Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (6A): 250900105-9.doi: 10.11896/jsjkx.250900105

• Artificial Intelligence • Previous Articles     Next Articles

Research on Cooperative Trajectory Optimization of Multi-truck-UAV System Based on UAV Exchange

JIN Kehan, JIA Riheng   

  1. College of Computer Science and Technology,Zhejiang Normal University,Jinhua,Zhejiang 321004,China
  • Online:2026-06-16 Published:2026-06-12
  • About author:JIN Kehan,born in 2001,postgraduate.His main research interest is the path optimization problem of unmanned aerialvehicles.
    JIA Riheng,born in 1989,Ph.D asso-ciate professor.His main research in-terests include the Internet of Things,wireless rechargeable sensor networks,unmanned aerial vehicle networks,and reinforcement learning.

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Abstract: For the last-mile delivery logistics,a novel synchronous truck-drone routing problem is proposed.The framework is extended by introducing two innovative mechanisms:a drone-swapping mechanism that allows drones to be launched and retrieved by different trucks;and a dynamic waiting mechanism that enables trucks to wait at customer nodes for optimal drone retrieval.These mechanisms improve the flexibility of routing and delivery efficiency.The problem is formulated as a multi-objective mixed-integer linear programming problem,aiming to minimize the total transportation cost,maximize customer satisfaction through timely delivery,and optimize the makespan.The genetic algorithm(GA) is improved and compared with three meta-heuristic algorithms,namely the simulated annealing algorithm(SA),the adaptive large-neighborhood search algorithm(ALNS),and the ant-colony optimization algorithm(ACO).Experimental results show that compared with the traditional fixed truck-drone model,the new mechanisms significantly improve the cost,satisfaction,and time metrics(with an optimization degree of 5%~15%).Comparative analysis highlights the advantages of the improved genetic algorithm,which shows excellent adaptability to the new mechanisms.The research results emphasize the potential of flexible drone-truck collaboration in efficient last-mile logistics.

Key words: Unmanned aerial vehicle, Urban logistics, Collaborative trajectory optimization, Multi-objective optimization problem, Genetic algorithm

CLC Number: 

  • TP301
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