期刊
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 269, 期 1, 页码 313-326出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2017.07.020
关键词
Supply chain management; Closed-loop supply chain; Vector auto-regressive process; Order-up-to policy; Random yield
资金
- JSPS KAKENHI [25380475]
- Grants-in-Aid for Scientific Research [25380475] Funding Source: KAKEN
We investigate the dynamics of a closed-loop supply chain with first-order auto-regressive (AR(1)) demand and return processes. We assume these two processes are cross-correlated. The remanufacturing process is subject to a random triage yield. Remanufactured products are considered as-good-as-new and used to partially satisfy market demand; newly manufactured products make up the remainder. We derive the optimal linear policy in our closed-loop supply chain setting to minimise the manufacturer's inventory costs. We show that the lead-time paradox can emerge in many cases. In particular, the auto- and cross-correlation parameters and variances of the error terms in the demand and the returns, as well as the remanufacturing lead time, all influence the existence of the lead-time paradox. Finally, we propose managerial recommendations for manufacturers. (C) 2017 Elsevier B.V. All rights reserved.
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