DocumentCode
3583174
Title
A dynamically switched crossover for genetic algorithms
Author
Ming, Liang ; Cheung, Yiu-Ming ; Wang, Yu-Ping
Author_Institution
Fac. of Sci., Xidian Univ., Xi´´an, China
Volume
5
fYear
2004
Firstpage
3254
Abstract
The traditional crossover operator performs the constant crossover between two parents without considering their homogeneity. Actually, the more homogeneous the parents are, the more disruptive the crossover should be. In this paper, a self-adaptive mechanism named adaptive recombination with three sub-populations (ARTS) is therefore presented to control the crossover operator of a genetic algorithm. The ARTS allows the crossover to be dynamically switched among two-point crossover (i.e., the least disruptive crossover), uniform crossover with probability 0.2, and uniform crossover with probability 0.5 (i.e., the most disruptive crossover). The experiments have shown the promising results.
Keywords
adaptive control; genetic algorithms; probability; self-adjusting systems; adaptive recombination with three subpopulations; crossover operator control; dynamically switched crossover operator; genetic algorithms; probability; self adaptive mechanism; Adaptive control; Algorithm design and analysis; Computer science; Frequency; Genetic algorithms; Machine learning; Probability; Programmable control; Subspace constraints; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1378597
Filename
1378597
Link To Document