Optimisation Modelling and Reinforcement Learning of Bus Routes Based on Raster Approach
The wiring and optimisation of bus routes has always been an extremely important part of urban planning and construction,and at present,in Shanghai,this work is downgraded to the district-level construction and trans-portation committees to implement,but the implementation of this work is not only labor-intensive,but also often lacks scientific nature,and fails to meet the travel needs of residents.In response to this practical problem,the bus route is divided into the two parts of site selection and route generation.Firstly,the regional map and all kinds of data are quantitatively modeled by raster method,and the optimal distribution of bus stops is generated by processing all kinds of data affecting the distribution of bus stops with MATLAB.Then,a group of optimal bus routes is generated through genetic algorithm by using Python,and the running speed is optimized by using reinforcement learning algo-rithm.Thus,the scientific routing optimization of bus lines in the region is realized,and the efficiency of related work is improved.
万方数据
维普
