Research On Train Scheduling Model And Algorithm Orienting Energy Saving And Emission Reduction

Train scheduling problem is a very complex issue in the railway transportation, many factors need to be considered. A sound scheduling scheme will balance the interests of the passengers and the railway sector on the premise of ensuring traffic safety. The passengers’ interests can conveyed as trying to meet more demand for passenger travel and reduce passengers’travel time, while the railway sector may prefer less operating costs. Domestic and foreign scholars focus only on the train energy consumption costs without taking the cost of carbon emission into account when considering the operating costs of the railway sector. However, along with the establishment of the world’s first carbon emissions trading system by EU, the transaction costs of carbon emission has been paid more and more attention, and gradually become an important part of the train operating costs. Therefore, considering the cost of carbon emissions is necessary. The contents of this thesis are as follows:This thesis firstly summarizes researches on train energy saving at home and abroad systematically, whose focus is concentrated in the train energy-saving scheduling and train energy-saving operation, but does not conduct in-depth study of emission reduction. The implementation of the EU emissions trading scheme, brings new changes to train energy-saving scheduling, and will have impact on the energy conservation and emission reduction of China’s railway sector. In this context, the thesis discusses a combination mode of transaction costs of carbon emission and train energy-saving scheduling.In the thesis, we consider train energy saving and carbon emission problem, a train scheduling problem with train running time and a train scheduling problem with fuzzy passengers’time were discussed. In the former, we propose a multi-objective train scheduling model on single-track railways by minimizing the total running time as well as the energy and carbon emission costs. The model is solved by a fuzzy multi-objective optimization algorithm to obtain a non-dominated solution. Numerical example is given to illustrate the model and solution methodology on a small network. The result shows that the fuzzy multi-objective optimization algorithm can find better results and achieve the effect of energy saving and emission reduction.In the train scheduling problem with fuzzy passengers’time, we define the concept of passengers’time for the importance of the number of passengers on board to the train’s travel time, then we set the number of passengers boarding and alighting within a certain time as a fuzzy variables taking into account the fluctuations of the passengers, and build the objective function of the fuzzy passengers’ time, combined with the optimization objects of the energy saving and emission reduction, we build a train scheduling model under uncertainty. For this problem, we give an example for model validation, the solution results show that the model is valid.