An improved theta-PSO algorithm with crossover and mutation

Particle swarm optimization (PSO) is an efficient optimization algorithm. A theta-PSO based on phase angle was put forward in our previous work, which has good optimization performance when dealing with some benchmark functions. But this algorithm may easily stick in the local minima sometime when handling some complex multi-mode functions. To enhance the optimization performance, crossover and mutation operators were introduced in this paper. Benchmark testing of some multi-mode functions shows that this improved theta-PSO can overcome the local minima and achieve the goal of global minimum in limited iterations.