A stochastic closed-loop supply chain network design problem with multiple recovery options

Zied Jemai (), Rim Jerbia, Mouna Kchaou Boujelben, Mohamed Sehli and Mohamed Amine Sehli
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Zied Jemai: LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec
Rim Jerbia: OASIS - Optimisation des systèmes industriels et de services [Tunis] - ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Tunis El Manar University [University of Tunis El Manar] [Tunisia] = Université de Tunis El Manar [Tunisie] = جامعة تونس المنار (ar)
Mouna Kchaou Boujelben: UAEU - United Arab Emirates University
Mohamed Sehli: OASIS - Optimisation des systèmes industriels et de services [Tunis] - ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Tunis El Manar University [University of Tunis El Manar] [Tunisia] = Université de Tunis El Manar [Tunisie] = جامعة تونس المنار (ar)

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Abstract: In this paper, a closed-loop supply chain network design problem with multiple recovery options is studied. First, the deterministic problem is formulated as a Mixed Integer Linear Program (MILP). A sensitivity analysis is carried out in order to investigate the impact of variations of the main input parameters such as customer return rates, revenues, costs as well as the proportions of returns assigned to each recovery option, on the network structure and the company profit. Then, a stochastic version of the model is developed to account for the high uncertainties faced by companies. A scenario-based approach is used to model the uncertainties of return rates, revenues, costs and the quality of returns. The computational results show that the solution of the stochastic problem is stable over different replications and that the benefit from using stochastic modeling increases when the penalty over non collected returns increases.

Keywords: Closed loop supply chain network design; Reverse logistics; Facility location; MILP; Two-stage stochastic program (search for similar items in EconPapers)
Date: 2018-04
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Citations: View citations in EconPapers (12)

Published in Computers & Industrial Engineering, 2018, 118, pp.23 - 32. ⟨10.1016/j.cie.2018.02.011⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01742193

DOI: 10.1016/j.cie.2018.02.011

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