Optimization Of Urban Rail Transit Scheduling Based On BFO Algorithm

Urban rail transit plays an important role in easing the prominent traffic problems with its characters of safety and comfort, green and environment protection,large passenger capacity and high comprehensive benefit. Train scheduling is the core work of operating companies of a urban rail transit and plays the crucial role in reducing the operating costs, improving operating efficiency and service levels. The key to conduct the scheduling optimization is to formulate the reasonable departure intervals which belong to multi-objective nonlinear optimization NP problem with big solving space, high variable dimension, complex constraint conditions, and more difficult traditional mathematics solving methods. With the development of intelligent computers, we can use the intelligent optimization algorithm effectively to solve the public transportation scheduling optimization problems. This article on the basis of analyzing the research achievements of scheduling optimization and intelligent optimization algorithm, proposes the urban rail transit scheduling optimization strategy relying on the bacteria foraging optimization algorithm. The main work is as follows:(I) Describe the research backgrounds, research status and hardware and software technologies of urban rail transit scheduling optimization problems.Introduce the achievements of intelligent optimization algorithm, conclude and state the theories, methods and characters of several common intelligent optimization algorithms.(II) Make an intensive research on the bacteria foraging optimization algorithm.Emphatically discuss the origin, basic principles, procedures of optimization algorithm and major operations of the bacterial foraging optimization algorithm. The influence of the parameters on the performance of the algorithm is analyzed, and the basic bacterial foraging optimization algorithm is improved by the adaptive swimming step and the adaptive migration rate.(III) Analyze and conclude the passenger flow forms and the space-time distribution characteristics of the urban rail transit. Research many factors what affectthe train scheduling. On the basis of analyzing the factors what affect the interests of both operating companies and passengers, establishing optimization objectives and constraint conditions, building the scheduling optimization mathematical models.(IV)Have a systematic introduction to the application process of the bacterial foraging optimization algorithm in scheduling optimization, including the population initialization, bacteria code, building the penalty function constraint conditions and experimental analysis of algorithm parameter setting,. Finally applying the urban rail transit scheduling optimization strategy will be based on bacterial foraging optimization algorithm of urban rail transit scheduling optimization strategy which bases on the bacteria foraging optimization algorithm to a certain city’s rail transit instance data for the simulation experiment, and comparing with the experimental results of other algorithms and verify the effectiveness of the algorithm and model in this article.