Vehicle and drones joint distribution model and optimization algorithm in multi-mode
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.
truck-drone joint distributionrouting optimizationdronesgenetic algorithmlast-mile distribution
NETL
NSTL
万方数据
