Abstract
Abstract. With the advancement of urbanization, urban-rural public transport issues have become one of the most critical issues in urban development. The paper makes a detailed study on the optimization of urban-rural bus routes in Erqi District of Zhengzhou, China. The factors of bus stop selection are analyzed, and the three categories, including traffic road condition factors, economic benefit factors and waiting number factors, are mainly considered. The analytic hierarchy process is used to determine 35 specific objectives of urban-rural bus stop optimization, 20 of which are selected for simulation experiment with large weight. Then the ant colony optimization (ACO) algorithm in path optimization is analyzed, which has the following two advantages. First, the global pheromone update is combined with the local pheromone update to enhance the algorithm's optimization ability and convergence speed. Second, through the method of spatial contraction transformation, the ant constructs a solution to reduce the number of construction steps and speed up the operation. Based on the actual analysis of urban-rural public transportation in the Erqi District of Zhengzhou, a simulation experiment is executed to show that the ACO algorithm is able to find out the optimal path, which is 15.1% shorter than the ant colony system (ACS) algorithm. The ACO algorithm improved path planning has good time effectiveness and path practicability.
Highlights
With the development of urbanization, an increasing number of rural residents take urban-rural public transportation to work in the cities
Based on the study of the current situation and the existing routes of urban-rural public transport, an ant colony optimization algorithm (ACO) (Martin, Frank, Hartmut, 2003) for optimal path planning is proposed according to the traffic characteristics of township residents and the analysis of traffic flow in each station, which the constraints of carrying capacity in urban-rural public transport are considered
The analytic hierarchy process and the ant colony optimization algorithm are used to complement each other, which are used to determine the weight of the point index in the urban-rural Public Transport path planning, which makes the determination of the selected point weight more objective
Summary
With the development of urbanization, an increasing number of rural residents take urban-rural public transportation to work in the cities. Based on the study of the current situation and the existing routes of urban-rural public transport, an ant colony optimization algorithm (ACO) (Martin, Frank, Hartmut, 2003) for optimal path planning is proposed according to the traffic characteristics of township residents and the analysis of traffic flow in each station, which the constraints of carrying capacity in urban-rural public transport are considered. The ant colony optimization algorithm is a simulation algorithm that optimizes the regularity of ant foraging in nature and mutual cooperation in foraging operations (Feng, Zheng, Liu, 2005) It is a self-organizing algorithm that increases the system without external influences. The analytic hierarchy process and the ant colony optimization algorithm are used to complement each other, which are used to determine the weight of the point index in the urban-rural Public Transport path planning, which makes the determination of the selected point weight more objective. This paper focuses on the analysis of the weight of the station, that bus station with large weight is selected for path planning
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
