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3878. A multiobjective model for adaptable train unit scheduling in normal and emergent conditions
Invited abstract in session TA-54: Resilience in Public Transport Planning, stream Public Transport Optimization.
Tuesday, 8:30-10:00Room: S01 (building: 101)
Authors (first author is the speaker)
| 1. | Zhiyuan Lin
|
| Institute for Transport Studies, University of Leeds | |
| 2. | David Watling
|
| Institute for Transport Studies, University of Leeds |
Abstract
Train unit scheduling optimisation(TUSO) involves allocating train unit vehicles to fulfil timetabled trips, with the option to couple or decouple units to allow flexible rolling stock configurations for a train. TUSO typically balances two conflicting objectives by Pareto multiobjective(MO) optimisation:meeting passenger demand and minimising rolling stock use. However, certain emergencies, eg adverse weather or signal failure, require a significantly reduced timetable, making it challenging to meet full passenger demand with fewer services. In this case, a different rule is used that as long as adjusted demand is met, a solution is acceptable regardless of other objectives. This is beyond the capability of Pareto methods, as setting a large weight on demand is oversimplification. Pareto methods also face challenges in decision making involving uncertainty/fuzziness. Experts may find real-time selection of frontier solutions impractical. We propose a novel MO TUSO model for both normal and emergency cases on a synthetic TUSO instance. By tuning its parameters, the model can switch between the two, or intermediate states. It provides a probabilistic metric for gauging solution desirability across a continuum, as seen by different experts/rules via tuned parameters, instead of binary choices in efficient and inefficient options.This is valuable for uncertainty or real-time scenarios where the ‘best’ solution relies on complex factors, eg hierarchically prioritising demand.
Keywords
- Multi-Objective Decision Making
- Railway Applications
- Fuzzy Sets and Systems
Status: accepted
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