Abstract
In this paper, we propose an improved genetic algorithm based on the combination of Bee system and Inverse-elitism, both are effective strategies for the improvement of GA. In the Bee system, in the beginning, each chromosome tries to find good solution individually as global search. When some chromosome is regarded as superior one, the other chromosomes try to find solution around there. However, since chromosomes for global search are generated randomly, Bee system lacks global search ability. On the other hand, in the Inverse-elitism, an inverse-elite whose gene values are reversed from the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes, but it lacks local search ability. In the proposed method, the Inverse-elitism with Pseudo-simplex method is employed for global search of Bee system in order to strengthen global search ability. In addition, it also has strong local search ability. The proposed method has synergistic effects of the three strategies. We confirmed validity and superior performance of the proposed method by computer simulations.
| Original language | English |
|---|---|
| Pages (from-to) | 883-889 |
| Number of pages | 7 |
| Journal | IEEJ Transactions on Electronics, Information and Systems |
| Volume | 124 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2004 |
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Keywords
- function optimization
- genetic algorithm
- pseudo-simplex method
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Improved Genetic Algorithm Based on the Cooperation of Elite and Inverse-elite. / Kanakubo, Masaaki; Hagiwara, Masafumi.
In: IEEJ Transactions on Electronics, Information and Systems, Vol. 124, No. 3, 2004, p. 883-889.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Improved Genetic Algorithm Based on the Cooperation of Elite and Inverse-elite
AU - Kanakubo, Masaaki
AU - Hagiwara, Masafumi
PY - 2004
Y1 - 2004
N2 - In this paper, we propose an improved genetic algorithm based on the combination of Bee system and Inverse-elitism, both are effective strategies for the improvement of GA. In the Bee system, in the beginning, each chromosome tries to find good solution individually as global search. When some chromosome is regarded as superior one, the other chromosomes try to find solution around there. However, since chromosomes for global search are generated randomly, Bee system lacks global search ability. On the other hand, in the Inverse-elitism, an inverse-elite whose gene values are reversed from the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes, but it lacks local search ability. In the proposed method, the Inverse-elitism with Pseudo-simplex method is employed for global search of Bee system in order to strengthen global search ability. In addition, it also has strong local search ability. The proposed method has synergistic effects of the three strategies. We confirmed validity and superior performance of the proposed method by computer simulations.
AB - In this paper, we propose an improved genetic algorithm based on the combination of Bee system and Inverse-elitism, both are effective strategies for the improvement of GA. In the Bee system, in the beginning, each chromosome tries to find good solution individually as global search. When some chromosome is regarded as superior one, the other chromosomes try to find solution around there. However, since chromosomes for global search are generated randomly, Bee system lacks global search ability. On the other hand, in the Inverse-elitism, an inverse-elite whose gene values are reversed from the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes, but it lacks local search ability. In the proposed method, the Inverse-elitism with Pseudo-simplex method is employed for global search of Bee system in order to strengthen global search ability. In addition, it also has strong local search ability. The proposed method has synergistic effects of the three strategies. We confirmed validity and superior performance of the proposed method by computer simulations.
KW - function optimization
KW - genetic algorithm
KW - pseudo-simplex method
UR - http://www.scopus.com/inward/record.url?scp=85024727021&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85024727021&partnerID=8YFLogxK
U2 - 10.1541/ieejeiss.124.883
DO - 10.1541/ieejeiss.124.883
M3 - Article
VL - 124
SP - 883
EP - 889
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
SN - 0385-4221
IS - 3
ER -