Transit Network Design For Urban And Suburb Based On Artificail Bee Colony Algorithm

The key to the optimization of the transit network is essentially to determine the set of bus stops for each line according to the given number of bus lines,and then to determine the sequences of the bus stops according to the determined bus stop set.The corresponding freuqncy should be set according to the assigned flow on each line.Curently,many studies focus on transit network optimization in the main urban area.However,few studies consider travel demand from suburbs to urban areas and how to design the effective transit network.In fact,due to the division of urban functions,the daily passenger traffic between urban and suburbs increase rapidly,suburban transit network is becoming more and more important,and have become an organic part of city transit nwtwork.Therefore,how to optimize the design of the transit nwtwork for urban and suburb has become an urgent problem.Based on this,this paper draws on the conventional conventional transit network optimization design model,extends and improves the model on this basis,builds a suburban bus line network optimization model.According to the constructed model,the corresponding solving algorithm and the actual case were used to solve the problem.The results show that the proposed method can significantly reduce the total travel time of passengers.The main research contents are as follows:Firstly,According to the conventional transit network model,an optimization model of the urban and suburban transit network based on the passenger perspective was constructed.Among them,the variables of the optimized transit network structure include the stop sequence of each line and the number of the final station that is the passenger flow gathering point.According to the tranist network structure,the passenger capacity constraint conditions are used to obtain the number of vehicles equipped for each line.The best network layout plan can be obtained in this way.Then,According to the constructed model,a two-stage model solving algorithm is proposed.In the first stage,K-means clustering algorithm is used to obtain the stop set of each line.In the second stage,based on the stop set of each line,the bee colony algorithm is used to further optimize the direction of bus routes and passenger flow gather stops.Among them,the bee colony algorithm designs three different neighborhood search methods for the tranist network to improve the efficiency of neighborhood search.Finally,Take the urban and suburban transit network in Tin Shui Wai,Hong Kong as an example,and use the constructed suburban bus network model and solving algorithm to optimize the existing bus services.The optimization results show that the proposed method can significantly reduce the travel time of passengers.And further analyzed the impact of the number of different circle lines on the final optimization results.