Abstract
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 IEOA is a very useful global optimization algorithm from the viewpoint of convergent speed and global search ability.
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