A single-point mutation evolutionary programming

被引：24

作者：

Ji, MJ ^{[1
]}

Tang, HW

Guo, J

机构：

[1] Dalian Univ Technol, Dept Appl Math, Dalian 116024, Peoples R China

[2] Dongbei Univ Finance & Econ, Dept Quantitat Econ, Dalian 116025, Peoples R China

来源：

INFORMATION PROCESSING LETTERS | 2004年 / 90卷 / 06期

关键词：

single-point mutation; classical evolutionary programming; fast evolutionary programming; generalized evolutionary programming; algorithms;

D O I：

10.1016/j.ipl.2004.03.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose an improved evolutionary programming based on single-point mutation, which is named Single-Point Mutation Evolutionary Programming (SPMEP). The distinctions between SPMEP and the classical evolutionary programming (EP) are the single-point mutation for each solution in each iteration and the fixed mutation scheme for deviation eta. Simulation results show that SPMEP is obviously superior to the classical EP, fast EP and generalized EP for multimodal and high-dimensional functions. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：293 / 299

页数：7

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