科研之友
微信
新浪微博
Facebook
分享链接
摘要
It is well known that mutation scale factor, the crossover constant, and the population size are three main control parameters of the differential evolution (DE) algorithm. These parameters are of great importance to the efficiency of a DE algorithm. However, finding appropriate settings is a difficult task. In this work, a self-adaptive DE with population adjustment scheme (SAPA) is proposed to tune the size of offspring population. The novel algorithm involves two DE strategies and two population adjustment schemes. The performance of the SAPA algorithm is evaluated on a set of benchmark problems. Simulation results show that the proposed algorithm is better than, or at least comparable with, other classic or adaptive DE algorithms. Performance comparisons with some other well-known evolutionary algorithms from literatures are also presented.
