On benchmarking functions for genetic algorithms

被引：346

作者：

Digalakis, JG ^{[1
]}

Margaritis, KG ^{[1
]}

机构：

[1] Univ Macedonia, Thessaloniki 54046, Greece

来源：

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2001年 / 77卷 / 04期

关键词：

genetic algorithms; benchmarking functions; population size; mutation rate; pseudo-random number generation;

D O I：

10.1080/00207160108805080

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper presents experimental results on the major benchmarking functions used for performance evaluation of Genetic Algorithms (GAs). Parameters considered include the effect of population size, crossover probability, mutation rate and pseudorandom generator. The general computational behavior of two basic GAs models, the Generational Replacement Model (GRM) and the Steady State Replacement Model (SSRM) is evaluated.

引用

页码：481 / 506

页数：26

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