Title: Optimisation of supply chain networks under uncertainty: conditional value at risk approach

Authors: Reza Babazadeh; Ali Sabbaghnia

Addresses: Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract: Supply chain network design is one of the strategic level decisions related to supply chain management and optimal determination of its decisions assures responsiveness of the supply chain. The important parameters of the supply chain network design problem are uncertain ones due to the strategic nature of the problem. Therefore, to determine optimal and robust decisions in supply chain network design problem, it is essential to employ efficient risk and uncertainty management tools. Conditional value at risk (CVaR) and robust stochastic programming approaches are two efficient tools to deal with uncertainty. In this paper, first, modelling of these two approaches in a supply chain network design problem is presented and then their performances are evaluated and compared under uncertainty. The case study of this study includes supply chain network design of a medium-density fibreboard (MDF) industry. Results show that the CVaR model provides solutions with higher degree of robustness compared to the robust stochastic programming approach.

Keywords: supply chain network design; SCND; uncertainty; conditional value at risk; CVaR; robust stochastic programming.

DOI: 10.1504/IJMDM.2018.095736

International Journal of Management and Decision Making, 2018 Vol.17 No.4, pp.488 - 508

Available online: 10 Oct 2018 *

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