IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5658-d810703.html
   My bibliography  Save this article

Fuzzy Demand Vehicle Routing Problem with Soft Time Windows

Author

Listed:
  • Tao Yang

    (College of Extended Education, Chongqing University of Education, Chongqing 400067, China)

  • Weixin Wang

    (School of International Business and Management, Sichuan International Studies University, Chongqing 400031, China)

  • Qiqi Wu

    (College of Finance and Economics, Sichuan International Studies University, Chongqing 400031, China)

Abstract

Considering the vehicle routing problem with fuzzy demand and fuzzy time windows, a vehicle routing optimization method is proposed considering both soft time windows and uncertain customer demand. First, a fuzzy chance-constrained programming model is established based on credibility theory, minimizing the total logistics cost. At the same time, a random simulation algorithm is designed to calculate the penalty cost of delivery failures caused by demand that cannot be satisfied. In order to overcome the shortcomings of GA, which easily falls into the local optimum in the process of searching, and the slow convergence speed of SA when the population is too large, a hybrid simulated annealing–genetic algorithm is adopted to improve the solution quality and efficiency. Finally, the Solomon standard example is used to verify the effectiveness of the algorithm, and the influence of decision-makers’ subjective cost preference is analyzed.

Suggested Citation

  • Tao Yang & Weixin Wang & Qiqi Wu, 2022. "Fuzzy Demand Vehicle Routing Problem with Soft Time Windows," Sustainability, MDPI, vol. 14(9), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5658-:d:810703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5658/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5658/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Saber Shiripour & Nezam Mahdavi-Amiri & Iraj Mahdavi, 2017. "A nonlinear model for location-allocation-routing problem in transportation network with intelligent travel times," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 29(3), pages 400-431.
    2. Maaike Hoogeboom & Wout Dullaert & David Lai & Daniele Vigo, 2020. "Efficient Neighborhood Evaluations for the Vehicle Routing Problem with Multiple Time Windows," Transportation Science, INFORMS, vol. 54(2), pages 400-416, March.
    3. Zheng Wang & Chunyue Zhou, 2016. "A Three-Stage Saving-Based Heuristic for Vehicle Routing Problem with Time Windows and Stochastic Travel Times," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-10, March.
    4. Nadizadeh, Ali & Hosseini Nasab, Hasan, 2014. "Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 238(2), pages 458-470.
    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. Feng, Xuehao & Song, Rui & Yin, Wenwei & Yin, Xiaowei & Zhang, Ruiyou, 2023. "Multimodal transportation network with cargo containerization technology: Advantages and challenges," Transport Policy, Elsevier, vol. 132(C), pages 128-143.

    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. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    2. Wei Wang & Li Huang & Zhaoxia Guo, 2017. "Optimization of Emergency Material Dispatch from Multiple Depot Locations to Multiple Disaster Sites," Sustainability, MDPI, vol. 9(11), pages 1-8, October.
    3. 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.
    4. Jihane El Ouadi & Hanae Errousso & Nicolas Malhene & Siham Benhadou & Hicham Medromi, 2022. "A machine-learning based hybrid algorithm for strategic location of urban bundling hubs to support shared public transport," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3215-3258, October.
    5. Zandieh, Fatemeh & Ghannadpour, Seyed Farid, 2023. "A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 685-707.
    6. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    7. Liu, Tian & Luo, Zhixing & Qin, Hu & Lim, Andrew, 2018. "A branch-and-cut algorithm for the two-echelon capacitated vehicle routing problem with grouping constraints," European Journal of Operational Research, Elsevier, vol. 266(2), pages 487-497.
    8. Jaller, Miguel & Pahwa, Anmol, 2023. "Coping with the Rise of E-commerce Generated Home Deliveries through Innovative Last-mile Technologies and Strategies," Institute of Transportation Studies, Working Paper Series qt5t76x0kh, Institute of Transportation Studies, UC Davis.
    9. Andrés Martínez-Reyes & Carlos L. Quintero-Araújo & Elyn L. Solano-Charris, 2021. "Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    10. Nasir, Jamal Abdul & Kuo, Yong-Hong, 2024. "Stochastic home care transportation with dynamically prioritized patients: An integrated facility location, fleet sizing, and routing approach," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
    11. Arjun Paul & Ravi Shankar Kumar & Chayanika Rout & Adrijit Goswami, 2021. "A bi-objective two-echelon pollution routing problem with simultaneous pickup and delivery under multiple time windows constraint," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 962-993, December.
    12. Kangye Tan & Yihui Tian & Fang Xu & Chunsheng Li, 2023. "Research on Multi-Objective Optimal Scheduling for Power Battery Reverse Supply Chain," Mathematics, MDPI, vol. 11(4), pages 1-26, February.
    13. Moshref-Javadi, Mohammad & Lee, Seokcheon, 2016. "The Latency Location-Routing Problem," European Journal of Operational Research, Elsevier, vol. 255(2), pages 604-619.
    14. Shiripour, Saber & Mahdavi-Amiri, Nezam, 2019. "Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    15. Pourya Pourhejazy & Oh Kyoung Kwon, 2016. "The New Generation of Operations Research Methods in Supply Chain Optimization: A Review," Sustainability, MDPI, vol. 8(10), pages 1-23, October.
    16. Weiwei Chen & Maozeng Xu & Qingsong Xing & Ligang Cui & Liudan Jiao, 2020. "A Fuzzy Demand-Profit Model for the Sustainable Development of Electric Vehicles in China from the Perspective of Three-Level Service Chain," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    17. Özarık, Sami Serkan & Veelenturf, Lucas P. & Woensel, Tom Van & Laporte, Gilbert, 2021. "Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    18. Fei Peng & Xian Fan & Puxin Wang & Mingan Sheng, 2022. "A Time-Space Network-Based Optimization Method for Scheduling Depot Drivers," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
    19. Zhang, Bo & Li, Hui & Li, Shengguo & Peng, Jin, 2018. "Sustainable multi-depot emergency facilities location-routing problem with uncertain information," Applied Mathematics and Computation, Elsevier, vol. 333(C), pages 506-520.
    20. Vincent F. Yu & Grace Aloina & Hadi Susanto & Mohammad Khoirul Effendi & Shih-Wei Lin, 2022. "Regional Location Routing Problem for Waste Collection Using Hybrid Genetic Algorithm-Simulated Annealing," Mathematics, MDPI, vol. 10(12), pages 1-23, June.

    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:jsusta:v:14:y:2022:i:9:p:5658-:d:810703. 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.