Competitive two - island cooperative coevolution for real parameter global optimisation

Cooperative coevolution has proven to be efficient in solving global optimisation and real world application problems. However, it is highly sensitive to problem decomposition, especially in the context of non-separable functions that possess interacting decision variables. Problem decomposition has been a challenge of cooperative coevolution. Efficient problem decomposition strategy ensures that interacting variables are grouped into separate subcomponents. Introduction of competition and collaboration features have shown to be advantageous in evolutionary algorithms but have not quite been fully explored in cooperative coevolution. In this paper, a method is utilized that enforces competition in coevolution whereby different problem decomposition schemes are implemented as islands that compete and collaborate with each other. The proposed framework is tested on several global optimisation benchmark problems and achieves promising results