Stochastic approaches for product recovery network design: a case study
AbstractIncreased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present stochastic programming based approaches by which a deterministic location model for product recoverynetwork design may be extended to explicitly account for the uncertainties. Such a stochastic model seeks a solution which is appropriately balanced between some alternative scenarios identified by field experts. We apply the stochastic models to a representative real case study on recycling sand from demolition waste in The Netherlands. The interpretation of the results is meant to give more insight into decision-making for reverse logistics.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2001-08.
Date of creation: 20 Mar 2001
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Location; Reverse logistics; Uncertainty; Stochastic programming;
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- Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
- Fleischmann, M., 2001. "Reverse Logistics Network Structures and Design," Research Paper ERS-2001-52-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
- Salema, Maria Isabel Gomes & Barbosa-Povoa, Ana Paula & Novais, Augusto Q., 2007. "An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1063-1077, June.
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