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Reliability Optimization Problems Using Adaptive Hybrid Genetic Algorithms
Minoru Mukuda*, YoungSu Yun**, and Mitsuo Gen***
*Department of Information Engineering, Nippon Institute of Technology, Minami-Saitama 345-8501, Japan
**School of Automotive, Industrial & Mechanical Engineering, Daegu University, Gyeongbuk Gyeongsan 712-714, Korea (Corresponding Author)
***Graduate School of Information, Production & Systems, Waseda University, Kitakyushu 808-0135, Japan
Received:September 25, 2003Accepted:March 29, 2004Published:July 20, 2004
Keywords:hybrid genetic algorithm, reliability optimization problem, adaptive scheme
Abstract
This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a local search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are considered. These aHGAs are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aHGA outperforms the other competing aHGAs.
Cite this article as:M. Mukuda, Y. Yun, and M. Gen, “Reliability Optimization Problems Using Adaptive Hybrid Genetic Algorithms,” J. Adv. Comput. Intell. Intell. Inform., Vol.8 No.4, pp. 437-441, 2004.Data files:
