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Dynamic Vehicle Routing Problem with Fuzzy Customer Response

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  • Gitae Kim

    (Department of Industrial Management Engineering, Hanbat National University, Daejeon 34158, Republic of Korea)

Abstract

This paper proposes a dynamic vehicle routing problem (DVRP) model with fuzzy customer responses and suggests optimal routing strategies. Most DVRP studies have focused on how to create a new route upon the occurrence of dynamic situations such as unexpected demands. However, the customer responses have received little attention. When a pop-up demand is added to one of the planned routes, the service for some optimally planned demands may be delayed. Customers may file complaints or cancel their orders as a result of the delays. As a result, the customer response has a significant impact on current profits as well as future demands. In this research, we consider the customer response in DVRP and address it with a fuzzy number. Changing distances or defining time windows can resolve the problem of customer response. The customer responses are represented by a fuzzy rule. The new routing strategy provides the viability to reduce customer complaints and avoid losing potential customers.

Suggested Citation

  • Gitae Kim, 2023. "Dynamic Vehicle Routing Problem with Fuzzy Customer Response," Sustainability, MDPI, vol. 15(5), pages 1-13, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4376-:d:1084378
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    References listed on IDEAS

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    1. Harilaos N. Psaraftis, 1980. "A Dynamic Programming Solution to the Single Vehicle Many-to-Many Immediate Request Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 14(2), pages 130-154, May.
    2. Jingling Zhang & Wanliang Wang & Yanwei Zhao & Carlo Cattani, 2012. "Multiobjective Quantum Evolutionary Algorithm for the Vehicle Routing Problem with Customer Satisfaction," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-19, December.
    3. Dimitris J. Bertsimas & Garrett van Ryzin, 1993. "Stochastic and Dynamic Vehicle Routing in the Euclidean Plane with Multiple Capacitated Vehicles," Operations Research, INFORMS, vol. 41(1), pages 60-76, February.
    4. Zhi-Long Chen & Hang Xu, 2006. "Dynamic Column Generation for Dynamic Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 40(1), pages 74-88, February.
    5. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    6. Zhang, Jian & Luo, Kelin & Florio, Alexandre M. & Van Woensel, Tom, 2023. "Solving large-scale dynamic vehicle routing problems with stochastic requests," European Journal of Operational Research, Elsevier, vol. 306(2), pages 596-614.
    7. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    8. Jian Yang & Patrick Jaillet & Hani Mahmassani, 2004. "Real-Time Multivehicle Truckload Pickup and Delivery Problems," Transportation Science, INFORMS, vol. 38(2), pages 135-148, May.
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