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Integrated production scheduling and maintenance planning in a hybrid flow shop system: a multi-objective approach

机译:混合流水车间系统中的集成生产计划和维护计划:多目标方法

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This study deals with a hybrid flowshop system with sequence-dependent setup times. Two objectives have been considered. Minimizing makespan for production purpose along with minimizing unavailability of the system for maintenance purpose are the objectives of this problem. Two meta-heuristics have been developed for the research problem. First one is a non-dominated sorting genetic algorithm-II (NSGA-II), while the second one is a hybridized NSGA-II (HNSGA-H), which is accompanied by a local search procedure to create better results. These two algorithms allow the decision maker to find compromise solutions between production objectives and preventive maintenance ones. Two decisions should be taken at the same time: finding the best assignment and sequence of jobs on machines in order to minimize the makespan, and deciding how often to perform preventive maintenance actions in order to minimize the system unavailability. Three approaches have been suggested for evaluation and comparison the efficiency of algorithms. The results indicate that the HNSGA-H presents better solutions compared to the ordinal NSGA-II in terms of objective functions viewpoint, while the results are obviously reversed in balance degree of achieving both objectives simultaneously.
机译:这项研究涉及一个具有序列依赖的建立时间的混合流水车间系统。已经考虑了两个目标。这个问题的目的是使用于生产目的的制造期最小化以及使用于维护目的的系统的不可用性最小化。针对该研究问题已经开发了两种元启发式方法。第一个是非主导的排序遗传算法-II(NSGA-II),第二个是杂交的NSGA-II(HNSGA-H),它伴随着局部搜索过程以产生更好的结果。这两种算法使决策者可以在生产目标和预防性维护目标之间找到折衷的解决方案。应该同时做出两个决定:在机器上找到最佳的作业分配和顺序,以最大程度地缩短工期,并决定执行预防性维护操作的频率,以最大程度地减少系统不可用性。已经提出了三种方法来评估和比较算法的效率。结果表明,从目标函数的角度来看,HNSGA-H较序数NSGA-II提出了更好的解决方案,但同时实现两个目标的平衡度却明显相反。

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