Double-Swarm Binary Particle Swarm Optimization

Abstract

The Binary Particle Swarm Optimization (BPSO) is the most popular swarm-based algorithm to tackle binary optimization problems. Based on the high performance of the BPSO, many proposals have been developed presenting modifications in the standard method. However, in the last decade, the Binary Cat Swarm Optimization (BCSO) has gained attention. In this paper, we introduce a new algorithm called Double-Swarm BPSO, which presents some modifications on the BPSO inspired in the BCSO optimization process. In this case, we propose to divide the agents into two sub-swarms. The experiments showed that the proposal overcomes the previous popular swarm-based methods and binary versions of the Genetic Algorithm in some instances of the 0/1 knapsack problem, especially in high dimension cases.