IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/117513.html
   My bibliography  Save this paper

Layer: An Alternative Approach To Solve Large Capacitated Vehicle Routing Problem with Time Window Using AI and Exact Method

Author

Listed:
  • Mukherjee, Krishnendu

Abstract

To the best of my knowledge, this problem has never been addressed by any researcher. This paper studies the effect of K-means, the Gaussian Mixture Model (GMM), and the integrated use of autoencoder and K-means on the computational time, MIP gap, feasible route, subtour, and the optimum use of vehicles. Miller-Tucker-Zemlin (MTZ) subtour elimination constraint is considered in this regard. This paper also gives the concept of a “layer”, which could be effective to solve a large vehicle routing problem with a time window (VRPTW) quickly.

Suggested Citation

  • Mukherjee, Krishnendu, 2023. "Layer: An Alternative Approach To Solve Large Capacitated Vehicle Routing Problem with Time Window Using AI and Exact Method," MPRA Paper 117513, University Library of Munich, Germany, revised 12 Jun 2023.
    • Handle: RePEc:pra:mprapa:117513
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/117513/1/An%20Integrated%20Approach%20of%20Machine%20Learning%20and%20Mixed%20Integer%20Linear%20Program%20to%20Solve%20Large%20VRPTW%20Problem.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. JANSSENS, Jochen & DE CORTE, Annelies & SÖRENSEN, Kenneth, 2016. "Water distribution network design optimisation with respect to reliability," Working Papers 2016007, University of Antwerp, Faculty of Business and Economics.
    2. Bach, Lukas & Hasle, Geir & Schulz, Christian, 2019. "Adaptive Large Neighborhood Search on the Graphics Processing Unit," European Journal of Operational Research, Elsevier, vol. 275(1), pages 53-66.
    3. Martins, Sara & Ostermeier, Manuel & Amorim, Pedro & Hübner, Alexander & Almada-Lobo, Bernardo, 2019. "Product-oriented time window assignment for a multi-compartment vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 276(3), pages 893-909.
    4. SteadieSeifi, M. & Dellaert, N.P. & Nuijten, W. & Van Woensel, T., 2017. "A metaheuristic for the multimodal network flow problem with product quality preservation and empty repositioning," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 321-344.
    5. He, Dongdong & Guan, Wei, 2023. "Promoting service quality with incentive contracts in rural bus integrated passenger-freight service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    6. Jone R. Hansen & Kjetil Fagerholt & Magnus Stålhane & Jørgen G. Rakke, 2020. "An adaptive large neighborhood search heuristic for the planar storage location assignment problem: application to stowage planning for Roll-on Roll-off ships," Journal of Heuristics, Springer, vol. 26(6), pages 885-912, December.
    7. 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.
    8. Li, Yuan & Chen, Haoxun & Prins, Christian, 2016. "Adaptive large neighborhood search for the pickup and delivery problem with time windows, profits, and reserved requests," European Journal of Operational Research, Elsevier, vol. 252(1), pages 27-38.
    9. Chen, Enming & Zhou, Zhongbao & Li, Ruiyang & Chang, Zhongxiang & Shi, Jianmai, 2024. "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    10. Raeesi, Ramin & Zografos, Konstantinos G., 2020. "The electric vehicle routing problem with time windows and synchronised mobile battery swapping," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 101-129.
    11. Timo Hintsch, 2019. "Large Multiple Neighborhood Search for the Soft-Clustered Vehicle-Routing Problem," Working Papers 1904, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    12. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.
    13. Ulrike Ritzinger & Jakob Puchinger & Richard Hartl, 2016. "Dynamic programming based metaheuristics for the dial-a-ride problem," Annals of Operations Research, Springer, vol. 236(2), pages 341-358, January.
    14. Vadlamani, Satish & Hosseini, Seyedmohsen, 2014. "A novel heuristic approach for solving aircraft landing problem with single runway," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 144-148.
    15. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    16. Timo Gschwind & Michael Drexl, 2016. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Working Papers 1624, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    17. 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.
    18. Paul Czioska & Ronny Kutadinata & Aleksandar Trifunović & Stephan Winter & Monika Sester & Bernhard Friedrich, 2019. "Real-world meeting points for shared demand-responsive transportation systems," Public Transport, Springer, vol. 11(2), pages 341-377, August.
    19. Zhang, Ruijuan & Dai, Ying & Yang, Fei & Ma, Zujun, 2024. "A cooperative vehicle routing problem with delivery options for simultaneous pickup and delivery services in rural areas," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    20. M A Krajewska & H Kopfer & G Laporte & S Ropke & G Zaccour, 2008. "Horizontal cooperation among freight carriers: request allocation and profit sharing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1483-1491, November.

    More about this item

    Keywords

    Machine Learning; Deep Learning; Mixed Integer Linear Program; and Large VRPTW;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:117513. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.