Presentation 2010-01-22
On search characteristics of an ant colony optimizer-paralleled by an improved adaptive resonance theory
Hiroshi KOSHIMIZU, Toshimichi SAITO,
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Abstract(in English) We consider basic characteristics of a novel parallel ant colony optimizer (ACO) in application to the traveling salesperson problems. The ACO is an evolutional optimization algorithm inspired by pheromone effect of ants. The improved adaptive resonance theory map (IART) is used to divide the feature space into some subspaces for the parallel processing. The Proposed ACO has two kind of ants: local ants that is assigned to search in a subspace and global ants for global search. They can communicate to each other through common pheromone information. In several benchmarks, we have investigated effects of some key parameters on the algorithm efficiency.
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Keyword(in English) Swarm Intelligence / Adaptive Resonance Theory / Ant Colony Optimization / Traveling Sales-person Problem
Paper # NLP2009-149
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Committee NLP
Conference Date 2010/1/14(1days)
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Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) On search characteristics of an ant colony optimizer-paralleled by an improved adaptive resonance theory
Sub Title (in English)
Keyword(1) Swarm Intelligence
Keyword(2) Adaptive Resonance Theory
Keyword(3) Ant Colony Optimization
Keyword(4) Traveling Sales-person Problem
1st Author's Name Hiroshi KOSHIMIZU
1st Author's Affiliation Major in Electrical Engineering, Hosei Univ.()
2nd Author's Name Toshimichi SAITO
2nd Author's Affiliation Faculty of Science and Engineering., Hosei Univ.
Date 2010-01-22
Paper # NLP2009-149
Volume (vol) vol.109
Number (no) 366
Page pp.pp.-
#Pages 5
Date of Issue