Solve Job-shop Scheduling Problem Based on Cooperative Optimization

coping with such disadvantages of particle swarm optimization algorithm and GA as being easy to run into local optima, the method of cooperative optimization is proposed to solve the job shop scheduling problem by combing the quantum-behaved particle swarm optimization and GA. The algorithm applied the parallel hybrid architecture of collaborative quantum particle swarm and GA, in which a kind migration operator was designed to associate all population, and the result shows that this algorithm has better answers and more rapid convergence.