Solving deceptive problems using a genetic algorithm with reserve selection

Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global optimum. This paper presents an improved genetic algorithm with reserve selection to solve deceptive problems. The concept ld...

Full description

Saved in:
Bibliographic Details
Published in2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) pp. 884 - 889
Main Authors Yang Chen, Jinglu Hu, Hirasawa, K., Songnian Yu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2008
Subjects
Convergence
Evolution (biology)
Evolutionary computation
Gallium
Genetic algorithms
Genetics
Search problems
Online AccessGet full text

Cover

More Information
Summary:Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global optimum. This paper presents an improved genetic algorithm with reserve selection to solve deceptive problems. The concept ldquopotentialrdquo of individuals is introduced as a new criterion for selecting individuals for reproduction, where some individuals with low fitness are also let survive only if they have high potentials. An operator called adaptation is further employed to release the potentials for approaching the global optimum. Case studies are done in two deceptive problems, demonstrating the effectiveness of the proposed algorithm.
ISBN:1424418224
9781424418220
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2008.4630900