Abstract
MOEA/D is a multi-objective metaheuristic which has shown a remarkable performance when solving hard optimization problems. In this paper, we propose a thread-based parallel version of MOEA/D designed to be executed on modern multi-core processors. Our interest is to study the potential benefits of the parallel approach in terms of speed-ups and the quality of the obtained Pareto front approximations when solving a benchmark composed of nine problems. The obtained results on two different multi-core based machines indicate that notable time reductions can be achieved. We have also found out that, with a few exceptions, there are not significant differences in terms of solution quality among the sequential MOEA/D and the parallel versions of it when using up to eight threads.
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Nebro, A.J., Durillo, J.J. (2010). A Study of the Parallelization of the Multi-Objective Metaheuristic MOEA/D. In: Blum, C., Battiti, R. (eds) Learning and Intelligent Optimization. LION 2010. Lecture Notes in Computer Science, vol 6073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13800-3_32
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DOI: https://doi.org/10.1007/978-3-642-13800-3_32
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