Vehicle and Drone Collaborative Transportation Route Planning Based on GALNS
In the aftermath of earthquakes,road damage hampers the urgent transportation of emergency supplies.This paper aims to minimize total costs by establishing a collaborative truck and drone transport model for disrupted roads.An adaptive variable neighborhood genetic algorithm(GALNS)is designed,integrating genetic and adaptive large neighborhood search algorithms.Simulations comparing GALNS with GA,PSO,and ALNS show that GALNS re-duces vehicle travel distance by 24.1％,20.32％,and 11.63％.Total time by 38.9％,31.43％,and 20.37％.And total cost by 36.07％,28.4％,and 18.7％,respectively.GALNS outperforms others in convergence speed and results,provid-ing effective cost reduction,better route planning,and time savings for disaster relief transportation.The findings offer guidance for efficient transport of emergency supplies during earthquakes or other natural disasters.
collaborative transportationroute planninggenetic algorithmadaptive large neighborhood search algorithm
万方数据
维普
