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Optimizing combination of job shop scheduling and quadratic assignment problem through multi-objective decision making approach

机译:通过多目标决策方法优化作业车间调度与二次分配问题的组合

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In this paper, we consider job shop scheduling and machine location problem, simultaneously. Processing, transportation, and setup times are defined as deterministic parameters. The purpose of this paper is to determine machine location and job scheduling such that the make span and transportation cost is minimized. Therefore, the proposed model is a multi-objective problem one, where the first objective function minimizes make span and another minimizes the transportation cost. To solve the multi-objective problem, two methods are evaluated. Considering combination of job shop scheduling problem and machine location problem makes the proposed model more complex than job shop scheduling problem, which is an NP-hard problem. Therefore, to solve the proposed model, genetic algorithm as a meta-heuristic algorithm is implemented. To show the efficiency of the proposed genetic algorithm, 6×6 job shop scheduling problems are considered.
机译:在本文中,我们同时考虑了作业车间调度和机器位置问题。加工,运输和准备时间定义为确定性参数。本文的目的是确定机器的位置和作业计划,以使制造跨度和运输成本最小化。因此,所提出的模型是一个多目标问题,其中第一个目标函数使制造跨度最小,而另一个使运输成本最小化。为了解决多目标问题,评估了两种方法。考虑到车间调度问题和机器位置问题的结合,使得该模型比车间调度问题更为复杂,后者是一个NP难题。因此,为了解决所提出的模型,实现了遗传算法作为一种元启发式算法。为了显示所提出的遗传算法的效率,考虑了6×6作业车间调度问题。

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