Stochastic Programming for Supply Chain Planning Under Demand Uncertainty

ManMohan S. Sodhi and Christopher S. Tang
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ManMohan S. Sodhi: City University
Christopher S. Tang: University of California, Los Angeles

Chapter Chapter 15 in Managing Supply Chain Risk, 2012, pp 259-277 from Springer

Abstract: Abstract In this chapter we focus on stochastic programming for making optimal supply chain planning decisions under uncertainty. In particular, we extend deterministic linear programming for supply-chain planning (SCP) by using stochastic programming to incorporate the issues of demand risk and liquidity risk. Because the resulting stochastic linear programming model is similar to that of Asset-Liability Management (ALM) and because the literature using stochastic programming for ALM is extensive, we survey various modeling and solution choices developed in this literature and discuss their applicability to supply chain planning. This survey forms a basis for making modeling/solution choices in research and in practice to manage the risks of unmet demand, excess inventory and inadequate cash liquidity when demand is uncertain.

Keywords: Stochastic Program; Demand Uncertainty; Liquidity Risk; Demand Scenario; Unmet Demand (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-3238-8_15

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