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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Swarm Intelligence / Adaptive Resonance Theory / Ant Colony Optimization / Traveling Sales-person Problem |
Paper # | NLP2009-149 |
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Committee | NLP |
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Conference Date | 2010/1/14(1days) |
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Registration To | Nonlinear Problems (NLP) |
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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 |
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