An island-based differential evolution algorithm with the multi-size populations

Abstract

Computational intelligence methods can provide high-quality solutions to a variety of complex optimization problems where exact analytical solutions are impossible to obtain within a reasonable time and other resources used. The article proposes a novel concept of island model with islands of different sizes as well as differential evolution algorithms implementing this concept. Such a multi-size approach facilitates the design of island-based algorithms and brings a variety of benefits. Among them: improved fitness dynamics throughout the entire time of operation even without migration of solutions among the islands. The absence of migration eliminates the need to establish the topology and the policy of migration. It also makes the efficiency of multi-size island-based algorithms independent of the particular islands' size and practically eliminates the need of tuning the size of islands which is usually done in the case of the canonical island model. All these features indicate the superiority of the proposed multi-size island model over the canonical one. The efficiency of the proposed multi-size approach has been tested by solving one of the most difficult scheduling problems which is the discrete-continuous scheduling with continuous resource discretization.