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Integrated production planning and scheduling under uncertainty: A fuzzy bi-level decision-making approach

机译:不确定性下的综合生产规划和调度:模糊双层决策方法

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Production planning and scheduling are two core decision layers, constrained and affected by one another in manufacturing systems. Owing to different time scales and objectives, planning and scheduling are often separately handled in a sequential way, which frequently results in infeasible or suboptimal solutions. Moreover, uncertain issues, e.g. the fuzzy startup time of a machine and the fuzzy processing time for a task, are inherent to manufacturing systems due to mechanized and/or man-made factors. Motivated by these challenges, this paper aims to develop fuzzy bi-level decision-making techniques to handle integrated planning and scheduling problems in the fuzzy manufacturing system. First, the integrated problem is formulated into a fuzzy bi-level decision model in which solving the higher-level planning problem has to take into account lower-level implicit scheduling reactions in advance. Second, a hybrid solution method is developed to solve the resulting bi-level decision model, in which a particle swarm optimization (PSO) algorithm is applied to update planning decisions, and then, in view of each given planning decision, a heuristic algorithm is presented to find an optimal schedule under fuzzy manufacturing conditions. Lastly, a set of computational study is constructed to demonstrate the effectiveness of the proposed fuzzy bi-level decision-making techniques. Compared with existing works, they can find better planning decisions fulfilled by schedules and perform much better in terms of computational efficiency. (C) 2020 Elsevier B.V. All rights reserved.
机译:生产计划和调度是两个核心决策层,受到制造系统中彼此的约束和影响。由于不同的时间尺度和目标,规划和调度通常以顺序方式单独处理,这通常会导致不可行或次优的解决方案。此外,不确定的问题,例如,由于机械化和/或人造因子,机器的模糊启动时间和任务的模糊处理时间是由制造系统固有的。这些挑战的激励,本文旨在开发模糊的双层决策技术,以处理模糊制造系统中的综合规划和调度问题。首先,将综合问题制定为模糊的双级决策模型,其中解决了更高级别的规划问题必须提前考虑较低级隐式调度反应。其次,开发了一种混合解决方法以解决所得到的双级决策模型,其中应用于更新规划决策的粒子群优化(PSO)算法,然后,考虑到每个给定的规划决策,启发式算法是提出在模糊制造条件下找到最佳的时间表。最后,构建了一组计算研究以证明所提出的模糊双级决策技术的有效性。与现有作品相比,他们可以找到按照时间表实现的更好的规划决策,并在计算效率方面表现更好。 (c)2020 Elsevier B.v.保留所有权利。

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