Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 2007.04a
- /
- Pages.233-236
- /
- 2007
Performance Improvement of Genetic Algorithms by Strong Exploration and Strong Exploitation
감 탐색과 강 탐험에 의한 유전자 알고리즘의 성능 향상
- Jung, Sung-Hoon (Department of Information & Communication Engineering, Hansung Univ.)
- 정성훈 (한성대학교)
- Published : 2007.04.20
Abstract
A new evolution method for strong exploration and strong exploitation termed queen-bee and mutant-bee evolution is proposed based on the previous queen-bee evolution [1]. Even though the queen-bee evolution has shown very good performances, two parameters for strong mutation are added to the genetic algorithms. This makes the application of genetic algorithms with queen-bee evolution difficult because the values of the two parameters are empirically decided by a trial-and-error method without a systematic method. The queen-bee and mutant-bee evolution has no this problem because it does not need additional parameters for strong mutation. Experimental results with typical problems showed that the queen-bee and mutant-bee evolution produced nearly similar results to the best ones of queen-bee evolution even though it didn't need to select proper values of additional parameters.