Multiobjective evolutionary algorithms on complex networks

Abstract

Spatially structured populations have been used in evolutionary computation for many years. Somewhat surprisingly, in the multiobjective optimization domain, very few spatial models have been proposed. In this paper, we introduce a new multiobjective evolutionary algorithm on complex networks. Here, the individuals in the evolving population are mapped onto the nodes of alternative complex networks - regular, small-world, scale-free and random. A selection regime based on a non-dominance rating and a crowding mechanism guides the evolutionary trajectory, Our model can be seen as an extension of the standard cellular evolutionary algorithm. However, the dynamical behaviour of the evolving pop..