Optimization and Verification of Parameters Used in Successive Zooming Genetic Algorithm

J. Ocean Eng. Technol. 2004;18(5):29-35.

KWON YOUNG-DOO,KWON HYUN-WOOK,KIM JAE-YONG,JIN SEUNG-BO

순차적 주밍 유전자 알고리즘 기법에 사용되는 파라미터의 최적화 및 검증

권영두,권현욱,김재용,진승보

경북대학교 기계공학과,경북대학교 기계공학과 대학원,경북대학교 기계공학과 대학원,경북대학교 기계공학과 대학원

Keywords: Successive Zooming Genetic Algorithm(SZGA), Reliability, Zooming Factor

핵심용어: 순차적 주밍 유전자 알고리즘, 신뢰도, 주밍인자

Abstract

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.