Fleet resupply by drones for last-mile delivery

卡车 无人机 计算机科学 车辆路径问题 整数规划 运筹学 布线(电子设计自动化) 运输工程 工程类 汽车工程 计算机网络 算法 遗传学 生物
作者
Juan C. Pina-Pardo,Daniel F. Silva,Alice E. Smith,Ricardo A. Gatica
出处
期刊:European Journal of Operational Research [Elsevier BV]
卷期号:316 (1): 168-182 被引量:3
标识
DOI:10.1016/j.ejor.2024.01.045
摘要

The Vehicle Routing Problem with Release Dates and Drone Resupply consists of routing a fleet of trucks to deliver orders that arrive at a depot over time. During the delivery horizon, the trucks can return to the depot to collect newly arrived orders, or these orders can be resupplied to the trucks along their routes via drones dispatched from the depot. A Mixed-Integer Linear Programming (MILP) formulation is developed for the version of the problem where order arrival times at the depot (generally termed order release dates) are known beforehand. To address large-size instances, we devise a unified matheuristic approach that provides high-quality solutions for both the truck-and-drone and the truck-only versions of the problem. In this approach, truck routes are iteratively modified using a tabu search scheme, where a subordinate fast MILP model defines optimal loading operations (truck depot returns and drone resupplies) for promising truck routes. We perform extensive numerical experiments with instances of up to 100 customers. Results show the effectiveness of the matheuristic approach for solving both the truck-and-drone and the truck-only versions of the problem. We also show the benefits of drone resupply to reduce completion times and the number of times the trucks need to return to the depot to collect newly released orders. Furthermore, we provide several managerial insights regarding fleet utilization and consolidation.
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