IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v180y2010i1p125-14410.1007-s10479-008-0487-y.html
   My bibliography  Save this article

A hybrid search method for the vehicle routing problem with time windows

Author

Listed:
  • Humberto Brandão de Oliveira
  • Germano Vasconcelos

Abstract

Vehicle Routing Problems have been extensively analyzed to reduce transportation costs. More particularly, the Vehicle Routing Problem with Time Windows (VRPTW) imposes the period of time of customer availability as a constraint, a common characteristic in real world situations. Using minimization of the total distance as the main objective to be fulfilled, this work implements an efficient algorithm which associates non-monotonic Simulated Annealing to Hill-Climbing and Random Restart. The algorithm is compared to the best results published in the literature for the 56 Solomon instances and it is shown how statistical methods can be used to boost the performance of the method. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Humberto Brandão de Oliveira & Germano Vasconcelos, 2010. "A hybrid search method for the vehicle routing problem with time windows," Annals of Operations Research, Springer, vol. 180(1), pages 125-144, November.
    • Handle: RePEc:spr:annopr:v:180:y:2010:i:1:p:125-144:10.1007/s10479-008-0487-y
    DOI: 10.1007/s10479-008-0487-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-008-0487-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-008-0487-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. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    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. Abdul Salam Khan & Qazi Salman Khalid & Khawar Naeem & Rafiq Ahmad & Razaullah Khan & Waqas Saleem & Catalin Iulian Pruncu, 2021. "Application of Exact and Multi-Heuristic Approaches to a Sustainable Closed Loop Supply Chain Network Design," Sustainability, MDPI, vol. 13(5), pages 1-25, February.
    2. Grigorios D. Konstantakopoulos & Sotiris P. Gayialis & Evripidis P. Kechagias, 2022. "Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification," Operational Research, Springer, vol. 22(3), pages 2033-2062, July.
    3. Yu, Vincent F. & Jodiawan, Panca & Redi, A.A.N. Perwira, 2022. "Crowd-shipping problem with time windows, transshipment nodes, and delivery options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    4. Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    5. Yang Zou & Hecheng Wu & Yunqiang Yin & Lalitha Dhamotharan & Daqiang Chen & Aviral Kumar Tiwari, 2024. "An improved transformer model with multi-head attention and attention to attention for low-carbon multi-depot vehicle routing problem," Annals of Operations Research, Springer, vol. 339(1), pages 517-536, August.

    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. Jumbo, Olga & Moghaddass, Ramin, 2022. "Resource optimization and image processing for vegetation management programs in power distribution networks," Applied Energy, Elsevier, vol. 319(C).
    2. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    3. Babagolzadeh, Mahla & Zhang, Yahua & Abbasi, Babak & Shrestha, Anup & Zhang, Anming, 2022. "Promoting Australian regional airports with subsidy schemes: Optimised downstream logistics using vehicle routing problem," Transport Policy, Elsevier, vol. 128(C), pages 38-51.
    4. Ido Orenstein & Tal Raviv & Elad Sadan, 2019. "Flexible parcel delivery to automated parcel lockers: models, solution methods and analysis," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 683-711, December.
    5. Tianlu Zhao & Yongjian Yang & En Wang, 2020. "Minimizing the average arriving distance in carpooling," International Journal of Distributed Sensor Networks, , vol. 16(1), pages 15501477198, January.
    6. Dessouky, Maged M & Shao, Yihuan E, 2017. "Routing Strategies for Efficient Deployment of Alternative Fuel Vehicles for Freight Delivery," Institute of Transportation Studies, Working Paper Series qt0nj024qn, Institute of Transportation Studies, UC Davis.
    7. A. Mor & M. G. Speranza, 2020. "Vehicle routing problems over time: a survey," 4OR, Springer, vol. 18(2), pages 129-149, June.
    8. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    9. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    10. Pradhananga, Rojee & Taniguchi, Eiichi & Yamada, Tadashi & Qureshi, Ali Gul, 2014. "Bi-objective decision support system for routing and scheduling of hazardous materials," Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 135-148.
    11. Yimei Chang & Jiaqi Yu & Yang Wang & Xiaoling Xie, 2025. "An Improved Salp Swarm Algorithm for Solving a Multi-Temperature Joint Distribution Route Optimization Problem," Mathematics, MDPI, vol. 13(4), pages 1-24, February.
    12. Y H Lee & J I Kim & K H Kang & K H Kim, 2008. "A heuristic for vehicle fleet mix problem using tabu search and set partitioning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 833-841, June.
    13. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    14. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    15. Tibor Holczinger & Olivér Ősz & Máté Hegyháti, 2020. "Scheduling approach for on-site jobs of service providers," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 913-948, December.
    16. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    17. Jinil Han & Chungmok Lee & Sungsoo Park, 2014. "A Robust Scenario Approach for the Vehicle Routing Problem with Uncertain Travel Times," Transportation Science, INFORMS, vol. 48(3), pages 373-390, August.
    18. Narjes MASHHADI BANDANI & Alireza NADERI & Mohsen AKBARPOUR SHIRZAEI, 2017. "Cement Transportation Limited-Fleet Modeling And Assigning To Rated Demands," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 12(1), pages 111-123, March.
    19. Ji, Chenlu & Mandania, Rupal & Liu, Jiyin & Liret, Anne, 2022. "Scheduling on-site service deliveries to minimise the risk of missing appointment times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    20. 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.

    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:annopr:v:180:y:2010:i:1:p:125-144:10.1007/s10479-008-0487-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.