The Research Of Job Shop Scheduling Problem Based On Particle Swarm Optimization Algorithm

Scheduling Problem is a key part of production management and control for enterprise. An optimum Scheduling is help for enterprise to strengthen its efficiency and competition. Research and exploring in this subject has important academic significance and practical significance.In this paper, first, the purpose and characteristic of the scheduling problem is discussed, the trend of the domestic and overseas research of scheduling problem and prevalent models and methods are analyzed. Second, the origin and basic theory of the particle swarm optimization algorithm are presented, the fresh analysis conclusion and renovation of the algorithm are summarized, and quantum particle swarm optimization algorithm is also introduced. Third, the particle swarm optimization algorithm and the quantum particle swarm optimization algorithm are applied to the job-shop scheduling problem. In order to resolve the flaw of the quantum particle swarm optimization algorithm that it is easily trapped into local optimization, the paper puts forward the hybrid algorithm which blends the QPSO algorithm and simulated annealing algorithm. The hybrid algorithm could escape from local optima and has good global search ability. The simulation results show that the hybrid algorithm has good global convergence ability. Finally, a scheduling management system is designed and developed.