Multi-routing planning design of Y-type urban rail transit

Abstract

A Y-type urban rail transit is composed of a trunk and a branch, and the passenger demand has the characteristics of multidirectional and unbalanced. It is important to design routing planning of Y-type urban rail transit and provide reasonable service for passengers with acceptable operational cost. In this study, a routing planning design model was proposed for Y-type urban rail transit aimed at minimizing the passenger travel time and train operating distance. The decision variables of the model were the locations of turn-backs and the departure frequencies of the train routings in the multirouting planning. The constraints of passenger demand and line condition were considered. The multi-objective model was turned into a single-objective model by giving weight values to the objectives. Then a genetic algorithm was applied to obtain optimal solutions of the proposed model. Finally, a case study was conducted, and the optimal solutions under different forms of multi-routing planning with different weight values were analyzed. The results showed that when the weight of the passenger travel time increased to a certain level, the optimal solution changed from a two-routing planning to a three-routing planning, and the latter one could better meet the characteristics of the passenger.

Multiobjective Collaborative Optimization Method for the Urban Rail Multirouting Train Operation Plan

“…Jiang and Guo [17] analyzed the spatial distribution and passenger fow of the rural road network in China and showed that combining the trunk lines and branch lines into "Y", double "Y," or "8" types for integrated transportation can reduce operating costs and exhaust emissions and improve operating efciency. Zhao et al [18] proposed a routing planning model for URT Y-type lines, aiming to minimize passenger travel time and train operating distance, determine the turnaround station of the routing, and the departure frequency of multiple routes. Tey found that by converting multiple targets into a single target and solving them by a genetic algorithm, the results show that three train routes are more suitable for the characteristics of passenger fow on a Y-type line.…”

Complex systems in mechanical engineering

“…Results for a case study show that when the weight of the passenger travel time increases to a certain level, the optimal solution changes from a two-routing planning to a threerouting planning, and the latter one can better meet the characteristics of the passenger. 8 In ''Particle swarm optimization used with proportional-derivative control to analyze nonlinear behavior in the atomic force microscope,'' Chin-Tsung Hsieh, Her-Terng Yau, Cheng-Chi Wang, and Yi-Sheng Hsieh investigate the nonlinear probe behavior in an atomic force microscope, caused by different excitation frequencies, and analyze the subsequent regulation using particle swarm optimization in combination with proportional-derivative control. They examine the system dynamic behavior using phase portrait, bifurcation diagrams, Poincare´maps, and the maximum Lyapunov exponent.…”