An Improved PSO for Multimodal Complex Problem

摘要: As the multimodal complex problem has many local optima, basic PSO is difficult to effectively solve this kind of problem. To conquer defect, firstly, we adopt Monte Carlo method simulate fly trajectory particle, and conclude reason for falling into optima. Then, by defining distance, average distance maximal between particles, an adaptive control factor (Adaptive rejection factor, ARF) pp pg was proposed increase ability escaping from In order test strategy, three benchmarks were selected conduct analysis convergence property statistical property. The simulation results show that particle swarm optimizer based on (ARFPSO) can avoid premature phenomenon. Therefore, ARFPSO available problems.