IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v93y2016icp57-70.html
   My bibliography  Save this article

Min–Max exact and heuristic policies for a two-echelon supply chain with inventory and transportation procurement decisions

Author

Listed:
  • Bertazzi, Luca
  • Bosco, Adamo
  • Laganà, Demetrio

Abstract

We study the problem in which one supplier delivers a product to a set of retailers over time by using an outsourced fleet of vehicles. Since the probability distribution of the demand is not known, we provide a Min–Max approach to find robust policies. We show that the optimal Min-Expected Value policy can be very poor in the worst case. We provide a Min–Max Dynamic Programming formulation that allows us to exactly solve the problem in small instances. Finally, we implement a Min–Max Matheuristic to solve benchmark instances and show that it is very effective.

Suggested Citation

  • Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2016. "Min–Max exact and heuristic policies for a two-echelon supply chain with inventory and transportation procurement decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 57-70.
    • Handle: RePEc:eee:transe:v:93:y:2016:i:c:p:57-70
    DOI: 10.1016/j.tre.2016.05.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554515302933
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2016.05.008?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. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. Kenneth F. Simpson, 1958. "In-Process Inventories," Operations Research, INFORMS, vol. 6(6), pages 863-873, December.
    3. Andrew J. Clark & Herbert Scarf, 2004. "Optimal Policies for a Multi-Echelon Inventory Problem," Management Science, INFORMS, vol. 50(12_supple), pages 1782-1790, December.
    4. R. Jothi Basu & Nachiappan Subramanian & Naoufel Cheikhrouhou, 2015. "Review of Full Truckload Transportation Service Procurement," Transport Reviews, Taylor & Francis Journals, vol. 35(5), pages 599-621, September.
    5. Niakan, Farzad & Rahimi, Mohammad, 2015. "A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 74-94.
    6. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    7. Eruguz, Ayse Sena & Sahin, Evren & Jemai, Zied & Dallery, Yves, 2016. "A comprehensive survey of guaranteed-service models for multi-echelon inventory optimization," International Journal of Production Economics, Elsevier, vol. 172(C), pages 110-125.
    8. Claudia Archetti & Luca Bertazzi & Gilbert Laporte & Maria Grazia Speranza, 2007. "A Branch-and-Cut Algorithm for a Vendor-Managed Inventory-Routing Problem," Transportation Science, INFORMS, vol. 41(3), pages 382-391, August.
    9. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
    10. Ahmadi Javid, Amir & Azad, Nader, 2010. "Incorporating location, routing and inventory decisions in supply chain network design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(5), pages 582-597, September.
    11. Huang, Shan-Huen & Lin, Pei-Chun, 2010. "A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(5), pages 598-611, September.
    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. de Kok, Ton & Grob, Christopher & Laumanns, Marco & Minner, Stefan & Rambau, Jörg & Schade, Konrad, 2018. "A typology and literature review on stochastic multi-echelon inventory models," European Journal of Operational Research, Elsevier, vol. 269(3), pages 955-983.
    2. Bertazzi, Luca & Coelho, Leandro C. & De Maio, Annarita & Laganà, Demetrio, 2019. "A matheuristic algorithm for the multi-depot inventory routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 524-544.
    3. Coelho, Leandro Callegari & De Maio, Annarita & Laganà, Demetrio, 2020. "A variable MIP neighborhood descent for the multi-attribute inventory routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    4. Ke, Ginger Y. & Bookbinder, James H., 2018. "Coordinating the discount policies for retailer, wholesaler, and less-than-truckload carrier under price-sensitive demand: A tri-level optimization approach," International Journal of Production Economics, Elsevier, vol. 196(C), pages 82-100.
    5. Bertazzi, Luca & Chua, Geoffrey A. & Laganà, Demetrio & Paradiso, Rosario, 2022. "Analysis of effective sets of routes for the split-delivery periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 298(2), pages 463-477.
    6. Kapustina Larisa M. & Chovancová Mária & Klapita Vladimír, 2017. "Application of Specific Theory of Constraints Technique for the Identification of Main Causes of Negative Consequences within Procurement Logistics," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 8(1), pages 56-63, May.

    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. Chih-Kang Lin & Shangyao Yan & Fei-Yen Hsiao, 2021. "Optimal Inventory Level Control and Replenishment Plan for Retailers," Networks and Spatial Economics, Springer, vol. 21(1), pages 57-83, March.
    2. Leandro C. Coelho & Jean-François Cordeau & Gilbert Laporte, 2014. "Thirty Years of Inventory Routing," Transportation Science, INFORMS, vol. 48(1), pages 1-19, February.
    3. Mosca, Alyssa & Vidyarthi, Navneet & Satir, Ahmet, 2019. "Integrated transportation – inventory models: A review," Operations Research Perspectives, Elsevier, vol. 6(C).
    4. A. Mor & M. G. Speranza, 2020. "Vehicle routing problems over time: a survey," 4OR, Springer, vol. 18(2), pages 129-149, June.
    5. Alvarez, Aldair & Cordeau, Jean-François & Jans, Raf & Munari, Pedro & Morabito, Reinaldo, 2021. "Inventory routing under stochastic supply and demand," Omega, Elsevier, vol. 102(C).
    6. Achkar, Victoria G. & Brunaud, Braulio B. & Pérez, Héctor D. & Musa, Rami & Méndez, Carlos A. & Grossmann, Ignacio E., 2024. "Extensions to the guaranteed service model for industrial applications of multi-echelon inventory optimization," European Journal of Operational Research, Elsevier, vol. 313(1), pages 192-206.
    7. Mirzapour Al-e-hashem, Seyed M.J. & Rekik, Yacine & Mohammadi Hoseinhajlou, Ebrahim, 2019. "A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem," International Journal of Production Economics, Elsevier, vol. 209(C), pages 381-398.
    8. Hadi Jahangir & Mohammad Mohammadi & Seyed Hamid Reza Pasandideh & Neda Zendehdel Nobari, 2019. "Comparing performance of genetic and discrete invasive weed optimization algorithms for solving the inventory routing problem with an incremental delivery," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2327-2353, August.
    9. Liu, Ming & Liu, Xin & Chu, Feng & Zheng, Feifeng & Chu, Chengbin, 2019. "Distributionally robust inventory routing problem to maximize the service level under limited budget," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 190-211.
    10. Shang, Xiaoting & Zhang, Guoqing & Jia, Bin & Almanaseer, Mohammed, 2022. "The healthcare supply location-inventory-routing problem: A robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    11. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    12. Yazdani, Majid & Aouam, Tarik, 2023. "Shipment planning and safety stock placement in maritime supply chains with stochastic demand and transportation times," International Journal of Production Economics, Elsevier, vol. 263(C).
    13. Markov, Iliya & Bierlaire, Michel & Cordeau, Jean-François & Maknoon, Yousef & Varone, Sacha, 2018. "A unified framework for rich routing problems with stochastic demands," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 213-240.
    14. Aouam, Tarik & Kumar, Kunal, 2019. "On the effect of overtime and subcontracting on supply chain safety stocks," Omega, Elsevier, vol. 89(C), pages 1-20.
    15. A. Mor & M. G. Speranza, 2022. "Vehicle routing problems over time: a survey," Annals of Operations Research, Springer, vol. 314(1), pages 255-275, July.
    16. Niakan, Farzad & Rahimi, Mohammad, 2015. "A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 74-94.
    17. Timajchi, Ali & Mirzapour Al-e-Hashem, Seyed M.J. & Rekik, Yacine, 2019. "Inventory routing problem for hazardous and deteriorating items in the presence of accident risk with transshipment option," International Journal of Production Economics, Elsevier, vol. 209(C), pages 302-315.
    18. Stephen C. Graves & Tor Schoenmeyr, 2016. "Strategic Safety-Stock Placement in Supply Chains with Capacity Constraints," Manufacturing & Service Operations Management, INFORMS, vol. 18(3), pages 445-460, July.
    19. Rossi, Roberto & Tomasella, Maurizio & Martin-Barragan, Belen & Embley, Tim & Walsh, Christopher & Langston, Matthew, 2019. "The Dynamic Bowser Routing Problem," European Journal of Operational Research, Elsevier, vol. 275(1), pages 108-126.
    20. Mahmutoğulları, Özlem & Yaman, Hande, 2023. "A Branch-and-Cut Algorithm for the Inventory Routing Problem with Product Substitution," Omega, Elsevier, vol. 115(C).

    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:eee:transe:v:93:y:2016:i:c:p:57-70. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.