Modified differential evolution and its application

被引：0

作者：

Lu Q. ^{[1
,2
]}

Zhang X. ^{[1
]}

Wen S. ^{[1
]}

Wu M. ^{[1
]}

Lan G. ^{[1
]}

Liu L. ^{[1
]}

机构：

[1] College of Mechanical Electronic Engineering, Taiyuan University of Science and Technology

[2] Department of Electrical and Electronic Engineering, Zhengzhou Technical College

来源：

Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery | 2010年 / 41卷 / 02期

关键词：

Choas; Differential evolution; Disaster factor; Global optimal capability;

D O I：

10.3969/j.issn.1000-1298.2010.02.039

中图分类号：

学科分类号：

摘要：

Differential evolution (DE) is one kind of evolution algorithm based on difference of individuals. DE has exhibited good performance on optimization. However, for the high dimension and perplexed function, the algorithm is apt to fall into premature convergence, its performance is strongly influenced by the value of each strategy parameter including scale factor. Therefore, a modified differential evolution algorithm (MDE) was proposed to solve the optimization problems. First, the scale factor was randomly initialized and calculated by chaos each generation, which decreases the participation of user and balances the convergency speed and global optimal capability. Next, disaster factor was introduced to eliminate the individual of a small probability, along with a new individual generating, which can increase the diversity of population and global optimal capability. Simulated results and engineering optimization design example showed that MDE outperforms standard DE in global optimal capability.

引用

页码：193 / 197

页数：4

共 17 条

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