Improved Catfish Particle Swarm Optimization with Fuzzy Adaptation

Catfish particle swarm optimization (CatfishPSO) algorithm is a novel swarm intelligence optimization, which inspired by the behavior between sardines and catfish, i.e. the so-called catfish effect is applied to improve the performance of particle swarm optimization (PSO). In this paper, we propose an improved CatfishPSO with fuzz), adaptive (F-CatfishPSO), which a fuzzy system is implemented to dynamically adapt the inertia weight of the CatfishPSO. In the conducted experiments, we adapt the inertia weight to strengthen the solution quality of PSO and CatfishPSO via fuzzy system. Six benchmark functions with unimodal and multimodal different trait are selected as the test functions. The experimental results indicate that the performance of the F-CatfishPSO is better than methods from the literature by statistical analysis.