Article

A deterministic metaheuristic approach using "logistic ants" for combinatorial optimization

Authors:

Rodolphe Charrier,

Christine Bourjot,

François CharpilletAuthors Info & Claims

ANTS'10: Proceedings of the 7th international conference on Swarm intelligence

Pages 344 - 351

Published: 08 September 2010 Publication History

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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https://dl.acm.org/doi/10.1016/j.engappai.2017.09.012
Jaddi NAbdullah SHamdan A(2015)Optimization of neural network model using modified bat-inspired algorithmApplied Soft Computing10.1016/j.asoc.2015.08.00237:C(71-86)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.asoc.2015.08.002

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Published In

ANTS'10: Proceedings of the 7th international conference on Swarm intelligence

September 2010

582 pages

ISBN:3642154603

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 08 September 2010

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Jaddi NAbdullah S(2018)Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecastingEngineering Applications of Artificial Intelligence10.1016/j.engappai.2017.09.01267:C(246-259)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1016/j.engappai.2017.09.012
Jaddi NAbdullah SHamdan A(2015)Optimization of neural network model using modified bat-inspired algorithmApplied Soft Computing10.1016/j.asoc.2015.08.00237:C(71-86)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.asoc.2015.08.002

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