Island-based differential evolution with varying subpopulation size

Abstract

Differential evolution (DE) is one of the evolutionally algorithms for solving optimization problems in a continuous space. DE has been widely applied to solve various optimization problems. Additionally, many modified DE algorithms have been developed in an attempt to improve search performance. In this paper, we propose island-based DE with varying subpopulation size. Island model is one of the effective parallel distributed model in evolutionary algorithms. In the proposed method, total population is divided into independent sub-populations called islands. The basic island model uses same control parameters for each subpopulation. In contrast, we allocate different control parameters to each island. Therefore, each island has a different convergence characteristic by using own control parameters. At fixed generation intervals, migration among islands is performed in order to preserve diversity of subpopulation. Additionally, by incorporating the operation of individual transfer, proposed method can vary subpopulation dynamically according to the function landscape. Numerical experiments are performed to illustrate the performance of the proposed method compared with basic DE. The results show that the proposed method outperforms basic DE on standard test functions including various landscape features.