A Modified Differential Evolution Algorithm with Local Enhanced Operator

ZHAO Guang-quan; PENG Xi-yuan; SUN Ning

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A Modified Differential Evolution Algorithm with Local Enhanced Operator

更新时间：2025-07-16

- A Modified Differential Evolution Algorithm with Local Enhanced Operator
- Acta Electronica Sinica Vol. 35, Issue 5, Pages: 849-853(2007)
- 作者机构：
  
  哈尔滨工业大学科学园3033信箱,黑龙江,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：2007
- 稿件说明：
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ZHAO Guang-quan, PENG Xi-yuan, SUN Ning. A Modified Differential Evolution Algorithm with Local Enhanced Operator[J]. Acta Electronica Sinica, 2007, 35(5): 849-853.
DOI：

ZHAO Guang-quan, PENG Xi-yuan, SUN Ning. A Modified Differential Evolution Algorithm with Local Enhanced Operator[J]. Acta Electronica Sinica, 2007, 35(5): 849-853. DOI：

摘要

微分进化算法具有鲁棒性强、易于使用、控制参数少等优点.但在搜索中存在一定的盲目性

搜索效率不高.本文通过引入局部增强算子

使种群中的部分个体在当前最优个体附近寻优

以加快算法的收敛速度.利用五个标准的优化算法测试函数对改进算法进行了测试

并与动态微分进化算法和微粒群算法进行了比较.算法分析和仿真结果表明

本文提出的改进算法大大提高了算法搜索效率.

Abstract

The differential evolution algorithm is robust

easy to use

and requires few control parameters.However

as the search of the algorithm is of some blindness

its efficiency is limited.To improve the efficiency of the algorithm

the local enhanced operator is proposed to make some individuals of the population search around the current best individual.Numerical study is carried out using five benchmark functions

and the result is compared with that of dynamic differential evolution and particle swarm optimization.Analysis and simulation results show that the efficiency of modified differential evolution is significantly improved.

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Related Institution

College of Information and Communication Engineering, Beijing Information Science & Technology University

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School of Applied MathematicsUniversity of Electronic Science and Technology of ChinaChengduSichuan 610054China

Department of Mathematical SciencesXidian UniversityXi’anShaanxi 710071China

School of Applied Mathematics,University of Electronic Science and Technology of China

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