Science and Technology Production
Book Chapter
Authorship
L.J. Zeballos
;
C.A. Méndez
;
A.P. Barbosa-Povoa
;
A. Novais
Date
2013
Publishing House and Editing Place
University of Calabria
Book
Proceedings of the international Workshop on Innovation for Logistics
(pp. 6-14)
University of Calabria
University of Calabria
ISBN
978-88-97999-30-0
Summary
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In this paper, a robust multi-stage stochastic programming approach is proposed for addressing the design and planning of multi-period, multi-product Closed-Loop Supply Chains (CLSCs) with uncertainty in supply and customer demands. Adjustments in the supply chain structure are allowed during the planning horizon providing flexibility to the network. Aspects related to operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution a...
In this paper, a robust multi-stage stochastic programming approach is proposed for addressing the design and planning of multi-period, multi-product Closed-Loop Supply Chains (CLSCs) with uncertainty in supply and customer demands. Adjustments in the supply chain structure are allowed during the planning horizon providing flexibility to the network. Aspects related to operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution and storage are also addressed. The effects of the uncertainty are considered by means of multiple scenarios. The objective is to find per period the optimal decisions related to the facility location, the average and variability of operational costs, as well as the revenue due to the amount of used products returned to the forward network. The effectiveness of the proposed approach is established by means of several case studies. A scenario reduction algorithm is applied in order to maintain within a manageable model size the complex case studies addressed.
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Key Words
StochasticRobust optimizationClose loop SC