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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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Submitted on : Tuesday, March 8, 2011 - 3:26:33 PM
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Long-term archiving on: : Tuesday, November 6, 2012 - 3:41:18 PM

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Rodolphe Charrier, Christine Bourjot, François Charpillet. A Deterministic Metaheuristic Approach using "Logistic Ants" for Combinatorial Optimization.. Ants 2010 Seventh International Conference on Swarm Intelligence, Sep 2010, Brussels, Belgium. pp.344-351, ⟨10.1007/978-3-642-15461-4_30⟩. ⟨inria-00549250⟩

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