Optimal Design of Feeder-bus Network Related to Urban Rail Line based on Transfer System

The feeder bus network design problem is researched in this paper, aiming at connecting with the urban rail transit as well as possible. In solving the problem, a set of process in locating feeder bus routes is presented first, and then an optimization model of determining feeder bus network is established. The genetic algorithm (GA) is used in solving the problem and it is implemented in VC++ language. Finally, a case study is presented based on the existing rail transit line 3 in Dalian, with optimized the feeder bus routes obtained. The result also shows that the model and the algorithm are feasible in solving the problem.

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Optimal Design and Experimental Assessment of a Wireless Power Transfer System for Home-Cage Monitoring

IEEE Transactions on Power Electronics ◽

10.1109/tpel.2019.2894182 ◽

2019 ◽

Vol 34 (10) ◽

pp. 9779-9793 ◽

Cited By ~ 6

Author(s):

Jeff Po-Wa Chow ◽

Henry Shu-Hung Chung ◽

Leanne Lai-Hang Chan ◽

Ruihua Shen ◽

Sai Chun Tang

Keyword(s):

Optimal Design ◽

Home Cage ◽

Wireless Power Transfer ◽

Transfer System ◽

Power Transfer ◽

Wireless Power ◽

Experimental Assessment ◽

Wireless Power Transfer System

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Optimal design of promotion based demand management strategies in urban rail systems

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2019.10.008 ◽

2019 ◽

Vol 109 ◽

pp. 155-173 ◽

Cited By ~ 3

Author(s):

Zhenliang Ma ◽

Haris N. Koutsopoulos

Keyword(s):

Optimal Design ◽

Demand Management ◽

Management Strategies ◽

Rail Systems ◽

Urban Rail

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Stop Plan of Express and Local Train for Regional Rail Transit Line

Journal of Advanced Transportation ◽

10.1155/2018/3179321 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Qin Luo ◽

Yufei Hou ◽

Wei Li ◽

Xiongfei Zhang

Keyword(s):

Energy Consumption ◽

Travel Time ◽

Programming Model ◽

Urban Rail Transit ◽

Rail Transit ◽

Long Distance ◽

Passenger Travel ◽

Urban Rail ◽

Proposed Model ◽

Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

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Timetable Design for Urban Rail Line with Capacity Constraints

Discrete Dynamics in Nature and Society ◽

10.1155/2015/429219 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Yu-Ting Zhu ◽

Bao-Hua Mao ◽

Lu Liu ◽

Ming-Gao Li

Keyword(s):

Solution Method ◽

Operating Cost ◽

Capacity Constraints ◽

Scheduling Model ◽

Urban Rail ◽

Proposed Model ◽

Rail Line ◽

First Come First Serve ◽

Waiting Cost ◽

Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

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