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Keywords = the remanufacturer’s capacity uncertainty

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20 pages, 744 KiB  
Article
Does a Buyback Contract Coordinate a Reverse Supply Chain Facing Remanufacturing Capacity Disruption and Returned Product Quality Uncertainty?
by Mehr Sadat Salami, Mohammadreza Eslamipirharati, Alireza Bakhshi, Amir Aghsami, Fariborz Jolai and Maziar Yazdani
Sustainability 2022, 14(23), 15939; https://doi.org/10.3390/su142315939 - 29 Nov 2022
Cited by 12 | Viewed by 3444
Abstract
This paper studies a two-echelon reverse supply chain (RSC) involving a remanufacturer and a collector, in which the collector receives the used products by paying a reward to consumers. The reward amount given to customers is crucial for encouraging them to exchange used [...] Read more.
This paper studies a two-echelon reverse supply chain (RSC) involving a remanufacturer and a collector, in which the collector receives the used products by paying a reward to consumers. The reward amount given to customers is crucial for encouraging them to exchange used products. An exchanged item is accepted if it meets the minimum acceptable quality level (AQL). Both the remanufacturing capacity and the quality of exchanged products present uncertainties. Under the buyback contract, the remanufacturer purchases used products at a higher price than in the decentralized and centralized cases from the collector. In return, the collector undertakes to repurchase a certain number of used products sold to the remanufacturer, but not remanufactured due to capacity shortages. Based on the aforementioned uncertainties, this study analyses channel coordination using buyback contracts and optimizes its parameters. By conducting a numerical analysis, we first ensure that under this contract, the risk of uncertainty is divided among the members, and that each party’s profit is higher than when decisions are made individually. Therefore, a buyback contract would guarantee a win-win situation for both of the parties, and coordination for the RSC. A range of percentages of extra items purchased by collectors is derived, as well as the amount the collector pays for each item and the effect of increasing or decreasing these values is examined. Full article
(This article belongs to the Special Issue Logistics and Operations Modelling and Optimisation for Sustainable Supply Chain)
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21 pages, 998 KiB  
Article
Accelerated Benders’ Decomposition for Integrated Forward/Reverse Logistics Network Design under Uncertainty
by Vahab Vahdat and Mohammad Ali Vahdatzad
Logistics 2017, 1(2), 11; https://doi.org/10.3390/logistics1020011 - 9 Dec 2017
Cited by 5 | Viewed by 6292
Abstract
In this paper, a two-stage stochastic programming modelling is proposed, to design a multi-period, multistage, and single-commodity integrated forward/reverse logistics network design problem under uncertainty. The problem involved both strategic and tactical decision levels. The first stage dealt with strategic decisions, which are [...] Read more.
In this paper, a two-stage stochastic programming modelling is proposed, to design a multi-period, multistage, and single-commodity integrated forward/reverse logistics network design problem under uncertainty. The problem involved both strategic and tactical decision levels. The first stage dealt with strategic decisions, which are the number, capacity, and location of forward and reverse facilities. In the second stage, tactical decisions, such as base stock level as an inventory policy, were determined. The generic introduced model consisted of suppliers, manufactures, and distribution centers in forward logistic and collection centers, remanufactures, redistribution, and disposal centers in reverse logistic. The strength of the proposed model is its applicability to various industries. The problem was formulated as a mixed-integer linear programming model and was solved by using Benders’ Decomposition (BD) approach. In order to accelerate the Benders’ decomposition, a number of valid inequalities were added to the master problem. The proposed accelerated BD was evaluated through small-, medium-, and large-sized test problems. Numerical results confirmed that the proposed solution algorithm improved the convergence of BD lower bound and the upper bound, enabling to reach an acceptable optimality gap in a convenient time. Full article
(This article belongs to the Section Sustainable Supply Chains and Logistics)
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