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A master production scheduling procedure for stochastic demand and rolling planning horizons

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  • Vargas, Vicente
  • Metters, Richard

Abstract

The problem of interest is a one product, uncapacitated master production schedule (MPS) in which decisions are made under rolling planning horizons. Demand is stochastic and time varying, and effectiveness is measured by inventory holding, production setup, and backorder costs. Typically, in both the research literature and the business practice the stochastic nature of the problem is modeled in an ad hoc fashion. The stochastic MPS problem is usually solved by adding safety stock to production quantities obtained from a deterministic lot-sizing algorithm. Here, the stochastic nature of the problem is explicitly considered, as an optimal algorithm for solving the static probabilistic dynamic lot-sizing problem is adapted to rolling planning horizons. The resulting algorithm is found to dominate traditional approaches over a wide variety of experimental factors, reducing total costs by an average of 16% over traditional methods.

Suggested Citation

  • Vargas, Vicente & Metters, Richard, 2011. "A master production scheduling procedure for stochastic demand and rolling planning horizons," International Journal of Production Economics, Elsevier, vol. 132(2), pages 296-302, August.
    • Handle: RePEc:eee:proeco:v:132:y:2011:i:2:p:296-302
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    References listed on IDEAS

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    Cited by:

    1. Gansterer, Margaretha, 2015. "Aggregate planning and forecasting in make-to-order production systems," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 521-528.
    2. de Sampaio, Raimundo J.B. & Wollmann, Rafael R.G. & Vieira, Paula F.G., 2017. "A flexible production planning for rolling-horizons," International Journal of Production Economics, Elsevier, vol. 190(C), pages 31-36.
    3. Fateme Akhoondi & M.M. Lotfi, 2016. "A heuristic algorithm for master production scheduling problem with controllable processing times and scenario-based demands," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3659-3676, June.
    4. Brahimi, Nadjib & Absi, Nabil & Dauzère-Pérès, Stéphane & Nordli, Atle, 2017. "Single-item dynamic lot-sizing problems: An updated survey," European Journal of Operational Research, Elsevier, vol. 263(3), pages 838-863.
    5. Lee, Shine-Der & Lan, Shu-Chuan, 2013. "Production lot sizing with a secondary outsourcing facility," International Journal of Production Economics, Elsevier, vol. 141(1), pages 414-424.
    6. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    7. Gahm, Christian & Dünnwald, Bastian & Sahamie, Ramin, 2014. "A multi-criteria master production scheduling approach for special purpose machinery," International Journal of Production Economics, Elsevier, vol. 149(C), pages 89-101.

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