IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i4p1065-1084.html
   My bibliography  Save this article

An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles

Author

Listed:
  • He-Yau Kang
  • Amy H.I. Lee
  • Chien-Wei Wu
  • Cheng-Han Lee

Abstract

How to improve competitive edges to meet rapidly changing market environment and dynamic customer needs is critical for the survival and success of firms these days. A good supply chain and inventory management is a necessity in the intensive competitive market. This paper considers a dynamic-demand joint replenishment problem with multiple vehicle routing. The problem is first formulated as a mixed integer programming model with an objective to minimise total costs, which include ordering cost, purchase cost, production cost, transportation cost and holding cost, under a prerequisite that inventory shortage is prohibited in the system. A particle swarm optimisation model is proposed next to solve large-scale problems which are computationally difficult. A case study of a touch panel manufacturer is presented to examine the practicality of the models.

Suggested Citation

  • He-Yau Kang & Amy H.I. Lee & Chien-Wei Wu & Cheng-Han Lee, 2017. "An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1065-1084, February.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1065-1084
    DOI: 10.1080/00207543.2016.1218564
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1218564
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2016.1218564?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. Moon, I.K. & Cha, B.C., 2006. "The joint replenishment problem with resource restriction," European Journal of Operational Research, Elsevier, vol. 173(1), pages 190-198, August.
    2. Ertogral, K. & Darwish, M. & Ben-Daya, M., 2007. "Production and shipment lot sizing in a vendor-buyer supply chain with transportation cost," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1592-1606, February.
    3. Khouja, Moutaz & Goyal, Suresh, 2008. "A review of the joint replenishment problem literature: 1989-2005," European Journal of Operational Research, Elsevier, vol. 186(1), pages 1-16, April.
    4. Frank T. Shu, 1971. "Economic Ordering Frequency for two Items Jointly Replenished," Management Science, INFORMS, vol. 17(6), pages 406-410, February.
    5. Niv Buchbinder & Tracy Kimbrel & Retsef Levi & Konstantin Makarychev & Maxim Sviridenko, 2013. "Online Make-to-Order Joint Replenishment Model: Primal-Dual Competitive Algorithms," Operations Research, INFORMS, vol. 61(4), pages 1014-1029, August.
    6. Amaya, Ciro Alberto & Carvajal, Jimmy & Castaño, Fabian, 2013. "A heuristic framework based on linear programming to solve the constrained joint replenishment problem (C-JRP)," International Journal of Production Economics, Elsevier, vol. 144(1), pages 243-247.
    7. Hammami, Ramzi & Temponi, Cecilia & Frein, Yannick, 2014. "A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts," European Journal of Operational Research, Elsevier, vol. 233(1), pages 159-170.
    8. Cha, B.C. & Moon, I.K. & Park, J.H., 2008. "The joint replenishment and delivery scheduling of the one-warehouse, n-retailer system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 720-730, September.
    9. Narayanan, Arunachalam & Robinson, Powell, 2010. "Efficient and effective heuristics for the coordinated capacitated lot-size problem," European Journal of Operational Research, Elsevier, vol. 203(3), pages 583-592, June.
    10. Lu, Liang & Qi, Xiangtong, 2011. "Dynamic lot sizing for multiple products with a new joint replenishment model," European Journal of Operational Research, Elsevier, vol. 212(1), pages 74-80, July.
    11. E P Robinson & A Narayanan & L-L Gao, 2007. "Effective heuristics for the dynamic demand joint replenishment problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 808-815, June.
    12. Amy Lee & He-Yau Kang & Chun-Mei Lai, 2013. "Solving lot-sizing problem with quantity discount and transportation cost," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(4), pages 760-774.
    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. Wang, Min & Zhao, Lindu & Herty, Michael, 2019. "Joint replenishment and carbon trading in fresh food supply chains," European Journal of Operational Research, Elsevier, vol. 277(2), pages 561-573.
    2. Baller, Annelieke C. & Dabia, Said & Dullaert, Wout E.H. & Vigo, Daniele, 2019. "The Dynamic-Demand Joint Replenishment Problem with Approximated Transportation Costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1013-1033.
    3. Avelina Alejo-Reyes & Erik Cuevas & Alma Rodríguez & Abraham Mendoza & Elias Olivares-Benitez, 2020. "An Improved Grey Wolf Optimizer for a Supplier Selection and Order Quantity Allocation Problem," Mathematics, MDPI, vol. 8(9), pages 1-24, August.
    4. Chen, Kuen-Suan & Wang, Ching-Hsin & Tan, Kim-Hua, 2019. "Developing a fuzzy green supplier selection model using six sigma quality indices," International Journal of Production Economics, Elsevier, vol. 212(C), pages 1-7.
    5. Amy H. I. Lee & He-Yau Kang & Sih-Jie Ye & Wan-Yu Wu, 2018. "An Integrated Approach for Sustainable Supply Chain Management with Replenishment, Transportation, and Production Decisions," Sustainability, MDPI, vol. 10(11), pages 1-21, October.

    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. Saravanan Venkatachalam & Arunachalam Narayanan, 2016. "Efficient formulation and heuristics for multi-item single source ordering problem with transportation cost," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4087-4103, July.
    2. Carvajal, Jimmy & Castaño, Fabian & Sarache, William & Costa, Yasel, 2020. "Heuristic approaches for a two-echelon constrained joint replenishment and delivery problem," International Journal of Production Economics, Elsevier, vol. 220(C).
    3. Wang, Lin & He, Jing & Wu, Desheng & Zeng, Yu-Rong, 2012. "A novel differential evolution algorithm for joint replenishment problem under interdependence and its application," International Journal of Production Economics, Elsevier, vol. 135(1), pages 190-198.
    4. Pundoor, Guruprasad & Chen, Zhi-Long, 2009. "Joint cyclic production and delivery scheduling in a two-stage supply chain," International Journal of Production Economics, Elsevier, vol. 119(1), pages 55-74, May.
    5. Nguyen, Christine & Dessouky, Maged & Toriello, Alejandro, 2014. "Consolidation strategies for the delivery of perishable products," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 108-121.
    6. Ongkunaruk, P. & Wahab, M.I.M. & Chen, Y., 2016. "A genetic algorithm for a joint replenishment problem with resource and shipment constraints and defective items," International Journal of Production Economics, Elsevier, vol. 175(C), pages 142-152.
    7. Cui, Ligang & Deng, Jie & Liu, Rui & Xu, Dongyang & Zhang, Yajun & Xu, Maozeng, 2020. "A stochastic multi-item replenishment and delivery problem with lead-time reduction initiatives and the solving methodologies," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    8. Baller, Annelieke C. & Dabia, Said & Dullaert, Wout E.H. & Vigo, Daniele, 2019. "The Dynamic-Demand Joint Replenishment Problem with Approximated Transportation Costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1013-1033.
    9. Yao, Ming-Jong & Lin, Jen-Yen & Lin, Yu-Liang & Fang, Shu-Cherng, 2020. "An integrated algorithm for solving multi-customer joint replenishment problem with districting consideration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    10. Tamar Cohen-Hillel & Liron Yedidsion, 2018. "The Periodic Joint Replenishment Problem Is Strongly 𝒩𝒫-Hard," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1269-1289, November.
    11. Amaya, Ciro Alberto & Carvajal, Jimmy & Castaño, Fabian, 2013. "A heuristic framework based on linear programming to solve the constrained joint replenishment problem (C-JRP)," International Journal of Production Economics, Elsevier, vol. 144(1), pages 243-247.
    12. Narayanan, Arunachalam & Robinson, Powell, 2010. "Evaluation of joint replenishment lot-sizing procedures in rolling horizon planning systems," International Journal of Production Economics, Elsevier, vol. 127(1), pages 85-94, September.
    13. Xuefei Shi & Haiyan Wang, 2022. "Design of the cost allocation rule for joint replenishment to an overseas warehouse with a piecewise linear holding cost rate," Operational Research, Springer, vol. 22(5), pages 4905-4929, November.
    14. Marcello Braglia & Davide Castellano & Marco Frosolini, 2016. "Joint-replenishment problem under stochastic demands with backorders-lost sales mixtures, controllable lead times, and investment to reduce the major ordering cost," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(8), pages 1108-1120, August.
    15. Ji Seong Noh & Jong Soo Kim & Biswajit Sarkar, 2019. "Stochastic joint replenishment problem with quantity discounts and minimum order constraints," Operational Research, Springer, vol. 19(1), pages 151-178, March.
    16. Stefanny Ramirez & Laurence H. Brandenburg & Dario Bauso, 2023. "Coordinated Replenishment Game and Learning Under Time Dependency and Uncertainty of the Parameters," Dynamic Games and Applications, Springer, vol. 13(1), pages 326-352, March.
    17. Péter Györgyi & Tamás Kis & Tímea Tamási & József Békési, 2023. "Joint replenishment meets scheduling," Journal of Scheduling, Springer, vol. 26(1), pages 77-94, February.
    18. Ke, Ginger Y. & Bookbinder, James H., 2012. "Discount pricing for a family of items: The supplier's optimal decisions," International Journal of Production Economics, Elsevier, vol. 135(1), pages 255-264.
    19. Khouja, Moutaz & Goyal, Suresh, 2008. "A review of the joint replenishment problem literature: 1989-2005," European Journal of Operational Research, Elsevier, vol. 186(1), pages 1-16, April.
    20. Shiyu Liu & Ou Liu & Xiaoming Jiang, 2023. "An Efficient Algorithm for the Joint Replenishment Problem with Quantity Discounts, Minimum Order Quantity and Transport Capacity Constraints," Mathematics, MDPI, vol. 11(4), pages 1-18, February.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:55:y:2017:i:4:p:1065-1084. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.