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• W2810322311 abstract "In this study, we investigate a closed-loop supply chain model consisting of a manufacturer and a retailer. The retailer orders items from the manufacturer to satisfy the end customer's demand. The manufacturer uses both regular production and remanufacturing processes to produce items to fulfill the demand from the retailer. The returned items are collected and screened by the manufacturer for recovering process. We consider learning process in regular production and remanufacturing processes. In addition, the imperfect items produced during regular production are reworked. The model contributes to the current literature by allowing the inclusion of learning process in regular production and remanufacturing processes, imperfect items, rework and multiple cycle policy. Our objective is to optimise the percentage of the used item purchasing price per raw material cost, retailer ordering cycle, number of regular production cycles and the number of remanufacturing cycles, so that the joint expected total annual profit incurred has a minimum value. Furthermore, an algorithm is proposed to find the solutions of the proposed model. We also provide a numerical example and perform a sensitivity analysis to illustrate the model's behaviour and feasibility." @default.
• W2810322311 created "2018-07-10" @default.
• W2810322311 creator A5024024185 @default.
• W2810322311 creator A5036394992 @default.
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• W2810322311 date "2018-01-01" @default.
• W2810322311 modified "2023-09-27" @default.
• W2810322311 title "Inventory decisions in a closed-loop supply chain system with learning and rework" @default.
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• W2810322311 doi "https://doi.org/10.1504/ijpm.2018.10014395" @default.
• W2810322311 hasPublicationYear "2018" @default.
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