IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v22y2022i2d10.1007_s12351-020-00593-3.html
   My bibliography  Save this article

A column generation approach for an inventory routing problem with fuzzy time windows

Author

Listed:
  • Amir Saeed Nikkhah Qamsari

    (Iran University of Science and Technology)

  • Seyyed-Mahdi Hosseini-Motlagh

    (Iran University of Science and Technology)

  • Seyed Farid Ghannadpour

    (Iran University of Science and Technology)

Abstract

This paper proposes a novel approach towards inventory routing problems with fuzzy time windows considering customer satisfaction for arrival intervals. In the presented model, a multi-priority structure for visiting the customers is proposed. In this study, customers are divided into three categories according to their features. These features have different degrees of importance from the distributer’s perspective. The satisfaction level of customers plays an important role in the decision of the supplier to fulfill their demand in each period. Since the proposed model is characterized as a highly complex problem, a decomposition-based heuristic approach is developed to obtain a high-quality solution in reasonable computational time. Moreover, to properly calibrate the parameters of the developed algorithm and decrease the number of experiments, Taguchi experimental design technique is utilized to measure the efficiency of the parameter. Comparing the obtained results with previous studies indicates that the presented procedure outperforms similar heuristic-based solution techniques proposed in the relevant literature. Finally, the practical application of the proposed model is discussed by studying a real-world case study of a blood distribution system in Tehran.

Suggested Citation

  • Amir Saeed Nikkhah Qamsari & Seyyed-Mahdi Hosseini-Motlagh & Seyed Farid Ghannadpour, 2022. "A column generation approach for an inventory routing problem with fuzzy time windows," Operational Research, Springer, vol. 22(2), pages 1157-1207, April.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:2:d:10.1007_s12351-020-00593-3
    DOI: 10.1007/s12351-020-00593-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-020-00593-3
    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/s12351-020-00593-3?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. Sun, Peng & Veelenturf, Lucas P. & Hewitt, Mike & Van Woensel, Tom, 2018. "The time-dependent pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 1-24.
    2. Iassinovskaia, Galina & Limbourg, Sabine & Riane, Fouad, 2017. "The inventory-routing problem of returnable transport items with time windows and simultaneous pickup and delivery in closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 570-582.
    3. 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.
    4. Veaceslav Ghilas & Jean-François Cordeau & Emrah Demir & Tom Van Woensel, 2018. "Branch-and-Price for the Pickup and Delivery Problem with Time Windows and Scheduled Lines," Transportation Science, INFORMS, vol. 52(5), pages 1191-1210, October.
    5. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    6. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    7. N H Moin & S Salhi, 2007. "Inventory routing problems: a logistical overview," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(9), pages 1185-1194, September.
    8. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    9. Reil, Sebastian & Bortfeldt, Andreas & Mönch, Lars, 2018. "Heuristics for vehicle routing problems with backhauls, time windows, and 3D loading constraints," European Journal of Operational Research, Elsevier, vol. 266(3), pages 877-894.
    10. 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.
    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. Lee, Jongsung & Kim, Byung-In & Johnson, Andrew L. & Lee, Kiho, 2014. "The nuclear medicine production and delivery problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 461-472.
    2. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    3. Frank, Markus & Ostermeier, Manuel & Holzapfel, Andreas & Hübner, Alexander & Kuhn, Heinrich, 2021. "Optimizing routing and delivery patterns with multi-compartment vehicles," European Journal of Operational Research, Elsevier, vol. 293(2), pages 495-510.
    4. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2017. "A hybrid solution approach for the 3L-VRP with simultaneous delivery and pickups," FEMM Working Papers 170005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    5. Corinna Krebs & Jan Fabian Ehmke & Henriette Koch, 2021. "Advanced loading constraints for 3D vehicle routing problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 835-875, December.
    6. Zongyi Chen & Mingkang Yang & Yijun Guo & Yu Liang & Yifan Ding & Li Wang, 2020. "The Split Delivery Vehicle Routing Problem with Three-Dimensional Loading and Time Windows Constraints," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    7. Mo, Pengli & Yao, Yu & D’Ariano, Andrea & Liu, Zhiyuan, 2023. "The vehicle routing problem with underground logistics: Formulation and algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    8. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    9. Aksen, Deniz & Kaya, Onur & Sibel Salman, F. & Tüncel, Özge, 2014. "An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 413-426.
    10. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    11. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2018. "A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1029-1075, October.
    12. Jian Li & Yang Li & Panos M. Pardalos, 2016. "Multi-depot vehicle routing problem with time windows under shared depot resources," Journal of Combinatorial Optimization, Springer, vol. 31(2), pages 515-532, February.
    13. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The fleet size and mix location-routing problem with time windows: Formulations and a heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 248(1), pages 33-51.
    14. Keskin, Merve & Branke, Juergen & Deineko, Vladimir & Strauss, Arne K., 2023. "Dynamic multi-period vehicle routing with touting," European Journal of Operational Research, Elsevier, vol. 310(1), pages 168-184.
    15. Lagos, Felipe & Pereira, Jordi, 2024. "Multi-armed bandit-based hyper-heuristics for combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 70-91.
    16. Jean-Yves Potvin, 2009. "State-of-the Art Review ---Evolutionary Algorithms for Vehicle Routing," INFORMS Journal on Computing, INFORMS, vol. 21(4), pages 518-548, November.
    17. Chen, Cheng & Demir, Emrah & Huang, Yuan, 2021. "An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1164-1180.
    18. Molenbruch, Yves & Braekers, Kris & Hirsch, Patrick & Oberscheider, Marco, 2021. "Analyzing the benefits of an integrated mobility system using a matheuristic routing algorithm," European Journal of Operational Research, Elsevier, vol. 290(1), pages 81-98.
    19. Sun, Peng & Veelenturf, Lucas P. & Hewitt, Mike & Van Woensel, Tom, 2020. "Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    20. Pottel, Steffen & Goel, Asvin, 2022. "Scheduling activities with time-dependent durations and resource consumptions," European Journal of Operational Research, Elsevier, vol. 301(2), pages 445-457.

    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:operea:v:22:y:2022:i:2:d:10.1007_s12351-020-00593-3. 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.