Work

Integrated optimization of train stopping plans and timetabling for urban rail transit based on dynamic demand

Year: 2025

Type: article

Abstract: This study addresses the higher demand of passengers during peak hours in urban rail transit by proposing an integrated optimization of train stopping plans and timetabling to reduce overcrowding and the total waiting time. A nonlinear integer programming model is developed, incorporating passenger demand, operation costs, train capacity, and station congestion levels. The decision variables include the stopping plan and departure headways. The objective is to minimize total operation time, average operation time, and waiting time, while reducing congestion variance across stations. A case study using the NSGA-II algorithm shows that the optimized solution significantly alleviates station congestion compared to the all-stop plan. Additionally, it reduces average operation time, total operation time, and waiting time by 3.42%, 9.40%, and 10.44%, respectively, demonstrating the model's feasibility and effectiveness.

Source: Digital Transportation and Safety

DOI: 10.48130/dts-0025-0001

Authors: Jiayao Han, Qiuchi Xue, Ye Yuan, Xin Yang, Jianjun Wu

Institutions: Beijing Jiaotong University, Dalian University of Technology

Language: English

Topic: Railway Systems and Energy Efficiency

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

Funders: National Natural Science Foundation of China, Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)