Canonical deterministic particle swarm optimization to sustain global search

Particle swarm optimization is very simple algorithm. However, the trajectory of each particle becomes pretty complicated because each particle is affected by the information of the other particles. In order to analyze the dynamics of the PSO rigorously, we propose the canonical deterministic PSO (CD-PSO). The CD-PSO is described by a canonical form, and the dynamics is characterized by the damping factor and the rotational angle. The dynamics of the CD-PSO can be analyzed theoretically, however, the solution search performance is worse than the conventional PSO. The reason why the performance of the CD-PSO is poor, is the rotation radius of the particle is decreased with the change of the best position. The small rotation radius contributes to the local search ability, but the global search ability is spoiled. Therefore, we propose a method to sustain the global search for the CD-PSO. The function is realized by maintaining the rotation radius. Applying the proposed method for the CD-PSO, the solution search performance improves that of the conventional CD-PSO.