An Efficient Parameter Optimization Approach Based on Real-Coded Genetic Algorithm-Reference-Cited by-同舟云学术

An Efficient Parameter Optimization Approach Based on Real-Coded Genetic Algorithm

Published:2012-02 Issue: Volume:479-481 Page:1835-1840
ISSN:1662-8985
Container-title:Advanced Materials Research
language:
Short-container-title:AMR

Author:

Chen Zhi Qiang¹

Affiliation:

1. Chongqing Technology and Business University

Abstract

In this paper, we present an efficient parameter optimization approach based on real-coded genetic algorithm, which breeds selectively offspring based on difference between individuals. A new crossover operator is proposed which generates offspring around the center of mass of parents with Laplace distribution. A set of 14 test problems available in the global optimization literature is used to evaluate the performance of proposed genetic algorithm. The comparative study shows that the proposed genetic algorithm performs quite well for parameter optimization problem.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Link

https://www.scientific.net/AMR.479-481.1835.pdf

Reference11 articles.

1. L.J. Eshelman, J.D. Schaffer, in: Real-coded genetic algorithms and interval schemata, Foundation of Genetic Algorithms II, Morgan Kaufmann, San Mateo, CA(1993), pp.187-202.

2. K. Deb, R.B. Agrawal, Complex Systems 9 (1995), pp.115-148.

3. I. Ono, S. Kobayashi, in: T. Back (Ed. ), Proceedings of the Seventh International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo, CA(1997), pp.246-253.

4. S. Tsutsui, M. Yamamura, T. Higuchi, in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-1 1999), pp.657-664.

5. K. Deb, A. Anand, D. Joshi, Evolutionary Computation Journal 10 (4) (2002), pp.371-395.