Publication Type

Journal Article

Publication Date

2004

Abstract

In this study, we provide a new taxonomy of parameters of genetic algorithms (GA), structural and numerical parameters, and analyze the effect of numerical parameters on the performance of GA based simulation optimization applications with experimental design techniques. Appropriate levels of each parameter are proposed for a particular problem domain. Controversial to existing literature on GA, our computational results reveal that in the case of a dominant set of decision variable the crossover operator does not have a significant impact on the performance measures, whereas high mutation rates are more suitable for GA applications.

Discipline

Business | Physical Sciences and Mathematics

Research Areas

Operations Management

Publication

Journal of Systemics, Cybernetics and Informatics

Volume

4

Issue

2

First Page

78

Last Page

83

ISSN

1690-4524

Share

COinS