瓶颈指向的启发式算法求解混合流水车间调度问题

Bottleneck Focused Heuristic Algorithm for Hybrid Flow Shop Scheduling Problem

  • 摘要: 针对以最小化时间表长为目标的复杂混合流水车间调度问题,提出了一种将机器布局和工件加工时间特征紧密结合的启发式算法. 首先,充分利用各阶段平均机器负荷一般不相等的特点确定瓶颈阶段,构建初始工件排序.其次,针对在瓶颈阶段前加工时间较短而瓶颈阶段后加工时间相对较长的工件,在第1阶段优先开始加工.同时,在瓶颈阶段前的每一个阶段,每当有工件等待加工或同时完工时, 优先选择瓶颈阶段前剩余加工时间最短的工件加工;在瓶颈阶段以及瓶颈阶段之后,则优先选择这台机器后剩余加工时间最长的工件加工. 最后,采用工件交换和插入操作改进初始调度.用Carlier和Neron的Benchmark算例测试提出的启发式算法.将计算结果与NEH启发式算法进行了比较,平均偏差降低了0.0555%, 表明这个启发式算法是有效的.

     

    Abstract: For the complex shop scheduling problem of hybrid flow shop with makespan minimization criterion, a heuristic algorithm cooperating the characters of machine configuration and job processing time intensively is proposed. Firstly, the bottleneck stage is identified using the character that the average processing time is not equal at every stage, and then an initial job sequence is constructed. Secondly, a job is given higher priority at the first stage when it takes shorter processing time before the bottleneck stage and longer processing time after the bottleneck stage. Meanwhile, at every stage before the bottleneck, if there are jobs waiting for processing or completed simultaneously, the priority is given to the job with shortest remain processing time before the bottleneck; at or after the bottleneck stage, it is given to the job with longest remaining processing time. Finally, pairwise interchange and insert operation are used to improve the initial scheduling. The performance of the proposed heuristic algorithm is tested using Carlier and Neron's benchmark problems. The computational results show that compared with the well-known NEH heuristic algorithm, the average deviation is reduced 0.0555%, which verifies the effectiveness of the proposed heuristic algorithm.

     

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