Research On Train Interval Optimization Of Intercity Railway Based On Artificial Bee Colony Algorithm

With the rapid development of China's high-speed train technology and the accelerating speed of urbanization,the concept of “city” has undergone fundamental changes.The urban morphology has moved from a single central city form to urban agglomerations,metropolitan areas,larger areas and a wider range of regional economies,exchanges and connections between cities have become more frequent,and intercity railways have become more and more important in the process of regional economic integration.As the core work of intercity railway operators,operating organizations play a very crucial role in reducing the costing of enterprises and improving the service level of enterprises.The key to the optimization of operating organization is to formulate the reasonable operating interval,it's a multi-objective and multi-constrained combination optimization problem,which is difficult to solve completely in the traditional mathematical programming or heuristic method.With the continuous development of intelligent computing,intelligent algorithms are widely used to solve the problem of operating optimization in urban transportation.As a new type of bionic intelligent optimization algorithm,Artificial Bee Colony(ABC)algorithm has the advantages of less control parameters,simple and easy control,and good robustness.Therefore,this dissertation proposes an optimization strategy of intercity railway train interval based on an ABC algorithm.Firstly,the current development status of China's intercity railway,the research status of operating organization optimization in the field of public transportation and rail transit are briefly described.The definition of intercity railway,passenger flow characteristics,passenger flow forecast,intercity railway train operation are expounded.and the main influencing factors affecting the passenger flow changes of intercity railways and train operation plan are analyzed.Secondly,the bionics foundation of the ABC algorithm is studied,and the concept,principle and implementation process of the ABC algorithm are emphatically explained.Aiming at the shortcomings of the ABC algorithm in the process of convergence,this article analyzes the search mechanism,performance parameters,operation steps,convergence performance,global search performance and parameter setting of the algorithm,and makes some improvements to the ABC algorithm.In order to verify the global search performance,accuracy and efficiency of the Improved Artificial Bee Colony(IABC)algorithm,the standard test function is used for the simulation test.The simulation results show that the IABC algorithm is feasible.Finally,in view of the actual operation of the intercity railway and the passenger outflow,the factors affecting the optimization of the intercity train interval are comprehensivelyconsidered;Taking the minimum average waiting time for all arriving passengers,the maximum waiting time for trains,an intercity railway train interval optimization model based on SS-ABC algorithm was established;Minimum total number of full days of train departure,all passengers arriving shortest waiting time,an optimization model of intercity railway driving organization based on SP-ABC algorithm was established.Based on the historical passenger flow data of Beijing-Tianjin intercity railway,the simulation results of the intercity train interval based on GA and ABC algorithm are compared by experimental simulation.The optimization results show that the IABC algorithm proposed can better solve the optimization problem of intercity train operating organization.