The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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A New Approach to Adaptive HFC-based GAs: Comparative Study on Crossover Genetic Operator

적응 HFC 기반 유전자알고리즘의 새로운 접근: 교배 유전자 연산자의 비교연구

  • Published : 2008.09.01
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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

References

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