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A flexibly structured lot sizing heuristic for a static remanufacturing system

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  • Schulz, Tobias
  • Voigt, Guido

Abstract

An effective planning of lot sizes is a key strategy to efficiently manage a combined manufacturing/remanufacturing system in the presence of substantial setup costs. Due to its complex interdependencies, optimal policies and solutions have not been identified so far, but several heuristic approaches have been analyzed in recent contributions. The main heuristic shortcuts are forcing equally sized lot sizes over the planning horizon as well as imposing a specific cycle structure, i.e., a sequence of manufacturing batches is followed by a sequence of remanufacturing batches. We are instead proposing a flexibly structured heuristic that allows for differently sized remanufacturing batches. We show in a comprehensive numerical study that our approach outperforms other existing approaches in more than half of all instances by up to 17%.

Suggested Citation

  • Schulz, Tobias & Voigt, Guido, 2014. "A flexibly structured lot sizing heuristic for a static remanufacturing system," Omega, Elsevier, vol. 44(C), pages 21-31.
    • Handle: RePEc:eee:jomega:v:44:y:2014:i:c:p:21-31
    DOI: 10.1016/j.omega.2013.09.003
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    References listed on IDEAS

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    Cited by:

    1. Pilar I. Vidal-Carreras & Jose P. Garcia-Sabater & Julio J. Garcia-Sabater, 2017. "A practical model for managing inventories with unknown costs and a budget constraint," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 118-129, January.
    2. Bimal Kumar Mawandiya & J. K. Jha & Jitesh J. Thakkar, 2020. "Optimal production-inventory policy for closed-loop supply chain with remanufacturing under random demand and return," Operational Research, Springer, vol. 20(3), pages 1623-1664, September.
    3. Voigt, Guido & Schulz, Tobias, 2015. "Note on “Heuristics with guaranteed performance bounds for a manufacturing system with product recovery”," European Journal of Operational Research, Elsevier, vol. 241(2), pages 575-578.
    4. Feng Tao & Tijun Fan & Xuefeng Jia & Kin Keung Lai, 2021. "Optimal production strategy for a manufacturing and remanufacturing system with return policy," Operational Research, Springer, vol. 21(1), pages 251-271, March.
    5. Yu-Chung Tsao & Vu-Thuy Linh & Jye-Chyi Lu & Vincent Yu, 2018. "A supply chain network with product remanufacturing and carbon emission considerations: a two-phase design," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 693-705, March.
    6. Kozlovskaya, Nadezhda & Pakhomova, Nadezhda & Richter, Knut, 2015. "Complete solution of the extended EOQ repair and waste disposal model with switching costs," Discussion Papers 376, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    7. Hariga, Moncer & As’ad, Rami & Khan, Zeinab, 2017. "Manufacturing-remanufacturing policies for a centralized two stage supply chain under consignment stock partnership," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 362-374.
    8. Mitra, Subrata, 2016. "Models to explore remanufacturing as a competitive strategy under duopoly," Omega, Elsevier, vol. 59(PB), pages 215-227.
    9. Yonit Barron, 2024. "Shortage Policies for a Jump Process with Positive and Negative Batch Arrivals in a Random Environment," Mathematics, MDPI, vol. 12(9), pages 1-30, April.
    10. Kozlovskaya, Nadezhda & Pakhomova, Nadezhda & Richter, Knut, 2016. "A general production and recovery EOQ model with stationary demand and return rates," Discussion Papers 378, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    11. Hong Sun & Yan Li, 2023. "Optimal Acquisition and Production Policies for Remanufacturing with Quality Grading," Mathematics, MDPI, vol. 11(7), pages 1-21, March.

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