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Hybridizing Adaptive Genetic Algorithm with Chaos Searching Technique for Numerical Optimization
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- 발행기관
- 보안공학연구지원센터(IJGDC) 바로가기
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- 간행물
- International Journal of Grid and Distributed Computing SCOPUS 바로가기
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- 통권
- Vol.9 No.2 (2016.02)바로가기
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- 페이지
- pp.131-144
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A271594
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Genetic algorithm (GA) is a population-based approach for heuristic search in optimi- zation problems based on the principle of biologic evolution and natural selection. In this paper, we present a hybrid adaptive genetic algorithm with chaos searching technique for numerical optimization. On the one hand, two sets of crossover and mutation rates are for- mulated to automatically maintain the balance between exploration and exploitation during the genetic search process. On the other hand, the chaos searching technique is introduced into the adaptive genetic algorithm based on the decision mechanism for premature conver- gence adopted in this paper, whose main goal is to avoid being trapped into the local opti- mum. In addition, half of the total evolutionary generation is utilized as one of the decision conditions so as to speed up the convergent process. To validate the effectiveness and efficiency of the proposed approach, we apply it to four benchmark functions obtained from the literature, and the experimental results show that the proposed algorithm can find global optimal or the closer-to-optimal solutions and have faster search speed as well as higher convergence rate.
목차
Abstract
1. Introduction
2. Dynamic Adjustments of Crossover and Mutation Rates by AGA Itself
2.1 Dynamic Linear Adjustments
2.2 Dynamic Nonlinear Adjustments
3. Dynamic Adjustments of Crossover and Mutation Rates with Heuristics
3.1 Heuristic 1
3.2 Heuristic 2
3.3 Heuristic 3
4. Hybrid AGA with Chaos Searching Technique
4.1 Chaos Searching Technique
4.2 AGA with Chaos Searching Technique
5. Experimental Results and Analysis
6. Conclusions and Future Work
Acknowledgements
References
키워드
Adaptive genetic algorithm (AGA) Chaos searching Exploration Exploitation Hybrid soft computing (HSC)저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Grid and Distributed Computing
- 간기
- 격월간
- pISSN
- 2005-4262
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.9 No.2
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