Research And Application On Job Shop Scheduling Based On Genetic Annealing Algorithm

Production scheduling is an important part of modern discrete manufacturing, and it can distribute resources reasonably to achieve optimal production goals. Reasonable production plan can improve utilization of machine and raw material, reduce production costs, and improve production efficiency. Therefore, how to obtain reasonable scheduling scheme quickly by computer algorithm has become a hot research.Firstly, Job Shop Scheduling Problem is deeply researched and the research situation both at home and abroad is introduced. On the basis, the mathematical model in order to minimize the maximum completion time is built. Basic processes, genetic operators, the advantages and disadvantages of genetic algorithm are introduced. Aimed at the premature convergence of genetic algorithm, simulated annealing algorithm is introduced and the new genetic annealing algorithm is proposed. In the new algorithm, crossover operators and mutation operators based on the job number are redesigned. Adaptive crossover probability and mutation probability are adopted. Metropolis criterions are introduced in each generation of genetic evolution. FT06 scheduling problem is simulated in the paper by means of genetic algorithm and simulated annealing algorithm and genetic annealing algorithm. The simulated results indicate that the new hybrid genetic algorithm can improve the searching efficiency and the satisfactory scheduling scheme is obtained.Secondly, emergent order and machine breakdown and order cancellation are three typical dynamic events, therefore it is necessary for the research of dynamic scheduling problem. The mathematical model of the dynamic job scheduling problem is established, in the combination of rolling window techniques, event-driven strategy is adopted. The dynamic job scheduling problem is solved by genetic annealing algorithm.Finally, in the application of bearing factory, the functional requirement of bearing factory is analyzed, and the function structure of job shop scheduling system is determined, and real-time data are obtained and entered into the database. The job shop scheduling optimized system based on genetic annealing algorithm is developed. The system is applied into the actual production, and good results are achieved, which demonstrate the effectiveness of the annealing algorithm.