一种阶段性策略自适应差分进化算法

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 106-110.

一种阶段性策略自适应差分进化算法

倪洪杰, 彭春祥, 周晓根, 俞立

浙江工业大学信息工程学院杭州310023

出版日期:2019-06-14 发布日期:2019-07-02
通讯作者: 倪洪杰(1978－),男,博士生,主要研究方向为智能信息处理、优化理论及算法设计,E-mail:zdfynhj@zjut.edu.cn
作者简介:彭春祥(1995－),男,硕士生,主要研究方向为优化理论及算法设计、生物信息学;周晓根(1987－),男,博士,CCF学生会员,主要研究方向为智能信息处理、优化理论及算法设计和生物信息学;俞立(1961－),男,博士,教授,主要研究方向为无线传感器网络、鲁棒控制和网络化控制系统。
基金资助:
本文受浙江省重点研发计划项目(2017C03060),国家自然科学基金(61573317)资助。

Differential Evolution Algorithm with Stage-based Strategy Adaption

NI Hong-jie, PENG Chun-xiang, ZHOU Xiao-gen, YU Li

College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 针对差分进化算法的变异策略选择问题,提出一种阶段性策略自适应差分进化算法(SSADE)。首先,根据各个体与当前最优个体之间的平均距离衡量种群的拥挤度,进而估计种群的进化阶段;然后,将整个种群划分为多个子种群,并针对不同阶段的特性,设计子种群协同进化变异策略池;最后,根据各变异策略的历史成功信息,从对应的策略池中动态自适应地选择合适的变异策略,从而达到平衡全局探测和局部搜索的目的。在12个经典测试函数上的实验结果表明,所提SSADE算法在计算代价、可靠性、解的质量和扩展性方面优于现有主流算法。

关键词: 策略自适应, 差分进化, 全局优化, 协同进化, 子种群

Abstract: To solve the problem of the selection for the mutation strategy in differential evolution algorithm,this paper proposed a differential evolution with stage-based strategy adaption.Firstly,the crowding degree of the population is measured by the average distance between each individual and the best individual,and the evolution stage is estimated.Then,the population is divided into multiple sub-populations,and a pool mutation strategy based on the coevolution of sub-populations is designed for different stages.Finally,according to the historical success information of each strategy,a suitable strategy is adaptively selected from the corresponding strategy pool to balance the exploration and exploitation.Experimental results on 12 classical test functions show that the proposed algorithm is superior to the mainstream algorithm in terms of the computational cost,success rate,quality of the solution,and scalability.

Key words: Coevolution, Differential evolution, Global optimization, Strategy self-adaption, Sub-population

中图分类号:

TP391

倪洪杰, 彭春祥, 周晓根, 俞立. 一种阶段性策略自适应差分进化算法[J]. 计算机科学, 2019, 46(6A): 106-110. https://doi.org/

NI Hong-jie, PENG Chun-xiang, ZHOU Xiao-gen, YU Li. Differential Evolution Algorithm with Stage-based Strategy Adaption[J]. Computer Science, 2019, 46(6A): 106-110. https://doi.org/

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