The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
A novel mobile charging service that utilizes vehicle-to-vehicle(V2V)charging technology has recently been proposed as a supplement to fixed charging infrastructure(CI),enabling electric vehicles(EVs)to exchange elect...A novel mobile charging service that utilizes vehicle-to-vehicle(V2V)charging technology has recently been proposed as a supplement to fixed charging infrastructure(CI),enabling electric vehicles(EVs)to exchange electricity.This study formulates a vehicle routing problem(VRP)of vehicle-to-vehicle(V2V)charging,optimizing the routing of discharging vehicles(DVs)to service recharging vehicles(RVs)while taking into account their willingness to join the V2V charging platform.A mixed integer linear programming(MILP)model is established to optimize the VRP-V2V(i.e.the VRP of V2V charging),which is known to be NP-hard.To solve large-scale instances for real-world applications,we propose an adaptive large neighbourhood search(ALNS)algorithm,which,when combined with the structure of the VRP-V2V problem,utilizes four local search procedures to enhance solution quality following destroy-and-repair operators.Results indicate that the proposed ALNS algorithm outperforms the optimization solver CPLEX in small-scale instances,and can solve large-scale instances that are unfeasible using the CPLEX solver.In a numerical analysis of Changsha’s large-scale network,we demonstrate that the V2V platform can save an average of 33.1%on the charging cost of RVs,hence raising customer satisfaction with charging services and reducing range anxiety.The platform’s profitability is also increased by using V2V charging in areas lacking fixed CI.展开更多
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金funded by the National Natural Science Foundation of China(Grant No.72201281)the Natural Science Foundation of Hunan Province,China(Grant No.2023JJ40781).
文摘A novel mobile charging service that utilizes vehicle-to-vehicle(V2V)charging technology has recently been proposed as a supplement to fixed charging infrastructure(CI),enabling electric vehicles(EVs)to exchange electricity.This study formulates a vehicle routing problem(VRP)of vehicle-to-vehicle(V2V)charging,optimizing the routing of discharging vehicles(DVs)to service recharging vehicles(RVs)while taking into account their willingness to join the V2V charging platform.A mixed integer linear programming(MILP)model is established to optimize the VRP-V2V(i.e.the VRP of V2V charging),which is known to be NP-hard.To solve large-scale instances for real-world applications,we propose an adaptive large neighbourhood search(ALNS)algorithm,which,when combined with the structure of the VRP-V2V problem,utilizes four local search procedures to enhance solution quality following destroy-and-repair operators.Results indicate that the proposed ALNS algorithm outperforms the optimization solver CPLEX in small-scale instances,and can solve large-scale instances that are unfeasible using the CPLEX solver.In a numerical analysis of Changsha’s large-scale network,we demonstrate that the V2V platform can save an average of 33.1%on the charging cost of RVs,hence raising customer satisfaction with charging services and reducing range anxiety.The platform’s profitability is also increased by using V2V charging in areas lacking fixed CI.
