The Research On Urban Dispatching Optimization Problem Of Qingdao Pure Electric Bus

The issue of urban pollution has received wide attention from all walks of life.The development of new energy sources and the conversion of old and new energy sources have also been put on the agenda.The new energy vehicle industry generated from this is also growing and playing an increasingly important role in improving the environment.Its advantages such as low noise,smooth operation and zero emission have been accepted by the general public and become more and more important in the daily travel of citizens.However,how to make better use of pure electric buses,give reasonable operation time and efficiency,and make them exert greater urban operation value is a subject worthy of attention and research by the government and academic circles,while further optimizing the scheduling of pure electric buses is the top priority of this subject.Whether it is the choice of charging mode of pure electric bus,determination of driving distance,collection of passenger flow,scheduling schedule,etc.,all of which are indispensable important contents in the study of pure electric bus scheduling,which is of great significance for the further sustainable development of the industry.In this paper,the relevant research on pure electric buses at home and abroad is firstly sorted out,including bus passenger flow demand,single-objective and multi-objective starting frequency optimization,etc.,and further comparative analysis is made on different charging modes and driving range of pure electric buses at home and abroad.Then this article by IC card and GPS time synchronization of data,matching to the delicious data and corresponding site,to minimize cost and maximize returns for the principle,with start time to replace the traditional interval variables,and build a pure electric bus multi-objective optimization model of vehicle scheduling,and based on the improved genetic simulated annealing algorithm to model.In the end,taking no.363 bus in Qingdao city as an example,the paper analyzed and tested according to the optimization model set in this paper,and made full use of the passenger flow data collected by IC card and GPS to obtain a more reasonable starting schedule of no.363 pure electric public vehicle.