[1]张茂清,汪镭,崔志华,等.基于混合策略的快速非支配排序算法II[J].郑州大学学报(工学版),2020,41(04):23-27.[doi:10.13705/j.issn.1671-6833.2020.04.007]
　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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基于混合策略的快速非支配排序算法II()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
41
期数:
2020年04期
页码:
23-27
栏目:
出版日期:
2020-08-12

文章信息/Info

Title:
Fast Non-dominated Sorting Genetic Algorithm II Based on Hybrid Strategies
作者:
张茂清; 汪镭; 崔志华; 郭为安
1. 同济大学电子与信息工程学院2. 太原科技大学计算机科学与技术学院3. 同济大学中德工程学院
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
关键词:
NSGA-Ⅱ; 多目标优化; 锦标赛策略; 混合策略; 种群多样性
Keywords:
NSGA-Ⅱ; Multi-objective optimization; tournament strategy; hybrid strategy; population diversity
DOI:
10.13705/j.issn.1671-6833.2020.04.007
文献标志码:
A
摘要:
快速非支配排序算法II（Fast Non-dominated Sorting Algorithm II, NSGA-II）是一个经典多目标优化算法，其中，锦标赛策略被用于选择交叉操作的父代个体。然而，锦标赛策略存在重复选择交叉父代个体的缺陷，并会进一步导致后代个体多样性的降低。为解决此问题，本问题出两种改进策略：第一，引入Lévy分布，对父代个体产生扰动，以此增加发现父代个体周围潜在较优个体的能力 第二，提出三父代个体的交叉策略，以降低重复选择父代个体的现象。通过将本文所提算法与其他算法对比，发现本文所提策略有效改进NSGA-II的整体性能。
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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更新日期/Last Update: 2020-10-06