Title

Sexual Selection for Genetic Algorithms

Publication Type

Journal Article

Publication Date

4-2003

Abstract

Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling functions.We also examine common problems and solution methods for such selection schemes. We then propose a new selection scheme inspired by sexual selection principles through female choice selection, and compare the performance of this new scheme with commonly used selection methods in solving some well-known problems including the Royal Road Problem, the Open Shop Scheduling Problem and the Job Shop Scheduling Problem.

Keywords

Genetic algorithm, Scheduling, Selection

Discipline

Operations and Supply Chain Management

Research Areas

Operations Management

Publication

Artificial Intelligence Review

Volume

19

Issue

2

First Page

123

Last Page

152

ISSN

0269-2821

Identifier

10.1023/A:1022692631328

Publisher

Springer Verlag

Additional URL

http://dx.doi.org/10.1023/A:1022692631328