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Optimization and Verification of Parameters Used in Successive Zooming Genetic Algorithm  

KWON YOUNG-DOO (경북대학교 기계공학과)
KWON HYUN-WOOK (경북대학교 기계공학과 대학원)
KIM JAE-YONG (경북대학교 기계공학과 대학원)
JIN SEUNG-BO (경북대학교 기계공학과 대학원)
Publication Information
Journal of Ocean Engineering and Technology / v.18, no.5, 2004 , pp. 29-35 More about this Journal
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.
Keywords
Successive Zooming Genetic Algorithm(SZGA); Reliability; Zooming Factor;
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