Abstract
In this paper several new approaches to parallelize multi-objective optimization algorithm NSGA-II are proposed, theoretically justified and experimentally evaluated. The proposed strategies are based on the optimization and parallelization of the Pareto ranking part of the algorithm NSGA-II. The speed-up of the proposed strategies have been experimentally investigated and compared with each other as well as with other frequently used strategy on up to 64 processors.
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Lančinskas, A., Žilinskas, J. (2012). Approaches to Parallelize Pareto Ranking in NSGA-II Algorithm. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2011. Lecture Notes in Computer Science, vol 7204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31500-8_38
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DOI: https://doi.org/10.1007/978-3-642-31500-8_38
Publisher Name: Springer, Berlin, Heidelberg
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