Optimization of Multi-group Train Operations for Transit Urban Rail with Even Load

Multi-group train operations is one important part of the network operation technologies. In order to solve the problem that the train with fewer vehicles is over oversaturated and the train with more vehicles has a lower load factor, a bi-level programming model is established considering the equilibrium of load factor between different trains. The constraints are policy headway, platform length, maximum load and fleet size. The upper-level model is an optimization model of train plan, which is used to determine the optimal frequencies of two types of trains. The lower- level model is an optimization model of equilibrium of load factor, which is to determine the optimal formation plans and departure interval. And a nested genetic algorithm is also proposed. The results indicate that when the train formation and frequency is fixed, the average load of the trains under the even headways is 50%, the difference is only 0.8% under the uneven headways. The number of vehicles of two kinds of trains has minor differences can improve the equilibrium of train load factor under even headways. Besides, adjusting the headways between different train formations under uneven headways can realize the equilibrium of load factor in time and space. Copyright © 2019 by Science Press.