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A linearisation approach to the stochastic dynamic capacitated lotsizing problem with sequence-dependent changeovers

机译:依赖序列依赖性转换的随机动态电容量化问题的线性化方法

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We present a mixed-integer linear programming formulation that simultaneously optimises lot sizes and production sequences on a capacity constrained machine with sequence-dependent changeovers subject to stochastic dynamic demand while at the same time satisfying a fill rate constraint. To tackle the non-linearity of the exact formulation, we introduce a piecewise linearisation technique both for the expected inventory on hand and for the backorder functions that uses the target service level and the parameters of the demand distribution to assign breakpoints to the most promising intervals of the linearisation domain. We show that our strategy leads to lower cost and to more conservative production plans, in comparison to techniques recommended by earlier research. In addition, we discuss why any breakpoint selection strategy that does not exclude the concave region for , is prone to be outperformed by the approach we present. Finally, we propose a Relax-and-Fix with Fix-and-Optimize heuristic, and show based on the broad set of instances from Haase, Knut, and Alf Kimms [2000. "Lot sizing and scheduling with sequence-dependent setup costs and times and efficient rescheduling opportunities." International Journal of Production Economics 66 (2): 159-169], that it is more effective than a state-of-the-art solver in terms of run time and solution quality.
机译:我们介绍了一种混合整数线性编程配方,同时在容量受限机器上同时优化批次尺寸和生产序列,其中依赖于依赖于随机动态需求,同时满足填充率约束。为了解决精确配方的非线性,我们引入都为手头上的预期的库存和使用目标服务水平和需求分布来分配断点最有前途的间隔的参数缺货功能的分段线性化技术线性化域。我们表明,与早期研究推荐的技术相比,我们的战略导致成本更低,更保守的生产计划。此外,我们讨论为什么任何不排除凹形区域的断点选择策略都容易被我们所呈现的方法所表现出来的。最后,我们提出了一种放松和修复的修复和优化启发式,并基于来自HAASE,KNUT和ALF KIMMS的广泛的情况显示[2000。 “用序列依赖的设置成本和时间和高效重新安排机会进行尺寸和调度。”国际生产经济学杂志66(2):159-169],在运行时间和解决方案质量方面比最先进的求职者更有效。

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