Optimal Procurement in Remanufacturing Systems with Uncertain Used-Item Condition

成果类型:
Article
署名作者:
Nadar, Emre; Akan, Mustafa; Debo, Laurens; Scheller-Wolf, Alan
署名单位:
Ihsan Dogramaci Bilkent University; Carnegie Mellon University; Dartmouth College
刊物名称:
OPERATIONS RESEARCH
ISSN/ISSBN:
0030-364X
DOI:
10.1287/opre.2023.2483
发表日期:
2023
页码:
1441-1453
关键词:
loop supply chains to-stock system inventory systems product acquisition assembly system optimal policy order system returns management QUALITY
摘要:
We consider a single-product remanufacture-to-order system with multiple uncertain quality levels for used items, random procurement lead times, and lost sales. The quality level of a used item is revealed only after it is acquired and inspected; the remanufacturing cost is lower for a higher-quality item. We model this system as a Markov decision process and seek an optimal policy that specifies when a used item should be procured, whether an arriving demand for the remanufactured product should be satisfied, and which available item should be remanufactured to meet this demand. We characterize the optimal procurement policy as following a new type of strategy: state-dependent noncongestive acquisition. This strategy makes decisions, taking into account the system congestion level measured as the number of available items and their quality levels. We also show that it is always optimal to meet the demand with the highest-quality item among the available ones. We conclude with extensions of our model to limited cases when the used-item condition is known a priori (for two quality levels) and remanufacture-to-stock systems in which the standard push strategy is optimal in the remanufacturing stage.
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