SS4-2 Parameter Analysis and Adaption of Cuckoo Search
◎Wataru Kumagai,Kenichi Tamura,Keiichiro Yasuda(Tokyo Metropolitan University)
In recently years, a new optimization paradigm called metaheuristics attracts attention. In this paper, we focus on Cuckoo Search (CS) that is one of metaheuristics, and propose an adaptive CS to improve its search performance and usability. First, we analyze basically and qualitatively the effects of CS's parameter on its search dynamics. Second, from the analysis results, we define an indicator that evaluates the search state of CS based on the effective metaheuristics strategy. Moreover, based on the indicator, we construct a new mechanism to control the search state by adaptively adjusting a parameter of CS. The performance of the proposed adaptive CS with the parameter adjustment mechanism is verified through numerical simulations for several types of typical benchmark problems.