IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v57y2006i8d10.1057_palgrave.jors.2602076.html
   My bibliography  Save this article

Two modifications of the least cost per period heuristic for dynamic lot-sizing

Author

Listed:
  • J C Ho

    (The University of Texas at El Paso)

  • Y-L Chang

    (Georgia Institute of Technology)

  • A O Solis

    (The University of Texas at El Paso)

Abstract

This paper proposes two constructive heuristics for the well-known single-level uncapacitated dynamic lot-sizing problem. The proposed heuristics, called net least period cost (nLPC) and nLPC(i), are developed by modifying the average period cost concept from Silver and Meal's heuristic, commonly known as least period cost (LPC). An improved tie-breaking stopping rule and a locally optimal decision rule are proposed in the second heuristic to enhance performance. We test the effectiveness of the proposed heuristics by using 20 benchmarking test problems frequently used in the literature. Furthermore, we perform a large-scale simulation study involving three factors, 50 experimental conditions, and 100 000 randomly generated problems to evaluate the proposed heuristics against LPC and six other well-known constructive heuristics in the literature. The simulation results show that both nLPC and nLPC(i) produce average holding and setup costs lower than or equal to those of LPC in every one of the 50 experimental conditions. The proposed heuristics also outperform each of the six other heuristics evaluated in all experimental conditions, without an increase in computational requirements. Lastly, considering that both nLPC and nLPC(i) are fairly simple for practitioners to understand and that lot-sizing heuristics have been commonly used in practice, there should be a very good chance for practical applications of the proposed heuristics.

Suggested Citation

  • J C Ho & Y-L Chang & A O Solis, 2006. "Two modifications of the least cost per period heuristic for dynamic lot-sizing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 1005-1013, August.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:8:d:10.1057_palgrave.jors.2602076
    DOI: 10.1057/palgrave.jors.2602076
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602076
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602076?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J Hu & C L Munson, 2002. "Dynamic demand lot-sizing rules for incremental quantity discounts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(8), pages 855-863, August.
    2. Harvey M. Wagner & Thomson M. Whitin, 1958. "Dynamic Version of the Economic Lot Size Model," Management Science, INFORMS, vol. 5(1), pages 89-96, October.
    3. Pan, C-H, 1994. "Sensitivity analysis of dynamic lot-sizing heuristics," Omega, Elsevier, vol. 22(3), pages 251-261, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tasdemir, Cagatay & Hiziroglu, Salim, 2019. "Achieving cost efficiency through increased inventory leanness: Evidences from oriented strand board (OSB) industry," International Journal of Production Economics, Elsevier, vol. 208(C), pages 412-433.
    2. Folarin B. Oyebolu & Jeroen Lidth de Jeude & Cyrus Siganporia & Suzanne S. Farid & Richard Allmendinger & Juergen Branke, 2017. "A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production," Journal of Heuristics, Springer, vol. 23(4), pages 231-256, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J Hu & C L Munson & E A Silver, 2004. "A modified Silver–Meal heuristic for dynamic lot sizing under incremental quantity discounts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(6), pages 671-673, June.
    2. Robinson, Powell & Narayanan, Arunachalam & Sahin, Funda, 2009. "Coordinated deterministic dynamic demand lot-sizing problem: A review of models and algorithms," Omega, Elsevier, vol. 37(1), pages 3-15, February.
    3. Battini, Daria & Persona, Alessandro & Sgarbossa, Fabio, 2014. "A sustainable EOQ model: Theoretical formulation and applications," International Journal of Production Economics, Elsevier, vol. 149(C), pages 145-153.
    4. Siao-Leu Phouratsamay & Safia Kedad-Sidhoum & Fanny Pascual, 2021. "Coordination of a two-level supply chain with contracts," 4OR, Springer, vol. 19(2), pages 235-264, June.
    5. Wolosewicz, Cathy & Dauzère-Pérès, Stéphane & Aggoune, Riad, 2015. "A Lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 3-12.
    6. Charles, Mehdi & Dauzère-Pérès, Stéphane & Kedad-Sidhoum, Safia & Mazhoud, Issam, 2022. "Motivations and analysis of the capacitated lot-sizing problem with setup times and minimum and maximum ending inventories," European Journal of Operational Research, Elsevier, vol. 302(1), pages 203-220.
    7. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    8. Liu, Tieming, 2008. "Economic lot sizing problem with inventory bounds," European Journal of Operational Research, Elsevier, vol. 185(1), pages 204-215, February.
    9. Lee, Jinkyu & Bae, Sanghyeon & Kim, Woo Chang & Lee, Yongjae, 2023. "Value function gradient learning for large-scale multistage stochastic programming problems," European Journal of Operational Research, Elsevier, vol. 308(1), pages 321-335.
    10. Kaijie Zhu & Ulrich W. Thonemann, 2009. "Coordination of pricing and inventory control across products," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(2), pages 175-190, March.
    11. Chakrabarti, T. & Chaudhuri, K. S., 1997. "An EOQ model for deteriorating items with a linear trend in demand and shortages in all cycles," International Journal of Production Economics, Elsevier, vol. 49(3), pages 205-213, May.
    12. Rossi, Tommaso & Pozzi, Rossella & Testa, Mariapaola, 2017. "EOQ-based inventory management in single-machine multi-item systems," Omega, Elsevier, vol. 71(C), pages 106-113.
    13. Timo Hilger & Florian Sahling & Horst Tempelmeier, 2016. "Capacitated dynamic production and remanufacturing planning under demand and return uncertainty," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(4), pages 849-876, October.
    14. Guerrero, W.J. & Prodhon, C. & Velasco, N. & Amaya, C.A., 2013. "Hybrid heuristic for the inventory location-routing problem with deterministic demand," International Journal of Production Economics, Elsevier, vol. 146(1), pages 359-370.
    15. Ming Zhao & Minjiao Zhang, 2020. "Multiechelon Lot Sizing: New Complexities and Inequalities," Operations Research, INFORMS, vol. 68(2), pages 534-551, March.
    16. Bouchery, Yann & Hezarkhani, Behzad & Stauffer, Gautier, 2022. "Coalition formation and cost sharing for truck platooning," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 15-34.
    17. Jenny Carolina Saldana Cortés, 2011. "Programación semidefinida aplicada a problemas de cantidad económica de pedido," Documentos CEDE 8735, Universidad de los Andes, Facultad de Economía, CEDE.
    18. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    19. van den Heuvel, Wilco & Gutiérrez, José Miguel & Hwang, Hark-Chin, 2011. "Note on "An efficient approach for solving the lot-sizing problem with time-varying storage capacities"," European Journal of Operational Research, Elsevier, vol. 213(2), pages 455-457, September.
    20. Zhili Zhou & Yongpei Guan, 2013. "Two-stage stochastic lot-sizing problem under cost uncertainty," Annals of Operations Research, Springer, vol. 209(1), pages 207-230, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:57:y:2006:i:8:d:10.1057_palgrave.jors.2602076. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.