TY - GEN
T1 - A Multi-objective Task-Driven Vehicle Routing Problem with Recirculating Delivery and its Solution Approaches
AU - Wang, Lei
AU - Meng, Fanchao
AU - Min, Xiaochuan
AU - Chu, Dianhui
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/28
Y1 - 2021/5/28
N2 - The task-driven vehicle routing problem with recirculating delivery (TDVRPRD) is similar to the expansion of the multi-objective multi-depot vehicle routing problem with time windows. Applied to the characteristics of large quantities of orders and high frequency round trip in real express delivery, the important problem is how to match task orders with delivery vehicles and make reasonable path planning for delivery vehicles. In this paper, we establish a task-driven vehicle recirculating distribution model with multi objectives of minimizing the total cost and maximizing the total profit of distribution, propose the heuristic algorithm and variable neighborhood search algorithm respectively for the existing traditional single delivery and recirculating delivery. The four algorithms are compared and tested for the simulation experimental data. We present a variety of results showing that the task-driven vehicle recirculating distribution model has strong superiority under weak time constraints, and the specific variable neighborhood search algorithm has high search quality and stability.
AB - The task-driven vehicle routing problem with recirculating delivery (TDVRPRD) is similar to the expansion of the multi-objective multi-depot vehicle routing problem with time windows. Applied to the characteristics of large quantities of orders and high frequency round trip in real express delivery, the important problem is how to match task orders with delivery vehicles and make reasonable path planning for delivery vehicles. In this paper, we establish a task-driven vehicle recirculating distribution model with multi objectives of minimizing the total cost and maximizing the total profit of distribution, propose the heuristic algorithm and variable neighborhood search algorithm respectively for the existing traditional single delivery and recirculating delivery. The four algorithms are compared and tested for the simulation experimental data. We present a variety of results showing that the task-driven vehicle recirculating distribution model has strong superiority under weak time constraints, and the specific variable neighborhood search algorithm has high search quality and stability.
KW - recirculating delivery
KW - task-driven
KW - variable neighborhood search algorithm
KW - vehicle routing problem
UR - https://www.scopus.com/pages/publications/85113733847
U2 - 10.1109/ICAIBD51990.2021.9459022
DO - 10.1109/ICAIBD51990.2021.9459022
M3 - 会议稿件
AN - SCOPUS:85113733847
T3 - 2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021
SP - 687
EP - 694
BT - 2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021
Y2 - 28 May 2021 through 31 May 2021
ER -