Adaptive Cuckoo search based on ranking of search point
Yuki Miyake, Kenichi Tamura, Junichi Tsuchiya, Keiichiro Yasuda · 2017
Recently, the development of high-performance metaheuristics has become an important subject. In this study, an adaptive Cuckoo Search based on ranking of search point is proposed. This study aims to improve the performance of Cuckoo Search by adjusting the parameter β to allow search points with good evaluation value to search nearby and those with poor evaluation value to search far away. Finally, the performance of the proposed method is evaluated by numerical experiments.