The risk-aware multi-period capacitated plant location problem (CPLP-Risk)

Heckmann, Iris, Stefan Nickel, Francisco Saldanha-da-Gama
Int Conf Inf Syst Log Supp Chain
Unexpected deviations and disruptions - subsumed under the notion of supply chain risk - increasingly aggravate the planning and optimization of supply chains. Over the last decade there has been a growing interest in including risk aspects for supply chain optimization models. This development has led to the adoption of risk concepts, terminologies and methods defined and applied in a broad variety of related research fields and methodologies. In Heckmann et al. 2015 the core characteristics of supply chain risk have been identified. Based on contemporary research gaps identified in Heckmann et al. 2015 for optimization approaches we introduce a mixed-integer two-stage stochastic programming model that extends the capacitated plant location problem and additionally offers the possibility to formalize and operationalize supply chain risk. The evaluation of the developed optimization model discloses its usefulness in terms of providing risk-aware solutions and of approaching risk by stochastic programming.
Logistik und Supply-Chain-Optimierung
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