Species co-evolutionary algorithm: a novel evolutionary algorithm based on the ecology and environments for optimization

摘要

In classic evolutionary algorithms (EAs), solutions communicate each other in a very simple way so the recombination operator design is simple, which is easy in algorithms' implementation. However, it is not in accord with nature world. In nature, the species have various kinds of relationships and affect each other in many ways. The relationships include competition, predation, parasitism, mutualism and pythogenesis. In this paper, we consider the five relationships between solutions to propose a co-evolutionary algorithm termed species co-evolutionary algorithm (SCEA). In SCEA, five operators are designed to recombine individuals in population. A set including several classical benchmarks are used to test the proposed algorithm. We also employ several other classical EAs in comparisons. The comparison results show that SCEA exhibits an excellent performance to show a huge potential of SCEA in optimization.