IDEAS home Printed from https://ideas.repec.org/a/spr/flsman/v37y2025i2d10.1007_s10696-024-09536-y.html
   My bibliography  Save this article

A first optimization approach to parameterize demand-driven MRP in the presence of multiple products and finite capacity

Author

Listed:
  • David Damand

    (EM Strasbourg Business School)

  • Youssef Lahrichi

    (ISCAE)

  • Marc Barth

    (EM Strasbourg Business School)

Abstract

Demand-Driven Material Requirements Planning (DDMRP) is a promising production planning and control system that first appeared in 2011. The main novelty of DDMRP is that it protects critical references with buffer stocks and generates replenishment orders based on real-time demand and stock. Many scholars have studied its performance relative to more established production planning systems and demonstrated its competitiveness. More recently, studies dealing with the parameterization of Demand-Driven MRP have emerged. These papers present algorithms to fix DDMRP parameters with the objective of maximizing the On-Time Delivery (OTD) that is the percentage of customer orders delivered on-time or minimizing the average on-hand inventory. These studies all consider either a single reference or multiple references without managing conflicts between references competing for a bottleneck resource. This paper presents a first study to parameterize DDMRP in the presence of multiple products and finite capacity. Capacity limitation is modeled as a limitation of WIP (work-in-progress). A multi-objective genetic algorithm, which we initially suggested for a single reference, is extended in this paper to multiple references and finite capacity. The optimization algorithm is tested and analyzed on 21 data instances with 10 references.

Suggested Citation

  • David Damand & Youssef Lahrichi & Marc Barth, 2025. "A first optimization approach to parameterize demand-driven MRP in the presence of multiple products and finite capacity," Flexible Services and Manufacturing Journal, Springer, vol. 37(2), pages 324-347, June.
    • Handle: RePEc:spr:flsman:v:37:y:2025:i:2:d:10.1007_s10696-024-09536-y
    DOI: 10.1007/s10696-024-09536-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10696-024-09536-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10696-024-09536-y?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. Jingjing Jiang & Suk-Chul Rim, 2017. "Strategic WIP Inventory Positioning for Make-to-Order Production with Stochastic Processing Times," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-7, November.
    2. Lage Junior, Muris & Godinho Filho, Moacir, 2010. "Variations of the kanban system: Literature review and classification," International Journal of Production Economics, Elsevier, vol. 125(1), pages 13-21, May.
    3. Angela Patricia Velasco Acosta & Christian Mascle & Pierre Baptiste, 2020. "Applicability of Demand-Driven MRP in a complex manufacturing environment," International Journal of Production Research, Taylor & Francis Journals, vol. 58(14), pages 4233-4245, July.
    4. Baptiste Bahu & Laurent Bironneau & Vincent Hovelaque, 2019. "Compréhension du DDMRP et de son adoption : premiers éléments empiriques," Post-Print halshs-02024594, HAL.
    5. Chan-Ju Lee & Suk-Chul Rim, 2019. "A Mathematical Safety Stock Model for DDMRP Inventory Replenishment," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-10, September.
    6. Romain Miclo & Matthieu Lauras & Franck Fontanili & Jacques Lamothe & Steven A. Melnyk, 2019. "Demand Driven MRP: assessment of a new approach to materials management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(1), pages 166-181, January.
    Full references (including those not matched with items on IDEAS)

    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. Daniela Favaretto & Alessandro Marin & Marco Tolotti, 2023. "A theoretical validation of the DDMRP reorder policy," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
    2. Matthias Thürer & Nuno O. Fernandes & Hermann Lödding & Mark Stevenson, 2025. "Material flow control in make-to-stock production systems: an assessment of order generation, order release and production authorization by simulation," Flexible Services and Manufacturing Journal, Springer, vol. 37(1), pages 1-37, March.
    3. Nuno Octávio Fernandes & Matthias Thürer & Sílvio Carmo Silva, 2024. "DDMRP relative priority for production execution: an assessment by simulation," Operations Management Research, Springer, vol. 17(4), pages 1244-1256, December.
    4. Bruno Michel Roman Pais Seles & Janaina Mascarenhas & Ana Beatriz Lopes de Sousa Jabbour & Adriana Hoffman Trevisan, 2022. "Smoothing the circular economy transition: The role of resources and capabilities enablers," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1814-1837, May.
    5. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    6. Diogo Ferraz & Fernanda P. S. Falguera & Enzo B. Mariano & Dominik Hartmann, 2021. "Linking Economic Complexity, Diversification, and Industrial Policy with Sustainable Development: A Structured Literature Review," Sustainability, MDPI, vol. 13(3), pages 1-29, January.
    7. Maico Roris Severino & Moacir Godinho Filho, 2019. "POLCA system for supply chain management: simulation in the automotive industry," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1271-1289, March.
    8. Brandenburg, Marcus & Govindan, Kannan & Sarkis, Joseph & Seuring, Stefan, 2014. "Quantitative models for sustainable supply chain management: Developments and directions," European Journal of Operational Research, Elsevier, vol. 233(2), pages 299-312.
    9. Ammar Y. Alqahtani & Surendra M. Gupta, 2017. "One-Dimensional Renewable Warranty Management within Sustainable Supply Chain," Resources, MDPI, vol. 6(2), pages 1-26, April.
    10. Omar Sacilotto Donaires & Luciana Oranges Cezarino & Lara Bartocci Liboni & Evandro Marcos Saidel Ribeiro & Flávio Pinheiro Martins, 2023. "Multivariate data analysis of categorical data: taking advantage of the rhetorical power of numbers in qualitative research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(6), pages 5283-5312, December.
    11. Carlos Cuartas & Jose Aguilar, 2023. "Hybrid algorithm based on reinforcement learning for smart inventory management," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 123-149, January.
    12. Lopes de Sousa Jabbour, Ana Beatriz & Ndubisi, Nelson Oly & Roman Pais Seles, Bruno Michel, 2020. "Sustainable development in Asian manufacturing SMEs: Progress and directions," International Journal of Production Economics, Elsevier, vol. 225(C).
    13. Peng Lin & Leidi Shen & Zhiheng Zhao & George Q. Huang, 2019. "Graduation manufacturing system: synchronization with IoT-enabled smart tickets," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2885-2900, December.
    14. Mota, André Luiz Siqueira & Lins, Romulo Gonçalves, 2025. "Production of customized commercial vehicles in assembly line based on modified-to-order demands: A novel method and study case," International Journal of Production Economics, Elsevier, vol. 282(C).
    15. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    16. Hidemichi Fujii & Kazuma Edamura & Koichi Sumikura & Yoko Furusawa & Naomi Fukuzawa & Shunsuke Managi, 2015. "How enterprise strategies are related to innovation and productivity change: an empirical study of Japanese manufacturing firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 24(3), pages 248-262, April.
    17. Rosmaini Ahmad & Rabiatul Fakhira Mohd Amin & Shaliza Azreen Mustafa, 2022. "Value stream mapping with lean thinking model for effective non-value added identification, evaluation and solution processes," Operations Management Research, Springer, vol. 15(3), pages 1490-1509, December.
    18. Maria Carolina Rezende de Carvalho Ferreira & Vinicius Amorim Sobreiro & Herbert Kimura & Flavio Luiz de Moraes Barboza, 2016. "A systematic review of literature about finance and sustainability," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 6(2), pages 112-147, April.
    19. George Marian AEVOAE, 2018. "How Can We Create Value From Enterprise Concentrations? A Meta-Analysis Of The Scientific Literature On M&As In The European Union," EURINT, Centre for European Studies, Alexandru Ioan Cuza University, vol. 5, pages 63-87.
    20. de Camargo Fiorini, Paula & Jabbour, Charbel José Chiappetta, 2017. "Information systems and sustainable supply chain management towards a more sustainable society: Where we are and where we are going," International Journal of Information Management, Elsevier, vol. 37(4), pages 241-249.

    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:spr:flsman:v:37:y:2025:i:2:d:10.1007_s10696-024-09536-y. 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.springer.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.