A Deterministic Metaheuristic Approach Using “Logistic Ants” for Combinatorial Optimization
Identifieur interne : 003141 ( Main/Exploration ); précédent : 003140; suivant : 003142A Deterministic Metaheuristic Approach Using “Logistic Ants” for Combinatorial Optimization
Auteurs : Rodolphe Charrier [France] ; Christine Bourjot [France] ; François Charpillet [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
English descriptors
Abstract
Abstract: Ant algorithms are usually derived from a stochastic modeling based on some specific probability laws. We consider in this paper a full deterministic model of “logistic ants” which uses chaotic maps to govern the behavior of the artificial ants. We illustrate and test this approach on a TSP instance, and compare the results with the original Ant System algorithm. This change of paradigm —deterministic versus stochastic— implies a novel view of the internal mechanisms involved during the searching and optimizing process of ants.
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DOI: 10.1007/978-3-642-15461-4_30
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We consider in this paper a full deterministic model of “logistic ants” which uses chaotic maps to govern the behavior of the artificial ants. We illustrate and test this approach on a TSP instance, and compare the results with the original Ant System algorithm. 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