Search results for "Ant Colony"

showing 10 items of 62 documents

An environment based approach for the ant colony convergence

2020

Abstract Ant colony optimization (ACO) algorithms are a bio inspired solutions which have been very successful in combinatorial problem solving, also known as NP-hard problems, including transportation system optimization. As opposed to exact methods, which could give the best results of a tested problem, this meta-heuristics is based on the stochastic logic but not on theoretical mathematics demonstration (or only on certain well defined applications). According to this, the weak point of this meta-heuristics is his convergence, its termination condition. We can finds many different termination criteria in the scientific literature, yet most of them are costly in resources and unsuitable f…

Ant ColonyEnvironment approachMathematical optimization021103 operations researchComputer science[SPI] Engineering Sciences [physics]Ant colony optimization algorithms0211 other engineering and technologiesSystem optimization02 engineering and technologyAnt colonyStochastic logic[SPI]Engineering Sciences [physics]Order (exchange)Convergence (routing)0202 electrical engineering electronic engineering information engineeringDynamic convergenceGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingPoint (geometry)ComputingMilieux_MISCELLANEOUSGeneral Environmental Science
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Towards a multilevel ant colony optimization

2014

Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 Ant colony optimization is a metaheuristic approach for solving combinatorial optimization problems which belongs to swarm intelligence techniques. Ant colony optimization algorithms are one of the most successful strands of swarm intelligence which has already shown very good performance in many combinatorial problems and for some real applications. This thesis introduces a new multilevel approach for ant colony optimization to solve the NP-hard problems shortest path and traveling salesman. We have reviewed different elements of multilevel algorithm which helped us in construction of our proposed mu…

Ant colony optimizationIKT590MathematicsofComputing_NUMERICALANALYSISVDP::Technology: 500::Information and communication technology: 550ComputingMethodologies_ARTIFICIALINTELLIGENCE
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Characterizing the collective personality of ant societies: aggressive colonies do not abandon their home.

2011

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…

Collective behaviorTemnothorax nylanderimedia_common.quotation_subjectved/biology.organism_classification_rank.speciesImmunologyZoologylcsh:MedicineBiologyNestBehavioral ecologymedicinePersonalityAnimalslcsh:ScienceBiologymedia_commonLikelihood FunctionsMultidisciplinaryBehavior AnimalEcologyved/biologyEcologyAggressionAntslcsh:RAnt colonyAggressionCommunity Ecologylcsh:QCollective animal behaviormedicine.symptomZoologyResearch ArticlePloS one
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No effect of lack of wood for acorn ant colonies development

2021

Acorn ants mostly inhabit cavities in fallen twigs and hollow acorns. Such places, e.g., dead wood, provide an attractive living resource for many groups of microorganisms, like fungi and bacteria, which can be important for ants. However, during experiments in laboratories, acorn ant colonies are typically kept without dead wood. During laboratory experi-ments, the preferences of the ant Temnothorax crassispinus for nest sites with pieces of dead wood were checked, and whether the presence of such wood influenced productivity. In binary choice tests, colonies had to choose a nest site when presented with two potential nest sites, one empty, or two cavities with different contents. The ant …

Collective decisionResource (biology)EcologyTemnothorax crassispinusDead woodAnt colonyBiologyAcornbehaviourTemnothorax crassispinusQL1-991collective decisionAnimal Science and ZoologyZoologynest choiceEuropean Zoological Journal
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Synthetic Genes for artificial ants. Diversity in ant colony optimization algorithms

2010

Inspired from the fact that the real world ants from within a colony are not clones (although they may look alike, they are different from one another), in this paper, the authors are presenting an adapted ant colony optimisation (ACO) algorithm that incorporates methods and ideas from genetic algorithms (GA). Following the first (introductory) section of the paper is presented the history and the state of the art, beginning with the stigmergy and genetic concepts and ending with the latest ACO algorithm variants as multiagent systems (MAS). The rationale and the approach sections are aiming at presenting the problems with current stigmergy-based algorithms and at proposing a (possible - ye…

Computer Networks and CommunicationsComputer sciencebusiness.industryMulti-agent systemAnt colony optimization algorithmsLocal variableAnt colonyStigmergyComputer Science ApplicationsComputational Theory and MathematicsConvergence (routing)Artificial intelligenceState (computer science)businessClosing (morphology)
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Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization

2018

Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.

Computer scienceAnt colony optimization algorithmsMathematicsofComputing_NUMERICALANALYSISMerkle–Hellman knapsack cryptosystemPlaintextData_CODINGANDINFORMATIONTHEORYAnt colonyComputingMethodologies_ARTIFICIALINTELLIGENCElaw.inventionKnapsack problemlawTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYCryptosystemCryptanalysisAlgorithmMetaheuristicSSRN Electronic Journal
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Optimizing PolyACO Training with GPU-Based Parallelization

2016

A central part of Ant Colony Optimisation (ACO) is the function calculating the quality and cost of solutions, such as the distance of a potential ant route. This cost function is used to deposit an opportune amount of pheromones to achieve an apt convergence, and in an active ACO implementation a significant part of the runtime is spent in this part of the code. In some cases, the cost function accumulates up towards 94 % in its run time making it a performance bottle neck.

Computer scienceMathematicsofComputing_NUMERICALANALYSISSignificant part02 engineering and technologyParallel computingFunction (mathematics)Ant colonyComputingMethodologies_ARTIFICIALINTELLIGENCEBottle neck030218 nuclear medicine & medical imaging03 medical and health sciencesAutomatic parallelization0302 clinical medicineConvergence (routing)0202 electrical engineering electronic engineering information engineeringCode (cryptography)020201 artificial intelligence & image processing
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Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery

2016

This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…

Computer sciencebusiness.industryAnt colony optimization algorithmsMultispectral imageFeature selectionPattern recognition02 engineering and technologyStatistical classification020204 information systemsPrincipal component analysisShortest path problem0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)Curse of dimensionality2016 International Conference on Communications (COMM)
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Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization

2008

The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…

Continuous optimizationMathematical optimizationEstimation theoryComputer scienceCumulative distribution functionAnt colony optimization algorithmsAnt colonyAlgorithmSearch treeEvolutionary computationWeibull distribution2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)
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Damage identification by a modified Ant Colony Optimization for not well spaced frequency systems

2011

Recently, it has been shown , that a damage detection strategy based on a proper functional calculated on the analytical signal of the structural dynamical response, consents to identify very low damage level. In this regard, they stressed the efficiency of Hilbert Transform to obtain the analytical response representation that shows more sensitivity for predicting damage with respect to the simple signal response. Then, a damage identification procedure based on the minimization of the difference between theoretical and measured data was proposed with satisfactory results. Unfortunately, this procedure, since the need of use of band pass filter around the natural frequency of the system, f…

Damage Identification; Hilbert Transform; Ant colony optimization.Ant colony optimization.Damage IdentificationSettore ICAR/08 - Scienza Delle CostruzioniHilbert Transform
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