Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP), to discuss the method to deal with uncertainty in a manufacturing system.\ud\udDesign/methodology/approach: In this paper, condition based maintenance (CBM), a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA) used in the previous article (Neale & Cameron,1979), an inserting algorithm (IA) is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.\ud\udFindings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM) is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.\ud\udOriginality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA) is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.
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机译:目的:本文重点研究运筹学中的经典优化问题,即柔性作业车间调度问题(FJSP),以讨论处理制造系统中不确定性的方法。\ ud \ udDesign / methodology / approach:本文中,建议进行基于状态的维护(CBM),这是一种预防性维护,可减少机器的不可用性。与前一篇文章(Neale&Cameron,1979)中使用的同时调度算法(SSA)不同,应用了插入算法(IA),其中首先通过启发式算法获得预调度,然后将维护任务插入\ ud \ udFindings:令人鼓舞的是,这项研究为FJSP基准中的实例获得了一个新的更好的解决方案。此外,实际上在文献中用于解决普通FJSPPM(带有PM的FJSP)中使用的SSA不适合于动态FJSPPM。通过在正常FJSPPM基准测试中的应用,发现IA虽然与文献中使用的SSA相比获得的效果较差,但执行速度却要好得多。\ ud \ ud原始值/值:与传统的FJSP调度不同,机器的不确定性考虑到这会增加问题的复杂性。提出了一种插入算法(IA)来解决动态调度问题。据指出,最终结果的质量在很大程度上取决于在解决正常FJSP过程中获得的预定时间表的质量。为了找到FJSP的最佳解决方案,对三种启发式算法进行了比较研究,综合GA,ACO和ABC。在比较研究中,我们发现GA在三种启发式算法中表现最佳。同时,本研究获得了一种针对FJSP基准测试实例的更好的新解决方案。
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