Particle multi-swarm optimization: A proposal of multiple particle swarm optimizers with information sharing

For enhancing the search performance of multiple particle swarm optimizers, in this paper we propose multiple particle swarm optimizers with information sharing by introducing a special strategy, called multi-swarm information sharing. The crucial idea here is to add a new confidence term into the updating rule of the particle's velocity by the best solution found by the multi-swarm search. This is a new approach for the technical development of particle multi-swarm optimization (PMSO) itself. In order to confirm the performance effectiveness of the information sharing strategy in the proposed multiswarm search, computer experiments of implementing a suite of benchmark problems are carried out. We investigate the intrinsic characteristics of the proposed methods, and compare them with the search ability and efficiency of multi-swarm information sharing without this strategy. The obtained experimental results show that the proposed methods have better search performance.