Non-dominated Sorting Genetic Algorithm II with Dimensionality Perturbation
[1]Zhang Maoqing,Li Dongyang,Huber Wang Lei,et al.Non-dominated Sorting Genetic Algorithm II with Dimensionality Perturbation[J].Journal of Zhengzhou University (Engineering Science),2020,41(01):38-43.[doi:10.13705/j.issn.1671-6833.2020.01.001]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
41
Number of periods:
2020 01
Page number:
38-43
Column:
Public date:
2020-03-10
- Title:
- Non-dominated Sorting Genetic Algorithm II with Dimensionality Perturbation
- Keywords:
- NSGA-ⅡＮ; multi-objective optimization algorithmtournament selectiondimensionality perturbation
- CLC:
- -
- Abstract:
- Non-dominated Sorting Genetic Algorithm II （NSGA-II） is a classical multi-objective optimization algorithm. The strategy of tournament selection employed in NSGA-II may produce a large amount of repeated individuals, and thus decreases the diversity of population and the overall performance. To tackle this problem, this paper proposed NSGA-II based on Dimensionality Perturbation. Firstly, perturbation parameter is introduced, and then it is further used to modify each dimensionality of the parent individuals to do crossover operator. After that, the modified parent individuals do the crossover operator as usual to avoid generⅡating the repeated offspring individuals. To verify the proposed algorithm, ZDT test suit is employed as benchmark problems. Compared to the state-of-art algorithms, the proposed algorithm is capable of effectively improving the performance of NSGA-II, thus demonstrating the effectiveness of the proposed strategy.
- References:
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Last Update:
2020-02-22