Three Sub-Swarm Discrete Particle Swarm Optimization Algorithm

Abstract

Three sub-swarm discrete particle swarm optimization algorithm (THSDPSO) is proposed. The new algorithm assumes that all particles are divided into three sub- swarms. One sub-swarm flies toward the global best position. The second sub-swarm flies in the opposite direction. The last sub-swarm flies randomly around the global best position. In THSDPSO algorithm, two ways are used to handle the position of particles. One way is using the corresponding velocity as a probability measure by the transfer function and THSDPSO with this way is called BTHSDPSO. Another is directly using the hard limit function and THSDPSO with this way is called HTHSDPSO. The two THSDPSOs and basic discrete particle swarm optimization algorithm (DPSO) are all used to solve two well-known test functions' optimization problems. Simulation results show that the two THSDPSOs are both able to find the best fitness more quickly and more precisely than DPSO. Especially the HTHSDPSO has more wonderful optimization performance.