Study On Passenger Special Line Train Regulation Model And Algorithm

Train regulation is a process to reschedule the train timetable when the actual train operation status deviate the project train schedule, and assure most trains running on time. Train regulation must be based on the project train timetable. Train regulation problem has the characteristic of high real-time, strong constraints and combinatorial optimization.In this thesis, the train regulation optimization problem of passenger line is studied. The main problems discussed are as follows:1. Analyzed the train regulation characteristic, its influence factors, the traits of passenger line train regulation, regulation strategies.2. With the goal of minimizing the total weighted delay time of all the trains, a train regulation optimization model on the passenger line was set up.3. Train regulation problem is a large scale combinatorial optimization problem, and also one kind of NP-hard problems. Since the problem itself requires the algorithm calculate the results in rather short time, and there also exists many constraints, the model can hardly be solved with the mathematical programming methods. In this paper, an intelligent optimization algorithm, genetic algorithm(GA) is applied to solve the problem. According to the characteristic of the train regulation problem, a two-dimension matrix encoding method is used, the crossover and mutation operators relative to the problem are designed. The constraints satisfaction methods is presented as well.4. An instance based on the background of Wuhan-Guangzhou passenger special line is constructed, and the genetic algorithm to the train regulation problem is programmed in matlab7.0 simulation environment. Finally, the example is solved with GA, and the simulation results is analyzed, the results prove the feasibility of the model and algorithm.