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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Parallel Ant Colony Optimizer Based on Adaptive Resonance Theory Maps
verfasst von : Hiroshi Koshimizu, Toshimichi Saito
Erschienen in: Advances in Neuro-Information Processing
Verlag: Springer Berlin Heidelberg
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This paper studies a parallel ant colony optimizer and its application to the traveling sales person problems. The parallel processing is based on the adaptive resonance theory map that divide the input space into subspaces. The ants are classified into two types: local ant for local search within either subspace and global ant for search of whole input space. Communication between local and global ants is a key for effective parallel processing. Applying the algorithm to basic bench marks, we can suggest that our algorithm realize fast and reasonable search.