Development of integrated evolutionary optimization algorithm and its application to optimum design of ship structures

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WEB OF SCIENCE

6
Citations

SCOPUS

6

초록

This paper proposes an integrated evolutionary optimization algorithm (IEOA) which is combined with genetic algorithm (GA), random tabu search method (TS) and response surface methodology (RSM). This algorithm, in order to improve the convergent speed that is thought to be the demerit of GA, uses RSM and the simplex method. Though mutation of GA offers random variety, systematic variety can be secured through the use of tabu-list. Efficiency of this method has been proven by applying traditional test functions and comparing the results to GA. And it is an evidence that the newly suggested algorithm can effectively find the global optimum solution by applying it to minimize the weight of fresh water tank that is placed in the rear of ship designed to avoid resonance. According to the results, GA's convergent speed in initial phase has been improved by using RSM. An optimized solution was calculated without the evaluation of additional actual objective function. Finally, it can be concluded that IE0A is a very useful global optimization algorithm from the viewpoint of convergent speed and global search ability.

키워드

evolutionary optimization algorithms; genetic algorithm; response surface methodology; tabu search method; simplex method; fresh water tank; GENETIC ALGORITHM; SIMPLEX-METHOD
제목
Development of integrated evolutionary optimization algorithm and its application to optimum design of ship structures
저자
Kong, Young-Mo; Choi, Su-Hyun; Yang, Bo-Suk; Choi, Byeong-Keun
DOI
10.1007/s12206-008-0402-0
발행일
2008-07
유형
Article
저널명
Journal of Mechanical Science and Technology
권
22
호
7
페이지
1313 ~ 1322