Approaches to parallelize pareto ranking in NSGA-II algorithm

Authors:
Algirdas Lančinskas;Julius Žilinskas
Affiliations:
Institute of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania;Institute of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania
Venue:
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part II
Year:
2011

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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.