基于PetriNets和混合遗传算法的双资源JSP动态优化调度

以带有控制器的Petri网为建模工具对柔性生产调度中的离散事件建模,利用遗传算法和模拟退火算法获得调度结果,并通过Petri网进行控制.用于解决作业车间的加工受到机床、操作工人等生产资源制约条件下的优化调度.以生产周期为目标进行的优化调度,将遗传算法和模拟退火相结合.通过多种交叉、变异、概率更新选择、再分配策略等遗传和模拟操作,得到目标的最优或次优解.对算法进行了仿真研究,仿真结果表明该算法是有效性.

Petri nets and genetic algorithm based approach for dynamic scheduling optimization of dual-resources

A Petri net with controller was used to model discrete events in flexible job shop scheduling,the scheduling results was obtained based on genetic and simulated annealing algorithm,and the model was controlled with the Petri net;The method is developed to address the scheduling problem in manufacturing systems constrained by machines,workers.The objective of scheduling problems is to minimize makes-pan,the algorithms combining with genetic and simulated annealing algorithms is used.After using crossover,mutation,probabilistic updating strategy and re-assignment strategy and so on genetic and simulated operation,a best or second best scheduling plan can be found.Simulation results based on some flow shop scheduling show that the GASA is feasible,efficient.