순차적 주밍 유전자 알고리즘 기법에 사용되는 파라미터의 최적화 및 검증

Optimization and Verification of Parameters Used in Successive Zooming Genetic Algorithm

  • 권영두 (경북대학교 기계공학과) ;
  • 권현욱 (경북대학교 기계공학과 대학원) ;
  • 김재용 (경북대학교 기계공학과 대학원) ;
  • 진승보 (경북대학교 기계공학과 대학원)
  • 발행 : 2004.10.01

초록

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is proposed for identifying a global solution, using continuous zooming factors for optimization problems. In order to improve the local fine-tuning of the GA, we introduced a new method whereby the search space is zoomed around the design variable with the best fitness per 100 generation, resulting in an improvement of the convergence. Furthermore, the reliability of the optimized solution is determined based on the theory of probability, and the parameter used for the successive zooming method is optimized. With parameter optimization, we can eliminate the time allocated for deciding parameters used in SZGA. To demonstrate the superiority of the proposed theory, we tested for the minimization of a multiple function, as well as simple functions. After testing, we applied the parameter optimization to a truss problem and wicket gate servomotor optimization. Then, the proposed algorithm identifies a more exact optimum value than the standard genetic algorithm.

키워드

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