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

Kannan Govindan and Mohammad Fattahi

International Journal of Production Economics, 2017, vol. 183, issue PC, 680-699

Abstract: 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.

Keywords: Supply chain network design; Stochastic programming; Scenario reduction; Solution׳s robustness; Risk consideration; Simulation (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:183:y:2017:i:pc:p:680-699

DOI: 10.1016/j.ijpe.2015.09.033

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