Cooperative Multi-Swarms Particle Swarm Optimizer for dynamic environment optimization

Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle swarm optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem. Particles converge at the local place quickly in basic particle swarm optimizer(PSO), led to lose the ability to tracking the dynamic optima. To solve the problem, itpsilas proposed the cooperative multi-swarms particle swarm optimizer(CmSPSO), which can cooperatively reinitialize a portion of particles in each swarm, which the distance between them is less than exclusive radius. Experiments have been made to demonstrate the simplicity and effectiveness, maintained the convergence and enhanced the diversity, and obtained the good effect at tracking the dynamic optima.