Cooperative Compounded Particle Swarm Optimization and application

In real-time high dimensions optimization problem, how to quickly find the optimal solution and give timely response or decisive adjustment is very important. Inspired by the mutual parasitic behaviors, this paper suggests a new PSO variant, Cooperative Compounded Particle Swarm Optimization (COMPSO) that improves the convergence speed and reduces the possibility of particles into the local optimum. By using of real encoding mechanism, COMPSO is applied to the vehicle routing problem. Compared with other PSO algorithms, experimental results show the superiority of COMPSO algorithm in terms of the solution quality and computational efficiency. It proves a helpful guiding significance.