A real-integer-discrete-coded particle swarm optimization for design problems

Abstract

Abstract The successful application of particle swarm optimization (PSO) to various real-valued problems motivates to develop some integer-coded versions of PSO for working directly with integer and discrete variables of a problem. However, in most of such works, actually a real-valued solution is just converted into a desired integer-valued solution by applying some posterior decoding mechanisms, while some problem-specific integer-coded versions of PSO are proposed in others. In this article, a novel version of PSO of general form is proposed, which can work directly with real, integer and discrete variables of a problem without any conversion. Quite satisfactory performance is obtained by applying the proposed PSO to some classical mechanical design problems of different nature.