Application Of Genetic Algorithm In Solving Transferred Paths Of Rail Transit

With the construction of rail traffic and urban development,the couplings among rail transport lines are increasingly higher,and the transfer between lines are becoming more frequently.Because of the high cost and long construction period of rail transit investment,different lines may be operated by different operation business. It is necessary to build a reasonable traffic ticket income distribution system to protect the interests of operators.The solving process of rail transit transferred paths is the critical issue to realize the traffic ticket income distribution system.In this thesis,we compared and analyzed several income distribution models. Select the K optimal paths income distribution model as the basic theory of research. Compared and analyzed the solving process of rail transit transferred paths algorithms in this model.And the existing models are not well suited for the construction of rail traffic and urban development.On the basis of dissertation of the fundamental conception,principle and operators of genetic algorithm,this thesis design algorithm to apply it to solve the rail transit transferred paths.A new genetic operator is developed to used in genetic algorithm.In order to improve the quality of the initial population,proposed a new method based on the concept of gene pairs.At last,rail transit operation lines model of Shanghai is used as an instance.We simulated the algorithm by using the Matlab language.By the calculation and analysis of the actual example,we verified the reasonability and effectiveness of the algorithm, which has more practical value to the actual traffic ticket income distribution problem.