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Research on Coordination and Optimization of Order Allocation and Delivery Route Planning in Take-Out System

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  • Guofeng Sun
  • Zhiqiang Tian
  • Renhua Liu
  • Yun Jing
  • Yawen Ma

Abstract

This paper studies the take-out route delivery problem (TRDP) with order allocation and unilateral soft time window constraints. The TRDP considers the order allocation and delivery route optimization in the delivery service process. The TRDP is a challenging version of vehicle routing problem. In order to solve this problem, this paper aims to minimize the total cost of delivery, builds an optimization model of this problem by using cumulative time, and adds time dimension in order allocation and path optimization dimensions. It can not only track the real-time location of delivery personnel but also record the delivery personnel to perform a certain task. The main algorithm is the dynamic allocation algorithm designed from the perspective of dispatch efficiency, and the subalgorithm is the improved genetic algorithm. Finally, some experiments are designed to verify the effectiveness of the established model and the designed algorithm, the order allocation and route optimization are calculated with/without the consideration of traffic jam, and the results show that the algorithm can generate better solution in each scene.

Suggested Citation

  • Guofeng Sun & Zhiqiang Tian & Renhua Liu & Yun Jing & Yawen Ma, 2020. "Research on Coordination and Optimization of Order Allocation and Delivery Route Planning in Take-Out System," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-16, July.
    • Handle: RePEc:hin:jnlmpe:7248492
    DOI: 10.1155/2020/7248492
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    Cited by:

    1. Tian, Yuan & Han, Minghao & Kulkarni, Chetan & Fink, Olga, 2022. "A prescriptive Dirichlet power allocation policy with deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 224(C).

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