Research On Optimization Of Cooperative Distribution Between Truck And UAV Under Urban Flood

When an emergency occurs,the key to disaster relief work is determining how to get emergency supplies to the disaster area as soon as possible.However,earthquakes,floods,and other natural disasters can cause damage to the road network in a disaster area,making it difficult for trucks to reach all affected points.Under such conditions,the introduction of new modes of distribution has significant practical implications for investigating new emergency logistics modes for disaster relief,improving distribution efficiency,and protecting people’s lives and property.This thesis begins by summarizing the research background,relevant theoretical foundation,and relevant domestic and international research review of truck-UAV collaborative distribution.It was found that existing research is mainly focused on urban logistics,and the delivery model primarily involves one truck carrying one drone in the mapping mode.Based on this,the research direction of this thesis is: research on cooperative delivery between trucks and drones carried by multiple trucks in natural disaster scenarios.Given the uncertainty of road network information in disaster areas when emergencies occur,a truck traffic restriction zone is introduced into the model,and the payload and flight time of the drone are constrained based on its own characteristics.A mixed integer programming model with the minimum arrival time at the distribution center as the target is constructed in response to the poor economy of emergency logistics and the urgency of demand.After summarizing and comparing existing metaheuristic algorithms,and a genetic algorithm is chosen to solve the problem;the precocious phenomenon that frequently occurs in genetic algorithms is improved by the elite selection method.The numerical example is analyzed after introducing the process of genetic algorithm to solve the path planning problem,and the results validate the effectiveness of the model and algorithm.Using the July 20 rainstorm in Zhengzhou as an example,first cluster the collected data from residential areas to obtain the location of the demand points in the actual calculation.Second,the demand for each demand point is calculated using the number of households in each residential area and the actual occupancy rate.The relevant data is then fed into the model for solution,and the delivery time of the most recent arrival at the distribution center is determined.When comparing delivery time to the traditional truck distribution model,the following conclusion is reached: The adoption of collaborative distribution of trucks and drones can significantly shorten the delivery time for emergency logistics in natural disasters.This study developed a collaborative distribution model of multiple trucks and multiple drones for emergency logistics,and the genetic algorithm was used for solving the model.Example calculations proved the model’s good usability.This research contributes to improving the efficiency of emergency material support in natural disasters and can also provide references for research on emergency delivery models for sudden events.