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A New Approach to Adaptive HFC-based GAs: Comparative Study on Crossover Genetic Operator  

Kim, Gil-Sung (수원대학교 전기공학과)
Choi, Jeoung-Nae (대림대학 전기과)
Oh, Sung-Kwun (수원대학교 전기공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.57, no.9, 2008 , pp. 1636-1641 More about this Journal
Abstract
In this study, we introduce a new approach to Parallel Genetic Algorithms (PGA) which combines AHFCGA with crossover operator. As to crossover operators, we use three types of the crossover operators such as modified simple crossover(MSX), arithmetic crossover(AX), and Unimodal Normal Distribution Crossover(UNDX) for real coding. The AHFC model is given as an extended and adaptive version of HFC for parameter optimization. The migration topology of AHFC is composed of sub-populations(demes), the admission threshold levels, and admission buffer for the deme of each threshold level through succesive evolution process. In particular, UNDX is mean-centric crossover operator using multiple parents, and generates offsprings obeying a normal distribution around the center of parents. By using test functions having multimodality and/or epistasis, which are commonly used in the study of function parameter optimization, Experimental results show that AHFCGA can produce more preferable output performance result when compared to HFCGA and RCGA.
Keywords
Parallel Genetic Algorithm (PGA); Adaptive Hierarchical Fair Competition-based Genetic Algorithm(AHFCGA); Migration; Crossover; Parameter optimization;
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