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Optimal acquisition policy in remanufacturing under general core quality distributions

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  • Cheng-Hu Yang
  • Jian Wang
  • Ping Ji

Abstract

The quality of acquirable used products (cores) is highly variable, which has made production planning and control of remanufacturing systems difficult. This paper studies an acquisition problem in presence of uncertain core quality. In order to derive optimal acquisition policy, the problem is formulated as a non-linear integer programming model in the framework of order statistics. The model is a strictly discrete convex problem with a unique global minimal solution. Then, a single bisection method is developed to obtain the optimal solution under a general continuous quality distribution. Moreover, the expressions of the optimal solution in some frequently used quality distributions are derived. Furthermore, the model is extended to the case of a general remanufacturing cost function, and corresponding results are presented. Finally, numerical experiments are conducted to test the effects of quality distribution, cost relationships of acquirable cores and remanufacturing cost function.

Suggested Citation

  • Cheng-Hu Yang & Jian Wang & Ping Ji, 2015. "Optimal acquisition policy in remanufacturing under general core quality distributions," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1425-1438, March.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:5:p:1425-1438
    DOI: 10.1080/00207543.2014.944283
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    Cited by:

    1. Byung Duk Song & Young Dae Ko, 2017. "Effect of Inspection Policies and Residual Value of Collected Used Products: A Mathematical Model and Genetic Algorithm for a Closed-Loop Green Manufacturing System," Sustainability, MDPI, vol. 9(9), pages 1-14, September.
    2. Senlin Zhao & Qinghua Zhu, 2017. "Remanufacturing supply chain coordination under the stochastic remanufacturability rate and the random demand," Annals of Operations Research, Springer, vol. 257(1), pages 661-695, October.
    3. Chen, Ke & Cheng, T.C.E. & Huang, Hailiang & Ji, Min & Yao, Danli, 2023. "Single-machine scheduling with autonomous and induced learning to minimize total weighted number of tardy jobs," European Journal of Operational Research, Elsevier, vol. 309(1), pages 24-34.
    4. Liao, Haolan & Zhang, Qingyu & Li, Lu, 2023. "Optimal procurement strategy for multi-echelon remanufacturing systems under quality uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).

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