Parallel ant colony optimizers with local and global ants

Authors:
Hiroshi Koshimizu;Toshimichi Saito
Affiliations:
Department of Electrical and Electronics Engineering, Hosei University, Tokyo, Japan;Department of Electrical and Electronics Engineering, Hosei University, Tokyo, Japan
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

This paper studies the ant colony optimizer with parallel processing function based on adaptive resonance theory map. The optimizer has two groups of ants: local ants that is assigned to search in a subspace and global ants for global search. Effective communication between local and global ants is key to realize desired optimization. Applying the algorithm to typical bench marks, we can suggest that the optimizer can realize adaptive and fast search of solutions.