IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v204y2023icp28-42.html
   My bibliography  Save this article

Route optimization in township logistics distribution considering customer satisfaction based on adaptive genetic algorithm

Author

Listed:
  • Cui, Huixia
  • Qiu, Jianlong
  • Cao, Jinde
  • Guo, Ming
  • Chen, Xiangyong
  • Gorbachev, Sergey

Abstract

With the development of the logistics economy, problems such as the timeliness of logistics distribution and the high cost of distribution have emerged. A new adaptive genetic algorithm is proposed to solve these problems. The pc and pm values of the algorithm are related to the number of iterations and the individual fitness values. To improve the local optimization ability of the algorithm, a large neighborhood search algorithm is proposed. In addition, this study establishes a soft time window town logistics distribution model with constraints. The model considers the optimal cost as the objective function and customer satisfaction as the influencing factor. In the experiment, the proposed adaptive genetic algorithm is compared with the traditional genetic algorithm, validating the effectiveness of the proposed algorithm.

Suggested Citation

  • Cui, Huixia & Qiu, Jianlong & Cao, Jinde & Guo, Ming & Chen, Xiangyong & Gorbachev, Sergey, 2023. "Route optimization in township logistics distribution considering customer satisfaction based on adaptive genetic algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 204(C), pages 28-42.
    • Handle: RePEc:eee:matcom:v:204:y:2023:i:c:p:28-42
    DOI: 10.1016/j.matcom.2022.05.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475422002087
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2022.05.020?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. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    2. Brian Kallehauge & Jesper Larsen & Oli B.G. Madsen & Marius M. Solomon, 2005. "Vehicle Routing Problem with Time Windows," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 67-98, Springer.
    3. Diego Cattaruzza & Nabil Absi & Dominique Feillet & Jesús González-Feliu, 2017. "Vehicle routing problems for city logistics," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 51-79, March.
    4. Wang, Minxi & Wang, Yajie & Liu, Wei & Ma, Yu & Xiang, Longtao & Yang, Yunqi & Li, Xin, 2021. "How to achieve a win–win scenario between cost and customer satisfaction for cold chain logistics?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    5. David Pisinger & Stefan Ropke, 2010. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 399-419, Springer.
    6. Zonggui Tian & Ray Y. Zhong & Ali Vatankhah Barenji & Y. T. Wang & Zhi Li & Yiming Rong, 2021. "A blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 2229-2249, April.
    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. Thibaut Vidal & Rafael Martinelli & Tuan Anh Pham & Minh Hoàng Hà, 2021. "Arc Routing with Time-Dependent Travel Times and Paths," Transportation Science, INFORMS, vol. 55(3), pages 706-724, May.
    2. Arpan Rijal & Marco Bijvank & Asvin Goel & René de Koster, 2021. "Workforce Scheduling with Order-Picking Assignments in Distribution Facilities," Transportation Science, INFORMS, vol. 55(3), pages 725-746, May.
    3. Anderluh, Alexandra & Nolz, Pamela C. & Hemmelmayr, Vera C. & Crainic, Teodor Gabriel, 2021. "Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics," European Journal of Operational Research, Elsevier, vol. 289(3), pages 940-958.
    4. Zheng Zhang & Bin Ji & Samson S. Yu, 2023. "An Adaptive Tabu Search Algorithm for Solving the Two-Dimensional Loading Constrained Vehicle Routing Problem with Stochastic Customers," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    5. El Mehdi, Er Raqabi & Ilyas, Himmich & Nizar, El Hachemi & Issmaïl, El Hallaoui & François, Soumis, 2023. "Incremental LNS framework for integrated production, inventory, and vessel scheduling: Application to a global supply chain," Omega, Elsevier, vol. 116(C).
    6. 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.
    7. Véronique François & Yasemin Arda & Yves Crama, 2019. "Adaptive Large Neighborhood Search for Multitrip Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 53(6), pages 1706-1730, November.
    8. 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.
    9. Pani, Agnivesh & Mishra, Sabya & Sahu, Prasanta, 2022. "Developing multi-vehicle freight trip generation models quantifying the relationship between logistics outsourcing and insourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    10. 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.
    11. 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).
    12. 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.
    13. Majid Eskandarpour & Pierre Dejax & Olivier Péton, 2019. "Multi-Directional Local Search for Sustainable Supply Chain Network Design," Post-Print hal-02407741, HAL.
    14. Feng Li & Zhi-Ping Fan & Bing-Bing Cao & Xin Li, 2020. "Logistics Service Mode Selection for Last Mile Delivery: An Analysis Method Considering Customer Utility and Delivery Service Cost," Sustainability, MDPI, vol. 13(1), pages 1-22, December.
    15. Julia Rieck & Jürgen Zimmermann, 2010. "A new mixed integer linear model for a rich vehicle routing problem with docking constraints," Annals of Operations Research, Springer, vol. 181(1), pages 337-358, December.
    16. Frómeta Moya, Jorge Israel & Pérez Campos, Javier de Jesús, 2021. "Modelo heurístico híbrido para el ruteo vehicular y manejo de inventario en una entidad comercializadora de combustibles. || Hybrid heuristic model for inventory routing management in a fuel comercial," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 31(1), pages 363-383, June.
    17. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
    18. Daniela Guericke & Leena Suhl, 2017. "The home health care problem with working regulations," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 977-1010, October.
    19. Guido, Rosita & Groccia, Maria Carmela & Conforti, Domenico, 2018. "An efficient matheuristic for offline patient-to-bed assignment problems," European Journal of Operational Research, Elsevier, vol. 268(2), pages 486-503.
    20. Martina Fischetti & Michele Monaci, 2016. "Proximity search heuristics for wind farm optimal layout," Journal of Heuristics, Springer, vol. 22(4), pages 459-474, August.

    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:matcom:v:204:y:2023:i:c:p:28-42. 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.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.