Effect of Link Length, Population Size, and Mutation Rate on the Convergence of an Order-Based Genetic Algorithm

Author

Hei Wong
Ming-Chuan Leu, Missouri University of Science and TechnologyFollow

Editor(s)

Stelson, K. and Oba, F.

Abstract

The convergence of an order-based genetic algorithm with random selection and mutation is analyzed in this paper. A measure of difference between two links called `link distance' is defined and used to study the convergence of the genetic algorithm. The changes in the expected average link distance of a mating pool due to genetic drift and mutation are first derived separately and then combined to describe their joint effect on the convergence of the genetic algorithm. The iterations required to reach convergence for various link lengths, population sizes, and mutation rates are obtained. The effects of these parameters are discussed.

Recommended Citation

H. Wong and M. Leu, "Effect of Link Length, Population Size, and Mutation Rate on the Convergence of an Order-Based Genetic Algorithm," Proceedings of the Japan/USA Symposium on Flexible Automation, American Society of Mechanical Engineers (ASME), Jan 1996.

Meeting Name

1996 Japan-USA Symposium on Flexible Automation Part 2

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Convergence of Numerical Methods; Iterative Methods; Neural Methods; Optimization

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1996 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Jan 1996