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A polynomial time algorithm to solve the single-item capacitated lot sizing problem with minimum order quantities and concave costs

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  • Hellion, Bertrand
  • Mangione, Fabien
  • Penz, Bernard

Abstract

This paper deals with the single-item capacitated lot sizing problem with concave production and storage costs, and minimum order quantity (CLSP-MOQ). In this problem, a demand must be satisfied at each period t over a planning horizon of T periods. This demand can be satisfied from the stock or by a production at the same period. When a production is made at period t, the produced quantity must be greater to than a minimum order quantity (L) and lesser than the production capacity (U). To solve this problem optimally, a polynomial time algorithm in O(T5) is proposed and it is computationally tested on various instances.

Suggested Citation

  • Hellion, Bertrand & Mangione, Fabien & Penz, Bernard, 2012. "A polynomial time algorithm to solve the single-item capacitated lot sizing problem with minimum order quantities and concave costs," European Journal of Operational Research, Elsevier, vol. 222(1), pages 10-16.
  • Handle: RePEc:eee:ejores:v:222:y:2012:i:1:p:10-16
    DOI: 10.1016/j.ejor.2012.04.024
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    References listed on IDEAS

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    Cited by:

    1. Ou, Jinwen, 2017. "Improved exact algorithms to economic lot-sizing with piecewise linear production costs," European Journal of Operational Research, Elsevier, vol. 256(3), pages 777-784.
    2. 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.
    3. Muriel, Ana & Chugh, Tammana & Prokle, Michael, 2022. "Efficient algorithms for the joint replenishment problem with minimum order quantities," European Journal of Operational Research, Elsevier, vol. 300(1), pages 137-150.
    4. Chung-Lun Li & Qingying Li, 2016. "Polynomial-Time Solvability of Dynamic Lot Size Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(03), pages 1-20, June.
    5. Hong, Zhaofu & Chu, Chengbin & Yu, Yugang, 2016. "Dual-mode production planning for manufacturing with emission constraints," European Journal of Operational Research, Elsevier, vol. 251(1), pages 96-106.
    6. Hnaien, Faicel & Afsar, Hasan Murat, 2017. "Robust single-item lot-sizing problems with discrete-scenario lead time," International Journal of Production Economics, Elsevier, vol. 185(C), pages 223-229.
    7. Archetti, Claudia & Bertazzi, Luca & Grazia Speranza, M., 2014. "Polynomial cases of the economic lot sizing problem with cost discounts," European Journal of Operational Research, Elsevier, vol. 237(2), pages 519-527.
    8. Stefano Coniglio & Arie M. C. A. Koster & Nils Spiekermann, 2018. "Lot sizing with storage losses under demand uncertainty," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 763-788, October.
    9. Ou, Jinwen & Feng, Jiejian, 2019. "Production lot-sizing with dynamic capacity adjustment," European Journal of Operational Research, Elsevier, vol. 272(1), pages 261-269.
    10. Zhu, Han & Liu, Xing & Chen, Youhua (Frank), 2015. "Effective inventory control policies with a minimum order quantity and batch ordering," International Journal of Production Economics, Elsevier, vol. 168(C), pages 21-30.
    11. Absi, Nabil & Dauzère-Pérès, Stéphane & Kedad-Sidhoum, Safia & Penz, Bernard & Rapine, Christophe, 2016. "The single-item green lot-sizing problem with fixed carbon emissions," European Journal of Operational Research, Elsevier, vol. 248(3), pages 849-855.
    12. Perera, Sandun & Janakiraman, Ganesh & Niu, Shun-Chen, 2017. "Optimality of (s, S) policies in EOQ models with general cost structures," International Journal of Production Economics, Elsevier, vol. 187(C), pages 216-228.
    13. Esra Koca & Hande Yaman & M. Selim Aktürk, 2014. "Lot Sizing with Piecewise Concave Production Costs," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 767-779, November.

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