考虑三类客户点的卡车-无人机协同配送模型及混合算法  

Truck-drone Collaborative Distribution Model and Hybrid Algorithm Considering Three Types of Customer Points

作　　者：狄卫民 杨文豪 张威风 DI Wei-min;YANG Wen-hao;ZHANG Wei-feng(School of Management,Zhengzhou University,Zhengzhou,Henan 450001)

机构地区：[1]郑州大学管理学院,河南郑州450001

出　　处：《供应链管理》2024年第7期33-46,共14页SUPPLY CHAIN MANAGEMENT

摘　　要：为了提高“最后一公里”配送效率,降低配送成本,文章提出一种考虑三类客户点的卡车-无人机协同配送模式。建立以配送成本和配送时间的加权和最小化为目标的数学模型,对三类客户点在卡车-无人机协同配送路径、卡车和无人机载重、协同时间以及无人机电量方面进行约束;使用由遗传算法、K-means聚类算法与构造算法共同组成的混合算法对模型求解。大规模算例和小规模算例结果显示本文算法求解效率和求解精度较高;以配送成本和配送时间的加权和最小化为目标对比以配送成本或配送时间最小化为目标结果更优。文章提出的模型和算法能有效解决卡车-无人机协同配送问题;以配送成本和配送时间的加权和最小化为目标相较于只考虑配送成本或配送时间更合理。In order to improve the efficiency of the last-mile delivery and reduce the delivery cost,a truck-drone collaborative distribution model considering three types of customer points is proposed.This paper establishes a mathematical model with the objective of weighting and minimization of distribution cost and distribution time,and constrains on three types of customer points in terms of truck-drone collaborative distribution paths,truck and drone loads,collaborative time,and drone electric quantity;it also uses hybrid algorithm consisting of genetic algorithm,K-means clustering algorithm together with construction algorithm to solve the model.The results of large-scale and small-scale examples show that the algorithm in this paper has relatively high solution efficiency and accuracy;the objective of minimizing the weighted sum of distribution cost and distribution time is better than the objective of minimizing distribution cost or distribution time.The results illustrate that the model and algorithm proposed in this paper can effectively solve the truck-drone collaborative delivery problem;it is more reasonable to aim at minimizing the weighted sum of distribution cost and distribution time compared to considering only distribution cost or distribution time.

关 键 词：卡车-无人机协同配送 遗传算法 K-MEANS聚类算法 构造算法 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]