멀티모달 함수의 최적화를 위한 멘델 연산 유전자 알고리즘

Abstract

In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendel`s genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.