IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i23p3664-d1527300.html
   My bibliography  Save this article

An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution

Author

Listed:
  • Vincent F. Yu

    (Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan)

  • Ching-Hsuan Lin

    (Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan)

  • Renan S. Maglasang

    (Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan)

  • Shih-Wei Lin

    (Department of Information Management, Chang Gung University, Taoyuan 333, Taiwan
    Department of Emergency Medicine, Keelung Chang Gung Memorial Hospital, Keelung 204, Taiwan
    Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 243, Taiwan)

  • Kuan-Fu Chen

    (Department of Emergency Medicine, Keelung Chang Gung Memorial Hospital, Keelung 204, Taiwan
    College of Intelligent Computing, Chang Gung University, Taoyuan 333, Taiwan)

Abstract

A variant of the vehicle routing problem (VRP) known as the Vehicle Routing Problem in Omnichannel Retailing Distribution Systems (VRPO) has recently been introduced in the literature, driven by the increasing adoption of omnichannel logistics in practice. The VRPO scenario involves a large retailer managing several stores, a depot, and a homogenous fleet of vehicles to meet the demands of both stores and online customers. This variant falls within the class of VRPs that consider precedence constraints. Although the vehicle routing problem in omnichannel retailing distribution (VRPO) has been addressed using a few heuristic and metaheuristic approaches, the use of Simulated Annealing (SA) remains largely unexplored in the pickup and delivery problem (PDP) literature, both before and after the rise of omnichannel logistics. This article introduces the Efficient Simulated Annealing (ESA) algorithm, demonstrating its suitability in generating new benchmark solutions for the VRPO. In experiments with sixty large instances, ESA significantly outperformed two previous algorithms, discovering new best-known solutions (BKSs) in fifty-nine out of sixty cases. Additionally, ESA demonstrated superior efficiency in 68.3% of the test cases in terms of reduced computational times, showcasing its higher effectiveness in handling complex VRPO instances.

Suggested Citation

  • Vincent F. Yu & Ching-Hsuan Lin & Renan S. Maglasang & Shih-Wei Lin & Kuan-Fu Chen, 2024. "An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3664-:d:1527300
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/23/3664/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/23/3664/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gerardo Berbeglia & Jean-François Cordeau & Irina Gribkovskaia & Gilbert Laporte, 2007. "Rejoinder on: Static pickup and delivery problems: a classification scheme and survey," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 45-47, July.
    2. Janjevic, Milena & Merchán, Daniel & Winkenbach, Matthias, 2021. "Designing multi-tier, multi-service-level, and multi-modal last-mile distribution networks for omni-channel operations," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1059-1077.
    3. Gerardo Berbeglia & Jean-François Cordeau & Irina Gribkovskaia & Gilbert Laporte, 2007. "Static pickup and delivery problems: a classification scheme and survey," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-31, July.
    4. Abdulkader, M.M.S. & Gajpal, Yuvraj & ElMekkawy, Tarek Y., 2018. "Vehicle routing problem in omni-channel retailing distribution systems," International Journal of Production Economics, Elsevier, vol. 196(C), pages 43-55.
    5. Vincent F. Yu & Putu A. Y. Indrakarna & Anak Agung Ngurah Perwira Redi & Shih-Wei Lin, 2021. "Simulated Annealing with Mutation Strategy for the Share-a-Ride Problem with Flexible Compartments," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    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. Gansterer, Margaretha & Hartl, Richard F. & Sörensen, Kenneth, 2020. "Pushing frontiers in auction-based transport collaborations," Omega, Elsevier, vol. 94(C).
    2. Forma, Iris A. & Raviv, Tal & Tzur, Michal, 2015. "A 3-step math heuristic for the static repositioning problem in bike-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 230-247.
    3. Hennig, F. & Nygreen, B. & Christiansen, M. & Fagerholt, K. & Furman, K.C. & Song, J. & Kocis, G.R. & Warrick, P.H., 2012. "Maritime crude oil transportation – A split pickup and split delivery problem," European Journal of Operational Research, Elsevier, vol. 218(3), pages 764-774.
    4. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    5. Gutiérrez-Jarpa, Gabriel & Desaulniers, Guy & Laporte, Gilbert & Marianov, Vladimir, 2010. "A branch-and-price algorithm for the Vehicle Routing Problem with Deliveries, Selective Pickups and Time Windows," European Journal of Operational Research, Elsevier, vol. 206(2), pages 341-349, October.
    6. Salazar-González, Juan-José & Santos-Hernández, Beatriz, 2015. "The split-demand one-commodity pickup-and-delivery travelling salesman problem," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 58-73.
    7. Connor Little & Salimur Choudhury & Ting Hu & Kai Salomaa, 2022. "Comparison of Genetic Operators for the Multiobjective Pickup and Delivery Problem," Mathematics, MDPI, vol. 10(22), pages 1-21, November.
    8. Qin, Hu & Moriakin, Anton & Xu, Gangyan & Li, Jiliu, 2024. "The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach," European Journal of Operational Research, Elsevier, vol. 318(3), pages 752-767.
    9. Albert H. Schrotenboer & Evrim Ursavas & Iris F. A. Vis, 2019. "A Branch-and-Price-and-Cut Algorithm for Resource-Constrained Pickup and Delivery Problems," Transportation Science, INFORMS, vol. 53(4), pages 1001-1022, July.
    10. Capelle, Thomas & Cortés, Cristián E. & Gendreau, Michel & Rey, Pablo A. & Rousseau, Louis-Martin, 2019. "A column generation approach for location-routing problems with pickup and delivery," European Journal of Operational Research, Elsevier, vol. 272(1), pages 121-131.
    11. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    12. Qiu, Ruozhen & Yuan, Mingli & Sun, Minghe & Fan, Zhi-Ping & Xu, Henry, 2025. "Optimizing omnichannel retailer inventory replenishment using vehicle capacity-sharing with demand uncertainties and service level requirements," European Journal of Operational Research, Elsevier, vol. 320(2), pages 417-432.
    13. Ohad Eisenhandler & Michal Tzur, 2019. "A Segment-Based Formulation and a Matheuristic for the Humanitarian Pickup and Distribution Problem," Transportation Science, INFORMS, vol. 53(5), pages 1389-1408, September.
    14. Margaretha Gansterer & Richard F. Hartl, 2021. "The Prisoners’ Dilemma in collaborative carriers’ request selection," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 73-87, March.
    15. Trotta, Manuel & Archetti, Claudia & Feillet, Dominique & Quilliot, Alain, 2022. "Pickup and delivery problems with autonomous vehicles on rings," European Journal of Operational Research, Elsevier, vol. 300(1), pages 221-236.
    16. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    17. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    18. Mohammad Torkjazi & Nathan Huynh, 2019. "Effectiveness of Dynamic Insertion Scheduling Strategy for Demand-Responsive Paratransit Vehicles Using Agent-Based Simulation," Sustainability, MDPI, vol. 11(19), pages 1-12, September.
    19. Jiliu Li & Zhixing Luo & Roberto Baldacci & Hu Qin & Zhou Xu, 2023. "A New Exact Algorithm for Single-Commodity Vehicle Routing with Split Pickups and Deliveries," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 31-49, January.
    20. Song, Yujian & Zhang, Jiantong & Liang, Zhe & Ye, Chunming, 2017. "An exact algorithm for the container drayage problem under a separation mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 231-254.

    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:gam:jmathe:v:12:y:2024:i:23:p:3664-:d:1527300. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.