Optimization Of Bus Dispatching Under The Influence Of Interval Overlap

2020 is the closing year for China to build a moderately prosperous society in an all-round way,and people’s happiness index will greatly improve.Although the current international environment is not satisfactory,China’s economic development is in the ascendant.Cities are the center of economic development,and the population is constantly converging from rural to urban areas.As the existing urban space is limited,the population density has greatly increased,and people experience more and more traffic congestion when they travel in daily life,work,and life.Serious.The huge population of China determines that China urgently needs to develop the construction of public transportation,and public transportation plays an important role in the development and construction of China’s cities.With the government’s attention and support to the construction of public transportation in recent years,the scope of the construction of the public transportation network has gradually improved,allowing more people to enjoy great convenience when taking public transportation.However,under the circumstance that the number of bus lines continues to be dense and increasing,the problem of wasting capacity resources caused by the operation of multiple bus lines in the same operating section has also arisen.Based on this,this paper considers the conditions of multiple bus lines operating in the same section at the same time,establishes an optimization model of bus departure interval,uses an improved genetic algorithm to solve the model,and uses vehicle and passenger data obtained from multiple bus lines in Lanzhou,To verify the validity of the model.Based on this,this paper considers the conditions of multiple bus lines operating in the same section at the same time,establishes an optimization model of bus departure interval,uses an improved genetic algorithm to solve the model,and uses vehicle and passenger data obtained from multiple bus lines in Lanzhou,To verify the validity of the model.This article first conducts a detailed study of the existing research on bus dispatching.Most of the research focuses on the establishment of models for the smallest passenger travel costs or the largest bus company revenue,and single or hybrid heuristic algorithms are used to solve the models.Domestic scholars’ research on bus dispatching focuses on the optimization of bus dispatching for a single line.Multi-line bus dispatching considering the overlapping characteristics of intervals is rarely involved.This paper determines that the collaborative dispatching of multiple bus lines operating in the same interval is the research object.By analyzing the movement process of the bus from the departure station to passing through each station,the travel cost classification of whether passengers travel in overlapping sections,and the composition of the operating cost of the bus company,the weight coefficient is introduced,and the second waiting of passengers is also considered Establish a bus dispatch optimization model with the bus departure interval as the optimization variable,and the minimum sum of passenger travel time cost and bus company operating cost as the optimization goal.The coding method and genetic operation in the traditional genetic algorithm are improved to improve the accuracy and convergence speed of the algorithm,and the improved genetic algorithm is applied to the solution of the model.This article first conducts a detailed study of the existing research on bus dispatch,summarizes the contributions made by scholars at home and abroad in the field of bus dispatch,summarizes the shortcomings in the existing research,and determines that multiple bus lines run in the same interval.Cooperative scheduling is the research object.After that,the theory and classification of bus dispatching and the data acquisition methods required for bus dispatching are introduced,and the impact of multiple bus lines running in overlapping sections is qualitatively analyzed.By analyzing the movement process of the bus from the departure station to passing through each station,the travel cost classification of whether passengers travel in overlapping sections,and the composition of the operating cost of the bus company,the weight coefficient is introduced,and the passenger’s second waiting situation is also considered Establish a bus dispatch optimization model with the bus departure interval as the optimization variable,and the minimum sum of passenger travel time cost and bus company operating cost as the optimization goal.The coding method and genetic operation in the traditional genetic algorithm are improved to improve the accuracy and convergence speed of the algorithm,and the improved genetic algorithm is applied to the solution of the model.Finally,this paper investigates the vehicle data and line passenger flow data of the 126,137,and 149 buses in Lanzhou City,organizes the acquired data,and uses the Matlab program to solve the model according to the established bus scheduling optimization model.Comparing the results obtained with the current dispatch results,the total travel time of passengers was reduced by 3.9%,and the total cost was reduced by 3.7%.The optimized bus departure timetable is given,which proves the veracity of the model.