Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain

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• 作者：Kannan Govindan^a ; ^{gov@sam.sdu.dk} ; Mohammad Fattahi^a ; ^b ; ^c
• 关键词：Supply chain network design ; Stochastic programming ; Scenario reduction ; Solution׳s robustness ; Risk consideration ; Simulation
• 刊名：International Journal of Production Economics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：183
• 期：part_PC
• 页码：680-699
• 全文大小：1251 K
• 卷排序：183

文摘

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.