Emergency Vehicle Routing Optimization And Algorithm Based On Multi-Graph Time-Dependent Network

With the rapid deterioration of the global natural environment,a series of emergencies bring severe challenges to social stability and economic development.How to effectively deal with emergencies is a hot issue that many scholars pay attention to it.optimization of terminal distribution of emergency supplies is a key link in emergency decision-making,scientific and reasonable emergency path planning can effectively alleviate disasters and reduce losses.Therefore,this paper analyzes the different interests of disaster-stricken sites and transporters under the emergency background,considering the complexity of the emergency road network structure and the time-varying of traffic information,in-depth study of static simple graph vehicle routing problem and dynamic multiple graph vehicle routing problem,design corresponding meta-heuristic algorithms for different models,and the effectiveness of models and algorithms is verified through different types of calculation examples.the main research content of this paper includes the following aspects:(1)By referring to the existing literature to understand the current status of domestic and foreign research on vehicle routing problems and its variants,and put forward the current problems and deficiencies in this field.On this basis,for the classic vehicle routing problem with soft time windows,a firefly-ant colony hybrid algorithm is designed that combining the neighborhood search capability of the firefly algorithm and the high solution efficiency of the ant colony algorithm.(2)Due to the suddenness of emergencies,the limited rescue facilities at the initial stage of emergency often cannot cope with the heavy rescue tasks,especially in the face of large-scale,multi-disaster rescue work,there may be insufficient transport vehicles.Therefore,this paper proposes a transportation mode of joint distribution of selfowned vehicles and vehicles rented by third-party,considering the different interests between demand points and transporters,a multi-objective hybrid vehicle routing optimization model is established.In view of the good performance of the ant colony algorithm in solving large-scale problems,the non-dominated sorting strategy and variable neighborhood descent search process are introduced into the ant colony algorithm,and a multi-objective non-dominated sorting ant colony algorithm is designed.(3)Analyze the time-varying of traffic information from the perspective of time-dependent attributes,and introduce the modeling method of continuous travel time function,considering the complexity of the road network structure,multiple effective paths between two demand points are abstracted into parallel arc segments,and a multi-graph road network model is constructed.Analyze the basis for optimization of transportation routes in emergency scenarios,use the timeliness and reliability of the path to measure the quality ofthe route,and establish a bi-objective optimization model.Considering the nesting phenomenon of pareto solution set in the multi-graph structure of bi-objective optimization,a double-loop non-dominated sorting genetic algorithm is designed,and the model and algorithm are verified using some data from the Solomon example.This paper aims to explore the route decision problem in emergency scenarios,by analyzing various factors affecting the transportation process,it is clear that multi-objective optimization is more in line with people's actual decision-making psychology,and a multi-objective optimization method for emergency routes is proposed.It can provide scientific decision-making basis for decision-makers under different emergency environments.