Fast Non-dominated Sorting Genetic Algorithm II Based on Hybrid Strategies

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Fast Non-dominated Sorting Genetic Algorithm II Based on Hybrid Strategies

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[1]ZHANG Maoqing,WANG Lei,CUI Zhihua,et al.Fast Non-dominated Sorting Genetic Algorithm II Based on Hybrid Strategies[J].Journal of Zhengzhou University (Engineering Science),2020,41(04):23-27.[doi:10.13705/j.issn.1671-6833.2020.04.007]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 41 Number of periods: 2020 04 Page number: 23-27 Column: Public date: 2020-08-12

Title:: Fast Non-dominated Sorting Genetic Algorithm II Based on Hybrid Strategies

Author(s):: ZHANG Maoqing1; WANG Lei1; CUI Zhihua2; GUO Weian3; 1.School of Electronics and Information,Tongji University,Shanghai 201804,China;2.School of Computer Science and Technology,Taiyuan University of Science and Technology,Shanxi 030024,China;3.Sino-Germany College of Applied Sciences,Tongji University,Shanghai 201804,China

Keywords:: NSGA-Ⅱ; Multi-objective optimization; tournament strategy; hybrid strategy; population diversity

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2020.04.007

Abstract:: Fast Non-dominated Sorting Algorithm II（NSGA-II）is an classics multi-objective optimization algorithm, in which tournament selection strategy is used to select parent individuals to do crossover operator. However, Tournament selection strategy has the drawback that the same individual may be selected many times, resulting in the low diversity of offspring population. To tackle this problem, this paper proposes two strategies. The first is to introduce Lévy distribution to parent individuals for increasing the probability of discovering potential better individuals around patent individuals while the second is to introduce crossover strategy with three patent individuals to decrease the probability of repeatedly selecting the same parent individuals. By comparison with other algorithms, the proposed method can efficiently improve the overall performance of NSGA-II.

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Last Update: 2020-10-06