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Periodic review, push inventory policies for remanufacturing

Author

Listed:
  • Mahadevan, B.
  • Pyke, David F.
  • Fleischmann, Moritz

Abstract

Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. This research is focused on product recovery, and in particular on production control and inventory management in the remanufacturing context. We study a remanufacturing facility that receives a stream of returned products according to a Poisson process. Demand is uncertain and also follows a Poisson process. The decision problems for the remanufacturing facility are when to release returned products to the remanufacturing line and how many new products to manufacture. We assume that remanufactured products are as good as new. In this paper, we employ a "push" policy that combines these two decisions. It is well known that the optimal policy parameters are difficult to find analytically; therefore, we develop several heuristics based on traditional inventory models. We also investigate the performance of the system as a function of return rates, backorder costs and manufacturing and remanufacturing lead times; and we develop approximate lower and upper bounds on the optimal solution. We illustrate and explain some counter-intuitive results and we test the performance of the heuristics on a set of sample problems. We find that the average error of the heuristics is quite low.
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Suggested Citation

  • Mahadevan, B. & Pyke, David F. & Fleischmann, Moritz, 2003. "Periodic review, push inventory policies for remanufacturing," European Journal of Operational Research, Elsevier, vol. 151(3), pages 536-551, December.
  • Handle: RePEc:eee:ejores:v:151:y:2003:i:3:p:536-551
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    1. McGee, Victor E. & Pyke, David F., 1996. "Periodic production scheduling at a fastener manufacturer," International Journal of Production Economics, Elsevier, vol. 46(1), pages 65-87, December.
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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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