

    PubMed

    Rukundo, Olivier; Cao, Hanqiang

    2016-01-01

    This paper presents an advance on image interpolation based on ant colony algorithm (AACA) for high resolution image scaling. The difference between the proposed algorithm and the previously proposed optimization of bilinear interpolation based on ant colony algorithm (OBACA) is that AACA uses global weighting, whereas OBACA uses local weighting scheme. The strength of the proposed global weighting of AACA algorithm depends on employing solely the pheromone matrix information present on any group of four adjacent pixels to decide which case deserves a maximum global weight value or not. Experimental results are further provided to show the higher performance of the proposed AACA algorithm with reference to the algorithms mentioned in this paper. PMID:27047729

  13. 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. PMID:16053571

  14. 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.

  15. Design of broadband omnidirectional antireflection coatings using ant colony algorithm.

    PubMed

    Guo, X; Zhou, H Y; Guo, S; Luan, X X; Cui, W K; Ma, Y F; Shi, L

    2014-06-30

    Optimization method which is based on the ant colony algorithm (ACA) is described to optimize antireflection (AR) coating system with broadband omnidirectional characteristics for silicon solar cells incorporated with the solar spectrum (AM1.5 radiation). It's the first time to use ACA method for optimizing the AR coating system. In this paper, for the wavelength range from 400 nm to 1100 nm, the optimized three-layer AR coating system could provide an average reflectance of 2.98% for incident angles from Raveθ+ to 80° and 6.56% for incident angles from 0° to 90°. PMID:24978076

  16. Ant colony optimization as a method for strategic genotype sampling.

    PubMed

    Spangler, M L; Robbins, K R; Bertrand, J K; Macneil, M; Rekaya, R

    2009-06-01

    A simulation study was carried out to develop an alternative method of selecting animals to be genotyped. Simulated pedigrees included 5000 animals, each assigned genotypes for a bi-allelic single nucleotide polymorphism (SNP) based on assumed allelic frequencies of 0.7/0.3 and 0.5/0.5. In addition to simulated pedigrees, two beef cattle pedigrees, one from field data and the other from a research population, were used to test selected methods using simulated genotypes. The proposed method of ant colony optimization (ACO) was evaluated based on the number of alleles correctly assigned to ungenotyped animals (AK(P)), the probability of assigning true alleles (AK(G)) and the probability of correctly assigning genotypes (APTG). The proposed animal selection method of ant colony optimization was compared to selection using the diagonal elements of the inverse of the relationship matrix (A(-1)). Comparisons of these two methods showed that ACO yielded an increase in AK(P) ranging from 4.98% to 5.16% and an increase in APTG from 1.6% to 1.8% using simulated pedigrees. Gains in field data and research pedigrees were slightly lower. These results suggest that ACO can provide a better genotyping strategy, when compared to A(-1), with different pedigree sizes and structures. PMID:19220227

  17. 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.

  18. Using Ant Colony Optimization for Routing in VLSI Chips

    NASA Astrophysics Data System (ADS)

    Arora, Tamanna; Moses, Melanie

    2009-04-01

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

  19. Routing in Ad Hoc Network Using Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Khanpara, Pimal; Valiveti, Sharada; Kotecha, K.

    The ad hoc networks have dynamic topology and are infrastructure less. So it is required to implement a new network protocol for providing efficient end to end communication based on TCP/IP structure. There is a need to re-define or modify the functions of each layer of TCP/IP model to provide end to end communication between nodes. The mobility of the nodes and the limited resources are the main reason for this change. The main challenge in ad hoc networks is routing. Due to the mobility of the nodes in the ad hoc networks, routing becomes very difficult. Ant based algorithms are suitable for routing in ad hoc networks due to its dynamic nature and adaptive behavior. There are number of routing algorithms based on the concept of ant colony optimizations. It is quite difficult to determine the best ant based algorithm for routing as these algorithms perform differently under various circumstances such as the traffic distribution and network topology. In this paper, the overview of such routing algorithms is given.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  1. Reconstruction of phylogenetic trees using the ant colony optimization paradigm.

    PubMed

    Perretto, Mauricio; Lopes, Heitor Silvério

    2005-01-01

    We developed a new approach for the reconstruction of phylogenetic trees using ant colony optimization metaheuristics. A tree is constructed using a fully connected graph and the problem is approached similarly to the well-known traveling salesman problem. This methodology was used to develop an algorithm for constructing a phylogenetic tree using a pheromone matrix. Two data sets were tested with the algorithm: complete mitochondrial genomes from mammals and DNA sequences of the p53 gene from several eutherians. This new methodology was found to be superior to other well-known softwares, at least for this data set. These results are very promising and suggest more efforts for further developments. PMID:16342043

  2. Wavelet phase estimation using ant colony optimization algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Shangxu; Yuan, Sanyi; Ma, Ming; Zhang, Rui; Luo, Chunmei

    2015-11-01

    Eliminating seismic wavelet is important in seismic high-resolution processing. However, artifacts may arise in seismic interpretation when the wavelet phase is inaccurately estimated. Therefore, we propose a frequency-dependent wavelet phase estimation method based on the ant colony optimization (ACO) algorithm with global optimization capacity. The wavelet phase can be optimized with the ACO algorithm by fitting nearby-well seismic traces with well-log data. Our proposed method can rapidly produce a frequency-dependent wavelet phase and optimize the seismic-to-well tie, particularly for weak signals. Synthetic examples demonstrate the effectiveness of the proposed ACO-based wavelet phase estimation method, even in the presence of a colored noise. Real data example illustrates that seismic deconvolution using an optimum mixed-phase wavelet can provide more information than that using an optimum constant-phase wavelet.

  3. Multiple ant colony algorithm method for selecting tag SNPs.

    PubMed

    Liao, Bo; Li, Xiong; Zhu, Wen; Li, Renfa; Wang, Shulin

    2012-10-01

    The search for the association between complex disease and single nucleotide polymorphisms (SNPs) or haplotypes has recently received great attention. Finding a set of tag SNPs for haplotyping in a great number of samples is an important step to reduce cost for association study. Therefore, it is essential to select tag SNPs with more efficient algorithms. In this paper, we model problem of selection tag SNPs by MINIMUM TEST SET and use multiple ant colony algorithm (MACA) to search a smaller set of tag SNPs for haplotyping. The various experimental results on various datasets show that the running time of our method is less than GTagger and MLR. And MACA can find the most representative SNPs for haplotyping, so that MACA is more stable and the number of tag SNPs is also smaller than other evolutionary methods (like GTagger and NSGA-II). Our software is available upon request to the corresponding author. PMID:22480582

  4. Particle Swarm and Ant Colony Approaches in Multiobjective Optimization

    NASA Astrophysics Data System (ADS)

    Rao, S. S.

    2010-10-01

    The social behavior of groups of birds, ants, insects and fish has been used to develop evolutionary algorithms known as swarm intelligence techniques for solving optimization problems. This work presents the development of strategies for the application of two of the popular swarm intelligence techniques, namely the particle swarm and ant colony methods, for the solution of multiobjective optimization problems. In a multiobjective optimization problem, the objectives exhibit a conflicting nature and hence no design vector can minimize all the objectives simultaneously. The concept of Pareto-optimal solution is used in finding a compromise solution. A modified cooperative game theory approach, in which each objective is associated with a different player, is used in this work. The applicability and computational efficiencies of the proposed techniques are demonstrated through several illustrative examples involving unconstrained and constrained problems with single and multiple objectives and continuous and mixed design variables. The present methodologies are expected to be useful for the solution of a variety of practical continuous and mixed optimization problems involving single or multiple objectives with or without constraints.

  5. The Role of Anchor-Tipped Larval Hairs in the Organization of Ant Colonies

    PubMed Central

    Penick, Clint A.; Copple, R. Neale; Mendez, Raymond A.; Smith, Adrian A.

    2012-01-01

    The spatial organization within a social insect colony is a key component of colony life. It influences individual interaction rates, resource distribution, and division of labor within the nest. Yet studies of social insect behavior are most often carried out in artificial constructions, which may change worker behavior and colony organization. We observed how workers of the ant Pheidole rhea organized brood in nests with deep chambers and textured walls that were designed to mimic their natural constructions more closely. Instead of clumping larvae into piles on the chamber floor, workers suspended fourth-instar larvae from the vertical walls and ceiling of each chamber while young larvae and pupae were clumped at the base. Fourth-instar larvae possess five rows of anchor-tipped hairs on their dorsal side, and we predicted that these hairs functioned to attach larvae to the nest walls. We gave larvae “haircuts,” where only the anchor-tipped hairs were removed, and then tested their ability to adhere to a textured surface raised to an angle of 90° and then 120° with respect to the horizontal plane. Larvae whose hairs had been clipped came unattached in almost all trials, while larvae whose hairs remained intact stayed attached. This confirmed that anchor-tipped hairs functioned to attach larvae to the walls of the nest. The presence of anchor-tipped hairs is widespread and has been documented in at least 22 genera from the ant subfamily Myrmicinae, including species that occur in a variety of environments and represent a broad range of nesting habits. Based on our results, it is likely that many species exhibit this larval hanging behavior, and this could impact colony characteristics such as spatial organization and the care of developing larvae by nurse workers. PMID:22848539

  6. 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.

  7. Adaptive tracking and compensation of laser spot based on ant colony optimization

    NASA Astrophysics Data System (ADS)

    Yang, Lihong; Ke, Xizheng; Bai, Runbing; Hu, Qidi

    2009-05-01

    Because the effect of atmospheric scattering and atmospheric turbulence on laser signal of atmospheric absorption,laser spot twinkling, beam drift and spot split-up occur ,when laser signal transmits in the atmospheric channel. The phenomenon will be seriously affects the stability and the reliability of laser spot receiving system. In order to reduce the influence of atmospheric turbulence, we adopt optimum control thoughts in the field of artificial intelligence, propose a novel adaptive optical control technology-- model-free optimized adaptive control technology, analyze low-order pattern wave-front error theory, in which an -adaptive optical system is employed to adjust errors, and design its adaptive structure system. Ant colony algorithm is the control core algorithm, which is characteristic of positive feedback, distributed computing and greedy heuristic search. . The ant colony algorithm optimization of adaptive optical phase compensation is simulated. Simulation result shows that, the algorithm can effectively control laser energy distribution, improve laser light beam quality, and enhance signal-to-noise ratio of received signal.

  8. 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. PMID:26197456

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Queen movement during colony emigration in the facultatively polygynous ant Pachycondyla obscuricornis

    NASA Astrophysics Data System (ADS)

    Pezon, Antoine; Denis, Damien; Cerdan, Philippe; Valenzuela, Jorge; Fresneau, Dominique

    2005-01-01

    In ants, nest relocations are frequent but nevertheless perilous, especially for the reproductive caste. During emigrations, queens are exposed to predation and face the risk of becoming lost. Therefore the optimal strategy should be to move the queen(s) swiftly to a better location, while maintaining maximum worker protection at all times in the new and old nests. The timing of that event is a crucial strategic issue for the colony and may depend on queen number. In monogynous colonies, the queen is vital for colony survival, whereas in polygynous colonies a queen is less essential, if not dispensable. We tested the null hypothesis that queen movement occurs at random within the sequence of emigration events in both monogynous and polygynous colonies of the ponerine ant Pachycondyla obscuricornis. Our study, based on 16 monogynous and 16 polygynous colony emigrations, demonstrates for the first time that regardless of the number of queens per colony, the emigration serial number of a queen occurs in the middle of all emigration events and adult ant emigration events, but not during brood transport events. It therefore appears that the number of workers in both nests plays an essential role in the timing of queen movement. Our results correspond to a robust colony-level strategy since queen emigration is related neither to colony size nor to queen number. Such an optimal strategy is characteristic of ant societies working as highly integrated units and represents a new instance of group-level adaptive behaviors in social insect colonies.

  15. Path efficiency of ant foraging trails in an artificial network.

    PubMed

    Vittori, Karla; Talbot, Grégoire; Gautrais, Jacques; Fourcassié, Vincent; Araújo, Aluizio F R; Theraulaz, Guy

    2006-04-21

    In this paper we present an individual-based model describing the foraging behavior of ants moving in an artificial network of tunnels in which several interconnected paths can be used to reach a single food source. Ants lay a trail pheromone while moving in the network and this pheromone acts as a system of mass recruitment that attracts other ants in the network. The rules implemented in the model are based on measures of the decisions taken by ants at tunnel bifurcations during real experiments. The collective choice of the ants is estimated by measuring their probability to take a given path in the network. Overall, we found a good agreement between the results of the simulations and those of the experiments, showing that simple behavioral rules can lead ants to find the shortest paths in the network. The match between the experiments and the model, however, was better for nestbound than for outbound ants. A sensitivity study of the model suggests that the bias observed in the choice of the ants at asymmetrical bifurcations is a key behavior to reproduce the collective choice observed in the experiments. PMID:16199059

  16. 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.

  17. 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. PMID:27441151

  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. 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

  20. 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. PMID:27149517

  1. Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm.

    PubMed

    Zhou, Dongsheng; Wang, Lan; Zhang, Qiang

    2016-01-01

    With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In this paper, we proposed an improved ant colony algorithm to solve this problem, which is effective and simple. Firstly, the models were established respectively, including the kinematic model of space manipulator and expression of valid path in space environment. Secondly, we described an improved ant colony algorithm in detail, which can avoid trapping into local optimum. The search strategy, transfer rules, and pheromone update methods were all adjusted. Finally, the improved ant colony algorithm was compared with the classic ant colony algorithm through the experiments. The simulation results verify the correctness and effectiveness of the proposed algorithm. PMID:27186473

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  3. 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. PMID:16539147

  4. [Application of rational ant colony optimization to improve the reproducibility degree of laser three-dimensional copy].

    PubMed

    Cui, Xiao-Yan; Huo, Zhong-Gang; Xin, Zhong-Hua; Tian, Xiao; Zhang, Xiao-Dong

    2013-07-01

    Three-dimensional (3D) copying of artificial ears and pistol printing are pushing laser three-dimensional copying technique to a new page. Laser three-dimensional scanning is a fresh field in laser application, and plays an irreplaceable part in three-dimensional copying. Its accuracy is the highest among all present copying techniques. Reproducibility degree marks the agreement of copied object with the original object on geometry, being the most important index property in laser three-dimensional copying technique. In the present paper, the error of laser three-dimensional copying was analyzed. The conclusion is that the data processing to the point cloud of laser scanning is the key technique to reduce the error and increase the reproducibility degree. The main innovation of this paper is as follows. On the basis of traditional ant colony optimization, rational ant colony optimization algorithm proposed by the author was applied to the laser three-dimensional copying as a new algorithm, and was put into practice. Compared with customary algorithm, rational ant colony optimization algorithm shows distinct advantages in data processing of laser three-dimensional copying, reducing the error and increasing the reproducibility degree of the copy. PMID:24059192

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Two distinct forms of colony social organization occur in the fire ant Solenopsis invicta: Colonies of the monogyne social form are headed by a single egg-laying queen, whereas those of the polygyne social form contain multiple egg-laying queens. Recent studies have demonstrated that genetic variati...

  7. 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.

  8. Pixel-based ant colony algorithm for source mask optimization

    NASA Astrophysics Data System (ADS)

    Kuo, Hung-Fei; Wu, Wei-Chen; Li, Frederick

    2015-03-01

    Source mask optimization (SMO) was considered to be one of the key resolution enhancement techniques for node technology below 20 nm prior to the availability of extreme-ultraviolet tools. SMO has been shown to enlarge the process margins for the critical layer in SRAM and memory cells. In this study, a new illumination shape optimization approach was developed on the basis of the ant colony optimization (ACO) principle. The use of this heuristic pixel-based ACO method in the SMO process provides an advantage over the extant SMO method because of the gradient of the cost function associated with the rapid and stable searching capability of the proposed method. This study was conducted to provide lithographic engineers with references for the quick determination of the optimal illumination shape for complex mask patterns. The test pattern used in this study was a contact layer for SRAM design, with a critical dimension and a minimum pitch of 55 and 110 nm, respectively. The optimized freeform source shape obtained using the ACO method was numerically verified by performing an aerial image investigation, and the result showed that the optimized freeform source shape generated an aerial image profile different from the nominal image profile and with an overall error rate of 9.64%. Furthermore, the overall average critical shape difference was determined to be 1.41, which was lower than that for the other off-axis illumination exposure. The process window results showed an improvement in exposure latitude (EL) and depth of focus (DOF) for the ACO-based freeform source shape compared with those of the Quasar source shape. The maximum EL of the ACO-based freeform source shape reached 7.4% and the DOF was 56 nm at an EL of 5%.

  9. Effect of time on colony odour stability in the ant Formica exsecta

    NASA Astrophysics Data System (ADS)

    Martin, S. J.; Shemilt, S.; Drijfhout, F. P.

    2012-04-01

    Among social insects, maintaining a distinct colony profile allows individuals to distinguish easily between nest mates and non-nest mates. In ants, colony-specific profiles can be encoded within their cuticular hydrocarbons, and these are influenced by both environmental and genetic factors. Using nine monogynous Formica exsecta ant colonies, we studied the stability of their colony-specific profiles at eight time points over a 4-year period. We found no significant directional change in any colony profile, suggesting that genetic factors are maintaining this stability. However, there were significant short-term effects of season that affected all colony profiles in the same direction. Despite these temporal changes, no significant change in the profile variation within colonies was detected: each colony's profile responded in similar manner between seasons, with nest mates maintaining closely similar profiles, distinct from other colonies. These findings imply that genetic factors may help maintain the long-term stability of colony profile, but environmental factors can influence the profiles over shorter time periods. However, environmental factors do not contribute significantly to the maintenance of diversity among colonies, since all colonies were affected in a similar way.

  10. 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

  11. An adaptive ant colony system algorithm for continuous-space optimization problems.

    PubMed

    Li, Yan-jun; Wu, Tie-jun

    2003-01-01

    Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates. Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved. PMID:12656341

  12. 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. PMID:25059256

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

    PubMed

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

    2016-01-01

    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

  14. A Hybrid Routing Algorithm Based on Ant Colony and ZHLS Routing Protocol for MANET

    NASA Astrophysics Data System (ADS)

    Rafsanjani, Marjan Kuchaki; Asadinia, Sanaz; Pakzad, Farzaneh

    Mobile Ad hoc networks (MANETs) require dynamic routing schemes for adequate performance. This paper, presents a new routing algorithm for MANETs, which combines the idea of ant colony optimization with Zone-based Hierarchical Link State (ZHLS) protocol. Ant colony optimization (ACO) is a class of Swarm Intelligence (SI) algorithms. SI is the local interaction of many simple agents to achieve a global goal. SI is based on social insect for solving different types of problems. ACO algorithm uses mobile agents called ants to explore network. Ants help to find paths between two nodes in the network. Our algorithm is based on ants jump from one zone to the next zones which contains of the proactive routing within a zone and reactive routing between the zones. Our proposed algorithm improves the performance of the network such as delay, packet delivery ratio and overhead than traditional routing algorithms.

  15. 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.

  16. 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

  17. 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. PMID:26465750

  18. 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

  19. Inverse transient radiation analysis in one-dimensional participating slab using improved Ant Colony Optimization algorithms

    NASA Astrophysics Data System (ADS)

    Zhang, B.; Qi, H.; Ren, Y. T.; Sun, S. C.; Ruan, L. M.

    2014-01-01

    As a heuristic intelligent optimization algorithm, the Ant Colony Optimization (ACO) algorithm was applied to the inverse problem of a one-dimensional (1-D) transient radiative transfer in present study. To illustrate the performance of this algorithm, the optical thickness and scattering albedo of the 1-D participating slab medium were retrieved simultaneously. The radiative reflectance simulated by Monte-Carlo Method (MCM) and Finite Volume Method (FVM) were used as measured and estimated value for the inverse analysis, respectively. To improve the accuracy and efficiency of the Basic Ant Colony Optimization (BACO) algorithm, three improved ACO algorithms, i.e., the Region Ant Colony Optimization algorithm (RACO), Stochastic Ant Colony Optimization algorithm (SACO) and Homogeneous Ant Colony Optimization algorithm (HACO), were developed. By the HACO algorithm presented, the radiative parameters could be estimated accurately, even with noisy data. In conclusion, the HACO algorithm is demonstrated to be effective and robust, which had the potential to be implemented in various fields of inverse radiation problems.

  20. 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.

  1. 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.

  2. Blochmannia endosymbionts improve colony growth and immune defence in the ant Camponotus fellah

    PubMed Central

    2009-01-01

    Background Microorganisms are a large and diverse form of life. Many of them live in association with large multicellular organisms, developing symbiotic relations with the host and some have even evolved to form obligate endosymbiosis [1]. All Carpenter ants (genus Camponotus) studied hitherto harbour primary endosymbiotic bacteria of the Blochmannia genus. The role of these bacteria in ant nutrition has been demonstrated [2] but the omnivorous diet of these ants lead us to hypothesize that the bacteria might provide additional advantages to their host. In this study, we establish links between Blochmannia, growth of starting new colonies and the host immune response. Results We manipulated the number of bacterial endosymbionts in incipient laboratory-reared colonies of Camponotus fellah by administrating doses of an antibiotic (Rifampin) mixed in honey-solution. Efficiency of the treatment was estimated by quantitative polymerase chain reaction and Fluorescent in situ hybridization (FISH), using Blochmannia specific primers (qPCR) and two fluorescent probes (one for all Eubacterial and other specific for Blochmannia). Very few or no bacteria could be detected in treated ants. Incipient Rifampin treated colonies had significantly lower numbers of brood and adult workers than control colonies. The immune response of ants from control and treated colonies was estimated by inserting nylon filaments in the gaster and removing it after 24 h. In the control colonies, the encapsulation response was positively correlated to the bacterial amount, while no correlation was observed in treated colonies. Indeed, antibiotic treatment increased the encapsulation response of the workers, probably due to stress conditions. Conclusion The increased growth rate observed in non-treated colonies confirms the importance of Blochmannia in this phase of colony development. This would provide an important selective advantage during colony founding, where the colonies are faced with severe

  3. 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. PMID:26162304

  4. Application of ant colony algorithm in plant leaves classification based on infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Guo, Tiantai; Hong, Bo; Kong, Ming; Zhao, Jun

    2014-04-01

    This paper proposes to use ant colony algorithm in the analysis of spectral data of plant leaves to achieve the best classification of different plants within a short time. Intelligent classification is realized according to different components of featured information included in near infrared spectrum data of plants. The near infrared diffusive emission spectrum curves of the leaves of Cinnamomum camphora and Acer saccharum Marsh are acquired, which have 75 leaves respectively, and are divided into two groups. Then, the acquired data are processed using ant colony algorithm and the same kind of leaves can be classified as a class by ant colony clustering algorithm. Finally, the two groups of data are classified into two classes. Experiment results show that the algorithm can distinguish different species up to the percentage of 100%. The classification of plant leaves has important application value in agricultural development, research of species invasion, floriculture etc.

  5. Host specificity and colony impacts of the fire ant pathogen, Solenopsis invicta virus 3.

    PubMed

    Porter, Sanford D; Valles, Steven M; Oi, David H

    2013-09-01

    An understanding of host specificity is essential before pathogens can be used as biopesticides or self-sustaining biocontrol agents. In order to define the host range of the recently discovered Solenopsis invicta virus 3 (SINV-3), we exposed laboratory colonies of 19 species of ants in 14 genera and 4 subfamilies to this virus. Despite extreme exposure during these tests, active, replicating infections only occurred in Solenopsis invicta Buren and hybrid (S. invicta×S. richteri) fire ant colonies. The lack of infections in test Solenopsis geminata fire ants from the United States indicates that SINV-3 is restricted to the saevissima complex of South American fire ants, especially since replicating virus was also found in several field-collected samples of the black imported fire ant, Solenopsis richteri Forel. S. invicta colonies infected with SINV-3 declined dramatically with average brood reductions of 85% or more while colonies of other species exposed to virus remained uninfected and healthy. The combination of high virulence and high host specificity suggest that SINV-3 has the potential for use as either a biopesticide or a self-sustaining biocontrol agent. PMID:23665158

  6. MAS Equipped with Ant Colony Applied into Dynamic Job Shop Scheduling

    NASA Astrophysics Data System (ADS)

    Kang, Kai; Zhang, Ren Feng; Yang, Yan Qing

    This paper presents a methodology adopting the new structure of MAS(multi-agent system) equipped with ACO(ant colony optimization) algorithm for a better schedule in dynamic job shop. In consideration of the dynamic events in the job shop arriving indefinitely schedules are generated based on tasks with ant colony algorithm. Meanwhile, the global objective is taken into account for the best solution in the actual manufacturing environment. The methodology is tested on a simulated job shop to determine the impact with the new structure.

  7. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence.

    PubMed

    Srinivasan, Thenmozhi; Palanisamy, Balasubramanie

    2015-01-01

    Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets. PMID:26495413

  8. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

    PubMed Central

    Srinivasan, Thenmozhi; Palanisamy, Balasubramanie

    2015-01-01

    Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets. PMID:26495413

  9. A clustering routing algorithm based on improved ant colony clustering for wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Xiao, Xiaoli; Li, Yang

    Because of real wireless sensor network node distribution uniformity, this paper presents a clustering strategy based on the ant colony clustering algorithm (ACC-C). To reduce the energy consumption of the head near the base station and the whole network, The algorithm uses ant colony clustering on non-uniform clustering. The improve route optimal degree is presented to evaluate the performance of the chosen route. Simulation results show that, compared with other algorithms, like the LEACH algorithm and the improve particle cluster kind of clustering algorithm (PSC - C), the proposed approach is able to keep away from the node with less residual energy, which can improve the life of networks.

  10. 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

  11. 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

  12. 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

  13. 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. PMID:27529548

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  15. 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.

  16. Protein folding in hydrophobic-polar lattice model: a flexible ant-colony optimization approach.

    PubMed

    Hu, Xiao-Min; Zhang, Jun; Xiao, Jing; Li, Yun

    2008-01-01

    This paper proposes a flexible ant colony (FAC) algorithm for solving protein folding problems based on the hydrophobic-polar square lattice model. Collaborations of novel pheromone and heuristic strategies in the proposed algorithm make it more effective in predicting structures of proteins compared with other state-of-the-art algorithms. PMID:18537736

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  19. 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

  20. 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. PMID:25025089

  1. 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

  2. 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…

  3. How an ant manages to display individual and colonial signals by using the same channel.

    PubMed

    Denis, Damien; Blatrix, Rumsaïs; Fresneau, Dominique

    2006-08-01

    Cuticular hydrocarbons are used by some ants to discriminate nestmates from nonnestmates. Every member of the colony bears the same pattern because they are continuously exchanged among nestmates. The postpharyngeal gland (PPG) stores the blend of hydrocarbons and is involved in the distribution of this common mixture. However, some individuals might display individual information on the cuticle (such as a chemical signal of fertility) that must not be mixed within the common pool. We investigated how this paradox is solved in the ant Pachycondyla goeldii by analyzing the nature and localization of colonial and fertility signals. Workers in a queenless condition showed a dominance hierarchy that was correlated with ovarian development. Hydrocarbons from the cuticle and the PPG analyzed by gas chromatography (GC) and identified by GC-mass spectrometry showed a clear discrimination among colonies, supporting the involvement of the PPG in the colonial identity signal. We identified and selected 11 cuticular hydrocarbons that permitted us to discriminate ovarian development classes and that might function as a fertility signal. They allowed clear colony discrimination as well, which suggests that the two signals (the individual signal of fertility and the common signal of colony identity) can be conveyed by the same compounds. However, the hydrocarbons in the PPG did not discriminate among ovarian developmental classes, suggesting that the portion of variation in the cuticular hydrocarbons constituting the fertility signal is superimposed on the signal of colony identity. PMID:16871445

  4. 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.

  5. 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. PMID:25954768

  6. 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

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  9. 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. PMID:17980590

  10. 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

  11. Serial Monodomy in the Gypsy Ant, Aphaenogaster araneoides: Does Nest Odor Reduction Influence Colony Relocation?

    PubMed Central

    McGlynn, Terry

    2010-01-01

    Serial monodomy is the nesting behavior in which a colony of animals maintains multiple nests for its exclusive use, occupying one nest at a time. Among serially monodomous ants, the availability of unoccupied nests reduces the probability and costs of army ant attacks. It has been proposed that nest odors mediate serial monodomy in the gypsy ant, Aphaenogaster araneoides Emery (Hymenoptera: Formicidae), and that colonies avoid returning to previously occupied nests that harbor colony odors. To evaluate this hypothesis, the odors inside the nests of A. araneoides colonies were experimentally reduced through ventilation; the nest movement behaviors of treatment and control colonies were compared. Odor reduction was found to have increased the frequency of movements into and out of the treated nest, without a change in the total occupation duration in the treated nest. Nests with a more open architecture that permitted natural flow of air were reoccupied more quickly than nests with smaller nest entrances. In summary, the openness of the architecture of A. araneoides nests and the ventilation of air through nests alters the use of these nests. These findings further support the working hypothesis that nest-bound odors mediate the pattern of serial monodomy in A. araneoides. PMID:21268704

  12. MOEA/D-ACO: a multiobjective evolutionary algorithm using decomposition and AntColony.

    PubMed

    Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

    2013-12-01

    Combining ant colony optimization (ACO) and the multiobjective evolutionary algorithm (EA) based on decomposition (MOEA/D), this paper proposes a multiobjective EA, i.e., MOEA/D-ACO. Following other MOEA/D-like algorithms, MOEA/D-ACO decomposes a multiobjective optimization problem into a number of single-objective optimization problems. Each ant (i.e., agent) is responsible for solving one subproblem. All the ants are divided into a few groups, and each ant has several neighboring ants. An ant group maintains a pheromone matrix, and an individual ant has a heuristic information matrix. During the search, each ant also records the best solution found so far for its subproblem. To construct a new solution, an ant combines information from its group's pheromone matrix, its own heuristic information matrix, and its current solution. An ant checks the new solutions constructed by itself and its neighbors, and updates its current solution if it has found a better one in terms of its own objective. Extensive experiments have been conducted in this paper to study and compare MOEA/D-ACO with other algorithms on two sets of test problems. On the multiobjective 0-1 knapsack problem,MOEA/D-ACO outperforms the MOEA/D with conventional genetic operators and local search on all the nine test instances. We also demonstrate that the heuristic information matrices in MOEA/D-ACO are crucial to the good performance of MOEA/D-ACO for the knapsack problem. On the biobjective traveling salesman problem, MOEA/D-ACO performs much better than the BicriterionAnt on all the 12 test instances. We also evaluate the effects of grouping, neighborhood, and the location information of current solutions on the performance of MOEA/D-ACO. The work in this paper shows that reactive search optimization scheme, i.e., the "learning while optimizing" principle, is effective in improving multiobjective optimization algorithms. PMID:23757576

  13. Pupal cocoons affect sanitary brood care and limit fungal infections in ant colonies

    PubMed Central

    2013-01-01

    Background The brood of ants and other social insects is highly susceptible to pathogens, particularly those that penetrate the soft larval and pupal cuticle. We here test whether the presence of a pupal cocoon, which occurs in some ant species but not in others, affects the sanitary brood care and fungal infection patterns after exposure to the entomopathogenic fungus Metarhizium brunneum. We use a) a comparative approach analysing four species with either naked or cocooned pupae and b) a within-species analysis of a single ant species, in which both pupal types co-exist in the same colony. Results We found that the presence of a cocoon did not compromise fungal pathogen detection by the ants and that species with cocooned pupae increased brood grooming after pathogen exposure. All tested ant species further removed brood from their nests, which was predominantly expressed towards larvae and naked pupae treated with the live fungal pathogen. In contrast, cocooned pupae exposed to live fungus were not removed at higher rates than cocooned pupae exposed to dead fungus or a sham control. Consistent with this, exposure to the live fungus caused high numbers of infections and fungal outgrowth in larvae and naked pupae, but not in cocooned pupae. Moreover, the ants consistently removed the brood prior to fungal outgrowth, ensuring a clean brood chamber. Conclusion Our study suggests that the pupal cocoon has a protective effect against fungal infection, causing an adaptive change in sanitary behaviours by the ants. It further demonstrates that brood removal–originally described for honeybees as “hygienic behaviour”–is a widespread sanitary behaviour in ants, which likely has important implications on disease dynamics in social insect colonies. PMID:24125481

  14. 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. PMID:24718496

  15. 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. PMID:24783812

  16. [The effect of chlordecone (Kepone) on the laboratory colonies of the Pharaoh's ant Monomorium pharanois].

    PubMed

    Berndt, K P; Nitschmann, J

    1976-03-01

    The control of the Pharaoh's ant Monomorium pharaonis is very difficult because of the social way of life in this insect pest. In regard to the reported good suppressing results of Chlordecone we analyzed the mode of action in this compound at laboratory colonies of the pharaoh's ant. Commercial gel and granular formulations as well as selfmade baits have been tested. The best results showed the granular bait on the basis of ground nut butter, while the effects of all of the others was much weaker. The pure gel, developed for cockroach control, was like the application in drinking water without success. The treatment of the colonies after a starvation period of 60 hours improved all of the effects. Sterility (fertility, fecundity) in the surviving queens was not measurable. For practical control measures the often recommended prebaiting is not at all desirable. The action on the worker ants is good, but the special mode of action based on the selective mortality in the queens and its detailed effects are unknown. Through the early absence of queens in the colonies will be induced in many cases a production of new sexuals, which compensate the success of the poison and allow the colonies to recover. The treatment leads faster to an eradiction if the ET90 to workers mortality reached earlier than that in the queens. Successful control of pharaoh's ant will Chlordecone should be considered with reserve. Nethertheless Chlordecone is in the present situation of pharaoh's ant control one of the best so far known organic-synthetically insecticides. PMID:1267219

  17. 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

  18. The role of colony size on tunnel branching morphogenesis in ant nests.

    PubMed

    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

  19. 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

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

    PubMed

    Liu, Wei; Chen, Hanwu; Chen, Ling

    2013-08-01

    It is one of the most important tasks in bioinformatics to identify the regulatory elements in gene sequences. Most of the existing algorithms for identifying regulatory elements are inclined to converge into a local optimum, and have high time complexity. Ant Colony Optimization (ACO) is a meta-heuristic method based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of real ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper designs and implements an ACO based algorithm named ACRI (ant-colony-regulatory-identification) for identifying all possible binding sites of transcription factor from the upstream of co-expressed genes. To accelerate the ants' searching process, a strategy of local optimization is presented to adjust the ants' start positions on the searched sequences. By exploiting the powerful optimization ability of ACO, the algorithm ACRI can not only improve precision of the results, but also achieve a very high speed. Experimental results on real world datasets show that ACRI can outperform other traditional algorithms in the respects of speed and quality of solutions. PMID:23746735

  1. 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.

  2. 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.

  3. Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

    NASA Astrophysics Data System (ADS)

    Akhoondzadeh, M.

    2015-04-01

    This study attempts to acknowledge AOD (Aerosol Optical Depth) seismo-atmospheric anomalies around the time of the Chile earthquake of 27 February 2010. Since AOD precursor alone might not be useful as an accurate and stand alone criteria for the earthquake anomalies detection, therefore it would be more appropriate to use and integrate a variety of other precursors to reduce the uncertainty of potential detected seismic anomalies. To achieve this aim, eight other precursors including GPS-TEC (Total Electron Content), H+, He+, O+ densities (cm-3) and total ion density (cm-3) from IAP experiment, electron density (cm-3) and electron temperature (K) from ISL experiment and VLF electric field from ICE experiment have been surveyed to detect unusual variations around the time and location of the Chile earthquake. Moreover, three methods including Interquartile, ANN (Artificial Neural Network) and ACO (Ant Colony Optimization) have been implemented to observe the discord patterns in time series of the AOD precursor. All of the methods indicate a clear abnormal increase in time series of AOD data, 2 days prior to event. Also a striking anomaly is observed in time series of TEC data, 6 days preceding the earthquake. Using the analysis of ICE data, a prominent anomaly is detected in the VLF electric field measurement, 1 day before the earthquake. The time series of H+, He+, O+ densities (cm-3) and total ion density (cm-3) from IAP and also electron density (cm-3) and electron temperature (K) from ISL, illustrate the abnormal behaviors, 3 days before the event. It should be noted that the acknowledgment of the different lead times in outcomes of the implemented precursors strictly depend on the proper understanding of Lithosphere-Atmosphere-Ionosphere (LAI) coupling mechanism during seismic activities. It means that these different anomalies dates between LAI precursors can be a hint of truthfulness of multi-precursors analysis.

  4. 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

  5. A multistrategy optimization improved artificial bee colony algorithm.

    PubMed

    Liu, Wen

    2014-01-01

    Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster. PMID:24982924

  6. Artificial Bee Colony Algorithm Based on Information Learning.

    PubMed

    Gao, Wei-Feng; Huang, Ling-Ling; Liu, San-Yang; Dai, Cai

    2015-12-01

    Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of subpopulation is dynamically adjusted based on the last search experience, which results in a clear division of labor. Furthermore, the two search mechanisms are designed to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively, which acts as the cooperation. Finally, the comparison results on a number of benchmark functions demonstrate that the proposed method performs competitively and effectively when compared to the selected state-of-the-art algorithms. PMID:25594992

  7. Artificial Bee Colony Algorithm for Solving Optimal Power Flow Problem

    PubMed Central

    Le Dinh, Luong; Vo Ngoc, Dieu

    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. PMID:24470790

  8. 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. PMID:24470790

  9. Automatic image enhancement by artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Yimit, Adiljan; Hagihara, Yoshihiro; Miyoshi, Tasuku; Hagihara, Yukari

    2013-03-01

    With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods.

  10. 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

  11. Modified artificial bee colony algorithm for reactive power optimization

    NASA Astrophysics Data System (ADS)

    Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

    2015-05-01

    Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

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

    PubMed

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

    2014-01-01

    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

  13. 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.

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

    PubMed

    Valles, Steven M; Porter, Sanford D; Choi, Man-Yeon; Oi, David H

    2013-07-01

    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, cricket paste, and soybean oil adsorbed to defatted corn grit) effectively transmitted SINV-3 infections to S. invicta colonies. Correspondingly, viral infection was shown to be detrimental to colony health and productivity. By day 32, all ant colonies exposed to a single 24h pulse treatment of SINV-3 became infected with the virus regardless of the bait formulation. However, the SINV-3 sugar and cricket bait-treated colonies became infected more rapidly than the oil-treated colonies. Sugar and cricket-treated colonies exhibited significant declines in their brood ratings compared with the untreated control and oil bait-treated colonies. Measures of colony health and productivity evaluated at the end of the study (day 47) showed a number of differences among the bait treatments and the control group. Statistically significant and similar patterns were exhibited among treatments for the quantity of live workers (lower), live brood (lower), total colony weight (lower), worker mortality (higher), proportion larvae (lower), and queen weight (lower). Significant changes were also observed in the number of eggs laid by queens (lower) and the corresponding ovary rating in SINV-3-treated colonies. The study provides the first successful demonstration of SINV-3 as a potential biopesticide against fire ants. PMID:23602901

  15. ABCluster: the artificial bee colony algorithm for cluster global optimization.

    PubMed

    Zhang, Jun; Dolg, Michael

    2015-10-01

    Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters. PMID:26327507

  16. A Graph-Based Ant Colony Optimization Approach for Process Planning

    PubMed Central

    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. PMID:24995355

  17. 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. PMID:19130503

  18. Structural link prediction based on ant colony approach in social networks

    NASA Astrophysics Data System (ADS)

    Sherkat, Ehsan; Rahgozar, Maseud; Asadpour, Masoud

    2015-02-01

    As the size and number of online social networks are increasing day by day, social network analysis has become a popular issue in many branches of science. The link prediction is one of the key rolling issues in the analysis of social network's evolution. As the size of social networks is increasing, the necessity for scalable link prediction algorithms is being felt more. The aim of this paper is to introduce a new unsupervised structural link prediction algorithm based on the ant colony approach. Recently, ant colony approach has been used for solving some graph problems. Different kinds of networks are used for testing the proposed approach. In some networks, the proposed scalable algorithm has the best result in comparison to other structural unsupervised link prediction algorithms. In order to evaluate the algorithm results, methods like the top- n precision, area under the Receiver Operating Characteristic (ROC) and Precision-Recall curves are carried out on real-world networks.

  19. 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. PMID:24995355

  20. 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. PMID:22399947

  1. Ant colony optimization for biomarker identification from MALDI-TOF mass spectra.

    PubMed

    Ressom, Habtom W; Varghese, Rency S; Orvisky, Eduard; Drake, Steven K; Hortin, Glen L; Abdel-Hamid, Mohamed; Loffredo, Christopher A; Goldman, Radoslav

    2006-01-01

    We present a novel method that combines ant colony optimization with support vector machines (ACO-SVM) to select candidate biomarkers from MALDI-TOF serum profiles of hepatocellular carcinoma (HCC) patients and matched controls. The method identified relevant mass points that achieve high sensitivity and specificity in distinguishing HCC patients from healthy individuals. The results indicate that the MALDI-TOF technology could provide the means to discover novel biomarkers for HCC. PMID:17946638

  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. Training spiking neural models using artificial bee colony.

    PubMed

    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

  4. 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.

  5. 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

  6. 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. PMID:26394148

  7. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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,...

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  11. 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. PMID:25395324

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

    PubMed

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

    2012-08-01

    The efficacy of toxic baits should be judged by their ability to kill entire ant colonies, including the colony queen or queens. We studied the efficacy of four toxic baits to the Argentine ant, Linepithema humile (Mayr) (Hymenoptera: Formicidae). These baits were Xstinguish that has the toxicant fipronil, Exterm-an-Ant that contains both boric acid and sodium borate, and Advion ant gel and Advion ant bait arena that both have indoxacarb. Experimental nests contained 300 workers and 10 queen ants that were starved for either 24 or 48 h before toxic bait exposure. The efficacy of the toxic baits was strongly influenced by starvation. In no treatment with 24-h starvation did we observe 100% worker death. After 24-h starvation three of the baits did not result in any queen deaths, with only Exterm-an-Ant producing an average of 25% mortality. In contrast, 100% queen and worker mortality was observed in colonies starved for 48 h and given Xstinguish or Exterm-an-Ant. The baits Advion ant gel and Advion ant bait arena were not effective against Argentine ants in these trials, resulting in <60% mortality in all treatments. Because of the strong influence of starvation on bait uptake, control efficacy may be maximized by applying bait when ants are likely to be starved. Our results suggest queen mortality must be assessed in tests for toxic bait efficacy. Our data indicate that of these four baits, Xstinguish and Exterm-an-Ant are the best options for control of Argentine ants in New Zealand. PMID:22928290

  13. 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. PMID:20492083

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  15. 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

  16. 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

  17. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

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

    NASA Astrophysics Data System (ADS)

    Abd-El-Barr, Mostafa

    2010-12-01

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

  1. 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. PMID:24592200

  2. 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).

  3. 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.

  4. 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

  5. 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

  6. 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

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

    PubMed

    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

  8. 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. PMID:24883356

  9. To b or not to b: a pheromone-binding protein regulates colony social organization in fire ants.

    PubMed

    Krieger, Michael J B

    2005-01-01

    A major distinction in the social organization of ant societies is the number of reproductive queens that reside in a single colony. The fire ant Solenopsis invicta exists in two distinct social forms, one with colonies headed by a single reproductive queen and the other containing several to hundreds of egg-laying queens. This variation in social organization has been shown to be associated with genotypes at the gene Gp-9. Specifically, single-queen colonies have only the B allelic variant of this gene, whereas multiple-queen colonies always have the b variant as well. Subsequent studies revealed that Gp-9 shares the highest sequence similarity with genes encoding pheromone-binding proteins (PBPs). In other insects, PBPs serve as central molecular components in the process of chemical recognition of conspecifics. Fire ant workers regulate the number of egg-laying queens in a colony by accepting queens that produce appropriate chemical signals and destroying those that do not. The likely role of GP-9 in chemoreception suggests that the essential distinction in colony queen number between the single and multiple-queen form originates from differences in workers' abilities to recognize queens. Other, closely related fire ant species seem to regulate colony social organization in a similar fashion. PMID:15612031

  10. Private information alone can trigger trapping of ant colonies in local feeding optima.

    PubMed

    Czaczkes, Tomer J; Salmane, Anete K; Klampfleuthner, Felicia A M; Heinze, Jürgen

    2016-03-01

    Ant colonies are famous for using trail pheromones to make collective decisions. Trail pheromone systems are characterised by positive feedback, which results in rapid collective decision making. However, in an iconic experiment, ants were shown to become 'trapped' in exploiting a poor food source, if it was discovered earlier. This has conventionally been explained by the established pheromone trail becoming too strong for new trails to compete. However, many social insects have a well-developed memory, and private information often overrules conflicting social information. Thus, route memory could also explain this collective 'trapping' effect. Here, we disentangled the effects of social and private information in two 'trapping' experiments: one in which ants were presented with a good and a poor food source, and one in which ants were presented with a long and a short path to the same food source. We found that private information is sufficient to trigger trapping in selecting the poorer of two food sources, and may be sufficient to cause it altogether. Memories did not trigger trapping in the shortest path experiment, probably because sufficiently detailed memories did not form. The fact that collective decisions can be triggered by private information alone may require other collective patterns previously attributed solely to social information use to be reconsidered. PMID:26747911

  11. SamACO: variable sampling ant colony optimization algorithm for continuous optimization.

    PubMed

    Hu, Xiao-Min; Zhang, Jun; Chung, Henry Shu-Hung; Li, Yun; Liu, Ou

    2010-12-01

    An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants' solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising. PMID:20371409

  12. 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. PMID:8537545

  13. Mobility Robustness Optimization in Femtocell Networks Based on Ant Colony Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Haijun; Liu, Hui; Ma, Wenmin; Zheng, Wei; Wen, Xiangming; Jiang, Chunxiao

    Mobility Robustness Optimization (MRO) is one of the most important goals in LTE-Advanced Self-Organizing Networks (SON). Seamless handover in femtocell network is urgent and challenging, which has not been paid enough attention. Handover decision parameters, such as Time-To-Trigger (TTT), Hysteresis, Cell Individual Offset (CIO), have great effect on mobility performance, which may lead to Radio Link Failures (RLFs) and Unnecessary Handover. This letter proposes a handover parameters optimization approach based on Ant Colony Algorithm in the femtocell networks. The simulation result shows that the proposed scheme has a better performance than the fixed parameters method.

  14. 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.

  15. Ant colony optimization image registration algorithm based on wavelet transform and mutual information

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Sun, Yanfeng; Zhai, Bing; Wang, Yiding

    2013-07-01

    This paper studies on the image registration of the medical images. Wavelet transform is adopted to decompose the medical images because the resolution of the medical image is high and the computational amount of the registration is large. Firstly, the low frequency sub-images are matched. Then source images are matched. The image registration was fulfilled by the ant colony optimization algorithm to search the extremum of the mutual information. The experiment result demonstrates the proposed approach can not only reduce calculation amount, but also skip from the local extremum during optimization process, and search the optimization value.

  16. An Energy Aware Ant Colony Algorithm for the Routing of Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Cheng, Deqiang; Xun, Yangyang; Zhou, Ting; Li, Wenjie

    Based on the characteristics of routing protocol for wireless sensor networks, an energy aware ant colony algorithm (EAACA) for the routing of wireless sensor networks is proposed in this paper. When EAACA routing protocol chooses the next neighbor node, not only the distance of sink node, but also the residual energy of the next node and the path of the average energy are taken into account. Theoretical analysis and simulation results show that compared with the traditional ACA algorithm for the routing of wireless sensor network, EAACA routing protocol balances the energy consumption of nodes in the network and extends the network lifetime.

  17. Integration of GPS and DinSAR for Deformation Monitoring Based on Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Shi, Guoqiang; He, Xiufeng; Xiao, Ruya

    2014-11-01

    To acquire three-dimensional earth surface deformation, a measurement method based on ant colony optimization (ACO) is proposed. It highly integrates high-accuracy GPS observations from sparse ground points with InSAR line-of-sight (LOS) direction information. Two constraints, GPS and DInSAR observations, are employed in constructing the energy function whose minimum value will be searched by the ACO operated in continuous space. Compared with conventional interpolation algorithms, the proposed method increases the three-dimensional deformation observation accuracy, especially showing the improvement in the up direction.

  18. Essential and alternative prey in a ponerine ant: variations according to the colony life cycle.

    PubMed

    Suzzoni, J P; Schatz, B; Dejean, A

    2000-11-01

    We studied the prey specialization of Plectroctena minor, a ponerine ant known to capture mostly millipedes. We compared the prey spectrum of the hunting workers from large colonies with that of the founding queens. The hunting workers captured all kinds of tested prey, but hunted mostly millipedes. Founding queens, which avoided relatively large prey, including the millipedes tested, captured mostly isopods under experimental conditions. We also verified that the presence of millipedes in the diet of the larvae of large colonies was necessary for the production of winged females and strongly enhanced the production of workers, permitting us to assert that P. minor is a predatory species specialized in the capture of millipedes. In contrast, the presence of millipedes had no impact on the production of males. We thus assert that millipedes constitute the 'essential prey' of P. minor, while other arthropod taxa are therefore 'alternative prey'. PMID:11144023

  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. PMID:12146794

  20. Role of relative humidity in colony founding and queen survivorship in two carpenter ant species.

    PubMed

    Mankowski, Mark E; Morrell, J J

    2011-06-01

    Conditions necessary for optimal colony foundation in two carpenter ant species, Camponotus modoc Wheeler and Camponotus vicinus Mayr, were studied. Camponotus modoc and C. vicinus queens were placed in Douglas-fir, Pseudotsuga menziesii (Mirb. Franco) and Styrofoam blocks conditioned in sealed chambers at 70, 80, or 100% RH. Nanitic workers produced after 12 wk were used to assess the effects of substrate and moisture content on colony initiation. Queens of C. vicinus in Douglas-fir and Styrofoam produced worker numbers that did not differ significantly with moisture content; however, the number of colonies initiated by C. modoc differed significantly with moisture content. The results indicate that colony founding in C. vicinus is less sensitive to moisture content than C. modoc for Douglas-fir and Styrofoam. In another test, groups of queens of each species were exposed to 20, 50, 70, and 100% RH and the time until 50% mortality occurred was recorded for each species. C. vicinus lived significantly longer at each of the test humidities than C. modoc, suggesting that the former species is adapted to better survive under xeric conditions. PMID:21735888

  1. 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.

  2. Ant pupae employ acoustics to communicate social status in their colony's hierarchy.

    PubMed

    Casacci, Luca P; Thomas, Jeremy A; Sala, Marco; Treanor, David; Bonelli, Simona; Balletto, Emilio; Schönrogge, Karsten

    2013-02-18

    The possession of an efficient communication system and an ability to distinguish between young stages are essential attributes that enable eusocial insects to live in complex integrated societies. Although ants communicate primarily via chemicals, it is increasingly clear that acoustical signals also convey important information, including status, between adults in many species. However, all immature stages were believed to be mute. We confirm that larvae and recently formed pupae of Myrmica ants are mute, yet once they are sclerotized, the pupae possess a fully functioning stridulatory organ. The sounds generated by worker pupae were similar to those of workers but were emitted as single pulses rather than in the long sequences characteristic of adults; both induced the same range and intensity of benevolent behaviors when played back to unstressed workers. Both white and sclerotized pupae have a higher social status than larvae within Myrmica colonies, but the latter's status fell significantly after they were made mute. Our results suggest that acoustical signals supplant semiochemicals as a means of identification in sclerotized pupae, perhaps because their hardened integuments block the secretion of brood pheromones or because their developing adult secretions initially differ from overall colony odors. PMID:23394832

  3. 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. PMID:22666056

  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. PMID:25097874

  5. 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

  6. An Improved Ant Colony Optimization Approach for Optimization of Process Planning

    PubMed Central

    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. PMID:25097874

  7. 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. PMID:26695205

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Hybrid real-code ant colony optimisation for constrained mechanical design

    NASA Astrophysics Data System (ADS)

    Pholdee, Nantiwat; Bureerat, Sujin

    2016-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Optic disc detection in color fundus images using ant colony optimization.

    PubMed

    Pereira, Carla; Gonçalves, Luís; Ferreira, Manuel

    2013-03-01

    Diabetic retinopathy has been revealed as the most common cause of blindness among people of working age in developed countries. However, loss of vision could be prevented by an early detection of the disease and, therefore, by a regular screening program to detect retinopathy. Due to its characteristics, the digital color fundus photographs have been the easiest way to analyze the eye fundus. An important prerequisite for automation is the segmentation of the main anatomical features in the image, particularly the optic disc. Currently, there are many works reported in the literature with the purpose of detecting and segmenting this anatomical structure. Though, none of them performs as needed, especially when dealing with images presenting pathologies and a great variability. Ant colony optimization (ACO) is an optimization algorithm inspired by the foraging behavior of some ant species that has been applied in image processing with different purposes. In this paper, this algorithm preceded by anisotropic diffusion is used for optic disc detection in color fundus images. Experimental results demonstrate the good performance of the proposed approach as the optic disc was detected in most of all the images used, even in the images with great variability. PMID:23160896

  18. Optimal Selection of Parameters for Nonuniform Embedding of Chaotic Time Series Using Ant Colony Optimization.

    PubMed

    Shen, Meie; Chen, Wei-Neng; Zhang, Jun; Chung, Henry Shu-Hung; Kaynak, Okyay

    2013-04-01

    The optimal selection of parameters for time-delay embedding is crucial to the analysis and the forecasting of chaotic time series. Although various parameter selection techniques have been developed for conventional uniform embedding methods, the study of parameter selection for nonuniform embedding is progressed at a slow pace. In nonuniform embedding, which enables different dimensions to have different time delays, the selection of time delays for different dimensions presents a difficult optimization problem with combinatorial explosion. To solve this problem efficiently, this paper proposes an ant colony optimization (ACO) approach. Taking advantage of the characteristic of incremental solution construction of the ACO, the proposed ACO for nonuniform embedding (ACO-NE) divides the solution construction procedure into two phases, i.e., selection of embedding dimension and selection of time delays. In this way, both the embedding dimension and the time delays can be optimized, along with the search process of the algorithm. To accelerate search speed, we extract useful information from the original time series to define heuristics to guide the search direction of ants. Three geometry- or model-based criteria are used to test the performance of the algorithm. The optimal embeddings found by the algorithm are also applied in time-series forecasting. Experimental results show that the ACO-NE is able to yield good embedding solutions from both the viewpoints of optimization performance and prediction accuracy. PMID:23144038

  19. 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

  20. A novel artificial bee colony based clustering algorithm for categorical data.

    PubMed

    Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

    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

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

    PubMed

    Chen, Tinggui; Xiao, Renbin

    2014-01-01

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

  2. 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

  3. Fracture enhancement based on artificial ants and fuzzy c-means clustering (FCMC) in Dezful Embayment of Iran

    NASA Astrophysics Data System (ADS)

    Nasseri, Aynur; Jafar Mohammadzadeh, Mohammad; Hashem Tabatabaei Raeisi, S.

    2015-04-01

    This paper deals with the application of the ant colony algorithm (AC) to a seismic dataset from Dezful Embayment in the southwest region of Iran. The objective of the approach is to generate an accurate representation of faults and discontinuities to assist in pertinent matters such as well planning and field optimization. The AC analyzed all spatial discontinuities in the seismic attributes from which features were extracted. True fault information from the attributes was detected by many artificial ants, whereas noise and the remains of the reflectors were eliminated. Furthermore, the fracture enhancement procedure was conducted by three steps on seismic data of the area. In the first step several attributes such as chaos, variance/coherence and dip deviation were taken into account; the resulting maps indicate high-resolution contrast for the variance attribute. Subsequently, the enhancement of spatial discontinuities was performed and finally elimination of the noise and remains of non-faulting events was carried out by simulating the behavior of ant colonies. After considering stepwise attribute optimization, focusing on chaos and variance in particular, an attribute fusion was generated and used in the ant colony algorithm. The resulting map displayed the highest performance in feature detection along the main structural feature trend, confined to a NW-SE direction. Thus, the optimized attribute fusion might be used with greater confidence to map the structural feature network with more accuracy and resolution. In order to assess the performance of the AC in feature detection, and cross validate the reliability of the method used, fuzzy c-means clustering (FCMC) was employed for the same dataset. Comparing the maps illustrates the effectiveness and preference of the AC approach due to its high resolution contrast for structural feature detection compared to the FCMC method. Accordingly, 3D planes of discontinuity determined spatial distribution of fractures

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

    PubMed

    Klobuchar, Emily A; Deslippe, Richard J

    2002-07-01

    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. PMID:12216859

  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. STUDIES ON ATTRACTIVENESS AND EFFECTIVENESS OF AN ARTIFICIAL ENTOMOPHAGE DIET FED TO HYBRID IMPORTED FIRE ANTS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An artificial entomophage diet (Cohen, U. S. Patent # 5,834,177. November 10, 1998) was offered to Solenopsis invicta Buren x Solenopsis richteri Forel (hybrid imported fire ant) in a series of choice tests. Foraging workers collected approx. 27 times more reconstituted diet than freeze-dried diet...

  7. 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.

  8. 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. PMID:23983638

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

    Wang, Hong-Jian; Xiong, Wei

    2009-03-01

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

  12. 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

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

    PubMed

    Li, Ke; Chen, Peng

    2011-01-01

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

  14. 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.

  15. 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. PMID:22294908

  16. 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

  17. 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.

  18. 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. PMID:24065871

  19. 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. PMID:26504895

  20. 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. PMID:25136678

  1. 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

  2. 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.

  3. 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

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

    PubMed

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

    2010-01-01

    For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively. PMID:22399890

  5. 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.

  6. Monte Carlo simulation using the PENELOPE code with an ant colony algorithm to study MOSFET detectors.

    PubMed

    Carvajal, M A; García-Pareja, S; Guirado, D; Vilches, M; Anguiano, M; Palma, A J; Lallena, A M

    2009-10-21

    In this work we have developed a simulation tool, based on the PENELOPE code, to study the response of MOSFET devices to irradiation with high-energy photons. The energy deposited in the extremely thin silicon dioxide layer has been calculated. To reduce the statistical uncertainties, an ant colony algorithm has been implemented to drive the application of splitting and Russian roulette as variance reduction techniques. In this way, the uncertainty has been reduced by a factor of approximately 5, while the efficiency is increased by a factor of above 20. As an application, we have studied the dependence of the response of the pMOS transistor 3N163, used as a dosimeter, with the incidence angle of the radiation for three common photons sources used in radiotherapy: a (60)Co Theratron-780 and the 6 and 18 MV beams produced by a Mevatron KDS LINAC. Experimental and simulated results have been obtained for gantry angles of 0 degrees, 15 degrees, 30 degrees, 45 degrees, 60 degrees and 75 degrees. The agreement obtained has permitted validation of the simulation tool. We have studied how to reduce the angular dependence of the MOSFET response by using an additional encapsulation made of brass in the case of the two LINAC qualities considered. PMID:19794247

  7. 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. PMID:26868846

  8. 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.

  9. 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

  10. 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