Optimal Control of Inventory Systems with Multiple Types of Remanufacturable Products
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AbstractProduct returns have become a significant feature of many manufacturing systems. Because products are returned under different operational conditions, they usually require different remanufacturing effort/costs. Motivated by a project with a major energy company that manages its inventory through options of ordering and remanufacturing returned products (cores) in various condition, in this paper, we study a single-product, periodic-review inventory system with multiple types of cores. The serviceable products used to fulfill stochastic customer demand can be either manufactured from new parts or remanufactured from the cores, and the objective is to minimize the expected total discounted cost over a finite planning horizon. We show that the optimal manufacturing remanufacturing disposal policy has a simple structure and can be completely characterized by a sequence of constant control parameters when manufacturing and remanufacturing leadtimes are the same. To demonstrate the value of the optimal policy, we conduct a numerical study that compares its performance with two simple heuristics, namely, pull policy without and with sorting. The results show that the reduction in system cost by using the optimal policy can be significant. When manufacturing and remanufacturing leadtimes are different, we develop a heuristic method for computing the near-optimal control policy that performs quite well as demonstrated numerically.
All Author(s) ListZhou SX, Tao ZJ, Chao XL
Journal nameManufacturing and Service Operations Management
Volume Number13
Issue Number1
PublisherINFORMS (Institute for Operations Research and Management Sciences)
Pages20 - 34
LanguagesEnglish-United Kingdom
Keywordsbase-stock policies; inventory system; optimal manufacturing and remanufacturing strategies; product returns; remanufacturing; reverse logistics
Web of Science Subject CategoriesBusiness & Economics; Management; MANAGEMENT; Operations Research & Management Science; OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Last updated on 2021-14-01 at 00:05