Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/6118

On the time-consistent stochastic dominance risk averse measure for tactical supply chain planning under uncertainty


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Title:
On the time-consistent stochastic dominance risk averse measure for tactical supply chain planning under uncertainty
Authors:
Escudero, Laureano F.
Monge Ivars, Juan Francisco
Romero Morales, Dolores
Department:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Issue Date:
2017-07-15
Abstract:
In this work a modeling framework and a solution approach have been presented for a multi-period stochastic mixed 0–1 problem arising in tactical supply chain planning (TSCP). A multistage scenario tree based scheme is used to represent the parameters’ uncertainty and develop the related Deterministic Equivalent Model. A cost risk reduction is performed by using a new time-consistent risk averse measure. Given the dimensions of this problem in real-life applications, a decomposition approach is proposed. It is based on stochastic dynamic programming (SDP). The computational experience is twofold, a compar- ison is performed between the plain use of a current state-of-the-art mixed integer optimization solver and the proposed SDP decomposition approach considering the risk neutral version of the model as the subject for the benchmarking. The add-value of the new risk averse strategy is confirmed by the compu- tational results that are obtained using SDP for both versions of the TSCP model, namely, risk neutral and risk averse.
Keywords/Subjects:
Tactical supply chain planning
Nonlinear separable objective function
Multistage stochastic integer optimization
Risk management
Time-consistency
Stochastic nested decomposition
Type of document:
application/pdf
Access rights:
info:eu-repo/semantics/openAccess
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