Abstract
Recently, a number of parallelized optimization algorithms have been proposed. We have proposed a co-evolutionary immune algorithm (IA) to solve the division-of-labor problems, in particular the n-th agent’s travelling salesman problem (n-TSP). In this article, we extend the co-evolutionary IA for a large-scale n-TSP with (1) an improvement for the search speed through parallelized search on the PC-cluster, and (2) the introduction of a new division-processing “pre-estimated division processing” to improve the search ability. Some computational experiments show the proposed method can obtain better quality solutions for division-of-labor problems, and present an applicable parameter cofinguration.
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