A time-varying mirrored S-shaped transfer function for binary particle swarm optimization

Abstract

Binary Particle swarm optimization (BPSO) is one of the most popular swarm intelligence algorithms to solve binary optimization problems. It has a few parameters, simple structure, and high execution speed. A transfer function is applied in BPSO to convert the continuous search space to the binary one. This algorithm and its variants can sometimes find local optima or exhibit slow convergence speed. Thus, many researchers have improved the structure of BPSO and its transfer function to overcome these shortcomings. In this study, a new time-varying mirrored S-shaped transfer function for BPSO (TVMS-BPSO) is introduced to enhance global exploration and local exploitation in the algorithm. The performance of the proposed transfer function has been compared with some well-known BPSO algorithms and binary meta-heuristic algorithms. These algorithms have been evaluated by CEC 2005 benchmark functions and set of 0–1 multidimensional knapsack problem (MKP) benchmark instances. The experimental results showed that the new transfer function significantly enhances the efficiency of BPSO for both local and global topologies in terms of solution accuracy and convergence speed.