Research On Emergency Transportation Path Problem Based On Improved Genetic Algorithm

Looking at the human history for thousands of years,we can clearly find that natural disasters occur frequently for years,accidents occur repeatedly,and public health events cannot be eradicated.On the one hand,China has a vast territory,which is not only vulnerable to tsunamis and typhoons,but also has a large number of hidden dangers left by geological activities,leading to earthquakes,mudslides and other natural disasters occurring year after year.On the other hand,the process of global integration is accelerating,and the impact of global public health events on China is becoming more and more serious.These disasters,which are difficult to predict and cannot be prevented,not only claim too many lives each year,but also cause great damage to the national economy and even affect social development and progress.To this end,the government has set up a reasonable and efficient emergency response mechanism,striving to send emergency relief materials to hospitals and disaster areas in the shortest time and with the greatest efficiency after the occurrence of a disaster,so as to minimize the impact of the disaster.All kinds of emergency relief supplies to ensure rapid in place will depend on the first time to select the optimal emergency rescue route,however,under the background of emergency transportation route choice is not easy,should not only consider the demand of each demand point,the connectivity of the path,and considering the time constraints,the deployment of vehicles,such as the key issue.This article takes vehicle path planning under public health emergencies as the research object,and analyzes the relevant theories of vehicle path planning under emergency conditions,including the causes of emergencies and transportation Impact,China’s emergency response system and the classification and model of vehicle routing problems.Then,in view of the shortcomings of the traditional genetic algorithm,combined with the actual requirements of the emergency vehicle transportation route optimization to be solved in this paper,an improved genetic algorithm mathematical model was proposed,and combined with the Xi’an Covid-19 designated hospital as the distribution point,the demand for its medical supplies Carry out example verification with delivery,and get the best delivery route and the minimum number of vehicles required.The research in this paper can provide an effective reference for relevant units and personnel in emergency management.The mathematical model of emergency transportation route optimization designed in this paper introduces the time reward cost.Combining the time penalty cost can greatly encourage the delivery vehicles to deliver emergency materials earlier,and prevent the vehicles from delivering after the time window expires.At the same time,in view of the shortcomings of the genetic algorithm’s local optimization ability,the idea of simulated annealing algorithm is added to the genetic algorithm to ensure that the algorithm maintains good performance.In addition,this article uses a comparative analysis method to analyze the championship and roulette strategies in order to choose a strategy that is more suitable for this algorithm.At the same time,the experimental analysis method was used to determine the relevant parameters of the algorithm to verify the effectiveness of the algorithm.