2973. A Scenario-Based Optimization Approach for Long-Term Railway Capacity Planning: Tracing Shifting Bottlenecks
Invited abstract in session MA-10: Timetabling, stream Automated Timetabling.
Monday, 8:30-10:00Room: Clarendon SR 1.06
Authors (first author is the speaker)
| 1. | Chimeta Mulambia
|
| Engineering, University of Birmingham | |
| 2. | Gemma Nicholson
|
| The University of Birmingham, Edgbaston, Birmingham Centre for Railway Research and Education |
Abstract
Railway capacity is a fundamental metric for evaluating how efficiently a network can accommodate current and future transport demand. Traditional capacity assessment methods often rely on detailed timetable overlays on existing infrastructure models. While effective for short-term operational analysis, these methods face significant challenges in long-term strategic planning (5–30 years) due to uncertainties in future timetables, evolving demand, and technological advancements. The reliance on static timetables limits the ability to anticipate network bottlenecks under future operational scenarios.
This study presents a scenario-based optimization approach for tracing shifting bottlenecks in railway networks without requiring predefined timetables. We employ a Macro-Mesoscopic Infrastructure Track Model combined with demand scenarios and train service specifications to simulate long-term changes in network topology. The methodology integrates network modifications, including station expansions, track reconfigurations, and rolling stock evolution. Using Gurobi-based optimization, we analyze capacity utilization (both practical and residual) and assess network robustness under varying operational conditions.
The proposed approach enhances railway capacity planning by providing a computational decision-support framework for long-term investment and policy decisions.
Keywords
- Strategic Planning and Management
- Transportation
- Network Design
Status: accepted
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