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首页> 外文期刊>International journal of production economics >Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain
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Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain

机译：在需求不确定性下调查供应链网络设计的风险和稳健性措施：以玻璃供应链为例

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This paper addresses a multi-stage and multi-period supply chain network design problem in which multiple commodities should be produced through different subsequent levels of manufacturing processes. The problem is formulated as a two-stage stochastic program under stochastic and highly time variable demands. To deal with the stochastic demands, a Latin Hypercube Sampling method is applied to generate a fan of scenarios and then, a backward scenario reduction technique reduces the number of scenarios. Weighted mean-risk objectives by using different risk measures and minimax objective are examined to obtain risk-averse and robust solutions, respectively. Computational results are presented on a real-life case study to illustrate the applicability of the proposed approaches. To compare these different decision-making situations, a simulation approach is used. Furthermore, by several test problems, the performance of the stochastic model is investigated and the scenario generation method is evaluated in terms of in-sample and out-of-sample stability. Finally, sensitivity analysis on main parameters of the problem is performed to drive some managerial insights. (C) 2015 Elsevier B.V. All rights reserved.
机译：本文解决了一个多阶段，多周期的供应链网络设计问题，在该问题中，应通过不同的后续制造过程级别来生产多种商品。该问题被表述为具有随机和高时间可变需求的两阶段随机程序。为了应对随机需求，应用了拉丁超立方体采样方法来生成场景的粉丝，然后使用后向场景减少技术来减少场景的数量。通过使用不同的风险度量和最小最大目标对加权平均风险目标进行了检验，分别获得了规避风险和稳健的解决方案。计算结果在一个实际案例研究中给出，以说明所提出方法的适用性。为了比较这些不同的决策情况，使用了一种仿真方法。此外，通过几个测试问题，研究了随机模型的性能，并根据样本内和样本外的稳定性评估了方案生成方法。最后，对问题的主要参数进行敏感性分析以推动一些管理洞察力。 （C）2015 Elsevier B.V.保留所有权利。

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