A Deterministic Metaheuristic Approach using "Logistic Ants" for Combinatorial Optimization.

Rodolphe Charrier 1 Christine Bourjot 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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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Dorigo, M. Ants 2010 Seventh International Conference on Swarm Intelligence, Sep 2010, Brussels, Belgium. Springer, 6234, pp.344-351, 2010, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/476620098120k852/fulltext.pdf〉. 〈10.1007/978-3-642-15461-4_30〉
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Rodolphe Charrier, Christine Bourjot, François Charpillet. A Deterministic Metaheuristic Approach using "Logistic Ants" for Combinatorial Optimization.. Dorigo, M. Ants 2010 Seventh International Conference on Swarm Intelligence, Sep 2010, Brussels, Belgium. Springer, 6234, pp.344-351, 2010, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/476620098120k852/fulltext.pdf〉. 〈10.1007/978-3-642-15461-4_30〉. 〈inria-00549250〉

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