Multi-objective Co-operative Co-evolutionary Genetic Algorithm
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Parallel neighbourhood search on many-core platforms
International Journal of Computational Science and Engineering
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In this paper we propose a parallel and distributed genetic algorithms (PDGA) on fixed network topology multiprocessor systems in which each processor element carries out genetic operations on its own chromosome set and communicates with only the neighbors (we say chromosome migration). We execute the proposed method to investigate effects of chromosome migration on the multiprocessor systems with ring, torus, and hypercube topology for benchmark problem instances. From the results, we find that the ring topology is more suitable for our proposed parallel and distributed execution since it avoids immature convergence for its topological feature. We show its effectiveness by experimental evaluation.