Presentation 2009-07-14
ART-based Parallel Ant Colony Optimizer : An application to TSP
Hiroshi KOSHIMIZU, Toshimichi SAITO,
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Abstract(in English) We consider a optimization algorithm of ART-based paralleled Ant Colony Optimization (ACO) and its application to Traveling Sales-person Problem (TSP). The ACO is an evolutional optimization algorithm inspired by pheromone effect of ants. The ACO can be extended by Adaptive Resonance Theory maps (ART). In proposed ACO, the feature space is divided into subspaces by ART as basic to parallel processing at first. Next, We search for (semi-) optimal solution of each space appling to ACO. Proposed ACO has two kind of ants: local ants that is assigned to search in a subspace and global ants for global search. In order to confirm the performance of our proposed ACO, The algorithm apply to TSP. We consider about relation between the results and parameter setting of proposed ACO.
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Keyword(in English) Ant Colony Optimization / Adaptive Resonance Theory / Traveling Sales-person Problem / Optimization Problem
Paper # NLP2009-28,NC2009-21
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Committee NLP
Conference Date 2009/7/6(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) ART-based Parallel Ant Colony Optimizer : An application to TSP
Sub Title (in English)
Keyword(1) Ant Colony Optimization
Keyword(2) Adaptive Resonance Theory
Keyword(3) Traveling Sales-person Problem
Keyword(4) Optimization Problem
1st Author's Name Hiroshi KOSHIMIZU
1st Author's Affiliation EE Dept, Hosei University()
2nd Author's Name Toshimichi SAITO
2nd Author's Affiliation EE Dept, Hosei University
Date 2009-07-14
Paper # NLP2009-28,NC2009-21
Volume (vol) vol.109
Number (no) 124
Page pp.pp.-
#Pages 5
Date of Issue