【摘要】 在批量生产柔性作业车间调度问题中,不但要考虑路径选取和加工排序两个子问题,而且工件还可被分割为多个子批量,不同子批可选择不同工艺路线。该问题是对传统柔性作业车间调度问题(FJSP)的扩充,它更接近于实际生产调度问题。针对问题的特点,提出了一种基于遗传算法的柔性分批调度算法。在算法中,提出了一种基于"游标"的柔性批量分割方法,并采用一种批量分割与加工工序相融合的染色体编码方法。该算法不但可根据机床负荷将工件分割成具有柔性批量的多个子批,而且可使子批工艺路线选取及加工排序同时得到优化。通过实例仿真,对算法性能进行分析和评价,结果表明了算法的有效性和可行性。更多还原

【Abstract】 In batch production flexible job-shop scheduling problem,the routing and sequencing sub-problems are taken into account,and a job lot can be split into a number of sub-lots and different sub-lots of the same job can be processed on distinct machines.This problem is an extension of classic flexible job-shop scheduling problem(FJSP),which provides a closer approximation to real scheduling problems.According to the characteristics of the problem,a novel flexible size lot-splitting scheduling algorithm based on genetic algorithm was put forward.In the algorithm,a flexible size lot-splitting approach based on "cursors" was proposed.Combined the lot-splitting and the sub-lot scheduling,a novel chromosome coding scheme was put forward,so that the algorithm can be used to split job lots into flexible size sub-lots according to machine workloads,and optimize the sub-lots routing and sequencing simultaneously.The performance of the proposed algorithm was evaluated through simulations,and the results demonstrate the feasibility and efficiency of the algorithm.更多还原