基于跳跃基因的多目标差分进化算法

doi:10.3969/j.issn.1000-3428.2016.04.030

计算机工程

基于跳跃基因的多目标差分进化算法

刘峥,郑力明

(暨南大学电子工程系,广州 510000)

收稿日期:2015-09-21 出版日期:2016-04-15 发布日期:2016-04-15
作者简介:刘峥(1990-),男,硕士研究生,主研方向为人工智能、多目标优化;郑力明,教授、博士。
基金资助:
广东省对外科技合作基金资助项目(2013B051000060);广东省教育部产学研结合基金资助重点项目(2011A090200085);深圳市科技创新委员会基金资助项目(ZYC201105180515A)。

Multi-objective Differential Evolution Algorithm Based on Jumping Genes

LIU Zheng,ZHENG Liming

(Department of Electronic Engineering,Jinan University,Guangzhou 510000,China)

Received:2015-09-21 Online:2016-04-15 Published:2016-04-15

摘要/Abstract

摘要： 为解决现有多目标差分进化算法容易陷入局部最优的问题,引入跳跃基因算子,提出基于跳跃基因的多目标差分进化算法。改进现有的多目标差分算法,在传统交叉算子之后执行跳跃基因操作,以保持种群多样性。数值实验结果表明,该算法能较好地解决局部最优问题,在ZDT和DTLZ测试函数集上具有明显优于现有算法的收敛性能。

关键词: 跳跃基因, 局部最优, 困难问题, 多目标差分进化算法

Abstract: In order to handle the local optimum problem of the existing multi-objective differential evolution algorithms,the jumping genes operation is introduced and a novel multi-objective differential evolution algorithm based on jumping genes is presented.Different from the existing algorithms,the proposed algorithm performs jumping genes operation after the classical crossover operation,in order to improve the population diversity.Numerical experimental results indicate that the proposed algorithm is capable of dealing with the local optimum problem and exhibits significantly better convergence performance than the existing algorithms on ZDT and DTLZ function tests.

Key words: jumping gene, local optimum, difficult problem, multi-objective differential evolution algorithm

中图分类号:

TP301.6

刘峥,郑力明. 基于跳跃基因的多目标差分进化算法[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.04.030.

LIU Zheng,ZHENG Liming. Multi-objective Differential Evolution Algorithm Based on Jumping Genes[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.04.030.

http://www.ecice06.com/CN/Y2016/V42/I4/168

参考文献

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