Optimization algorithm combines artificial life system with particle swarm optimization

An optimization algorithm that combines artificial life system with particle swarm optimization (PSO) is proposed. This algorithm includes two stages. In the first stage, artificial life system is created. As artificial life organisms have a sensing system, they can find the resource they want and metabolize it. The micro-interaction with each other in the artificial life's group results in emergent colonization in the whole system. The emergent colonization of artificial life system is used to provide better position of initial population for PSO. And PSO is further used to find the optimal solution in the second stage. In the end, a well-known test function (Rosenbrock) is given to verify the optimizing ability of this proposed algorithm. The numerical result shows that the proposed algorithm is effective.