Particle swarm optimisation based on self-organising topology driven by fitness with different links removing strategies

摘要

In this paper, a novel particle swarm optimisation (PSO) based on self-organising topology driven by fitness (PSO-SOTDF) is proposed. The topology will be gradually generated as the construction process and the optimisation process progress synchronously. And the construction process of topology involves operations of adding and removing links under invariable network sizes. Further, due to the operation of removing links influencing topology characteristics heavily, three kinds of links removing strategies are designed, which are referred to as Removal Strategy I, II and III. To obtain deep insights, the PSO-SOTDF with Removal Strategy I, II and III are used to solve benchmarks. Simulation results show that Removal Strategy I is more effective than other links removing strategies. In addition, the performance of PSO-SOTDF with Removal Strategy I is compared with other variants of PSO. Simulation results indicate that PSO-SOTDF with Removal Strategy I is competitive.