Vehicle and drones joint distribution model and optimization algorithm in multi-mode

被引：0

作者：

Jia Z.-H. ^{[1
,2
]}

Wang S.-G. ^{[1
]}

Liu C. ^{[1
]}

机构：

[1] School of Internet, Anhui University, Hefei

[2] School of Computer Science and Technology, Anhui University, Hefei

来源：

Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 07期

关键词：

drones; genetic algorithm; last-mile distribution; routing optimization; truck-drone joint distribution;

D O I：

10.13195/j.kzyjc.2023.0349

中图分类号：

学科分类号：

摘要：

Drones have been widely utilized in logistics delivery, offering advantages of fast delivery and low cost. In this study, we propose a multi-mode vehicle-drone joint delivery model and its path optimization problem to address the needs of customers located far from the warehouse center and facing transportation limitations. This model integrates the vehicle-drone collaborative delivery and parallel delivery models, incorporating trucks equipped with drones and independent drone fleets. Building upon this model, we establish a mixed integer programming model with the objective of minimizing delivery time and design a multi-operator genetic algorithm based on knowledge learning strategies to improve search efficiency. Experimental results demonstrate that the vehicle-drone joint delivery model significantly reduces delivery time compared to traditional delivery methods. The improved genetic algorithm exhibits superior performance on large-scale datasets. The findings of this research provide guidance and reference for tackling the complex and dynamic “last-mile”problem in logistics delivery. © 2024 Northeast University. All rights reserved.

引用

页码：2125 / 2132

页数：7

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