Research On The Method For Cooperative Logistics Scheduling Of Multi-vehicle And Multi-drone

With the rapid development of e-commerce,the diversified demand of logistics is growing gradually.The outbreak of COVID-19 has also accelerated the transformation of logistics distribution mode.Therefore,a new logistics model with drone as a distribution tool emerges,which provides a new solution for intelligent logistics.Due to the limitations of drone platform,this thesis adopts the logistics mode of multivehicle and multi-drone cooperation to realize the complementary advantages of vehicle and drone distribution.According to the actual demand of logistics and the existing situation of drone technology,this thesis analyzed the multi-vehicle and multi-drone cooperated logistics scheduling system,focusing on the collaborative routing planning of multivehicle and multi-drone.Based on the background of terminal logistic distribution,this thesis focuses on the model and solution of multi-vehicle and multi-drone cooperated logistic scheduling.The main contributions are as follows:(1)To make the collaborative logistic of vehicle and drone applied in practice,the details of collaborative logistic model of vehicle and drone are analyzed in the thesis.The collaborative logistic model considers the synchronization way of vehicle and drone,the flight process and delivery modes of drone,the launch and recovery technology of drone and application scenarios.Aimed at minimizing the makespan,the vehicle and drone cooperated logistics scheduling system is analyzed,which plans the scheduling process from placing orders to parcel receipt in detail.The cooperated logistics scheduling system is conducive to the rapid generation of collaborative routes under complex demand,so as to provide real-time task planning.(2)For small-scale logistics distribution,the collaborative routing planning of single-vehicle and single-drone is proposed and a mixed integer programming model is established.To solve the small-scale distribution problem,this thesis presented a heuristic based on maximum saving.The heuristic generates the vehicle route by ant colony algorithm in the first stage,and inserts the drone serving nodes by maximum saving rule in the second stage.To test the effectiveness of the heuristic in the small-scale,the experiments are designed.Additionally,the comparison experiments demonstrate that the collaborative distribution is more superior than the traditional truck distribution.(3)To optimize the collaborative logistics model,this thesis proposed the collaborative routing planning of multi-vehicle and multi-drone and provided a mathematical model.Due to the complexity of the problem,this thesis innovatively proposed an improved variable neighborhood descent(IVND).According to “clustered first,route second”,the algorithm integrated variable neighborhood search with the Metropolis acceptance criterion and tabu list to avoid repeated operations and falling into the local optimality easily.The comparison experiment of logistic models proves that the collaborative distribution can save about 30% time for traditional truck distribution.Additionally,the experimental results of comparing algorithms show that the IVND can provide an efficient solution for the collaborative routing planning of multi-vehicle and multi-drone in a short time.The parameter analysis and practical experiments also prove the robustness and practicability of the IVND.(4)To satisfy the return & exchange demand of customers,the collaborative routing planning of multi-vehicle and multi-drone with simultaneous pickup and delivery,integrating the forward logistics(delivery goods)and reverse logistics(return goods).We formulated a mathematical model and proposed an adaptive large-scale neighborhood search(ALNS),which applies the Saving algorithm and Nearest Neighbor to generates the initial solution.Experiments on different scales are conducted,and the experimental results show the superior effectiveness and convergence of the ALNS.Moreover,the practicability of the ALNS is demonstrated in the practical experiment.The research results can provide theoretical and technical support for the application of drone in logistics distribution.The research also further promotes the development of the intelligent logistics.There are 83 figures,18 tables and 108 references.