Study on Automatic Parameter Configuration to Enhance Real-Time Railway Traffic Management

RECIFE-MILP tackles the real-time railway traffic management problem. It relies on the solution of a mixed integer linear programming (MILP) model through a MILP solver. Mostly linked to this solver, RECIFE-MILP includes numerous configurable parameters, which can significantly influence its performance and are challenging to configure manually. Consequently, automatic parameter configuration appears as a promising option to obtain the best possible performance in a short computation time. This paper addresses two research questions: (1) Can automatic parameter configuration significantly enhance RECIFE-MILP's performance? (2) Do distinct classes of problem instances require specialized configurations? To answer these questions, we present an experimental study using irace, a state-of-the-art parameter configuration tool. Experiments on three French control areas demonstrate that automatically chosen configurations achieve significant performance gains compared to default parameter settings, achieving better performance on computation time or solution quality in more than 80 % of the 360 instances. However, the benefit of configuring RECIFE-MILP for specific classes of instances does not clearly emerge.

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Publication Details

Published
2025-09-08
DOI
https://doi.org/10.1109/mt-its68460.2025.11223597
Primary Topic
Railway Systems and Energy Efficiency
Type
article
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article

Study on Automatic Parameter Configuration to Enhance Real-Time Railway Traffic Management

Paola Pellegrini, Manuel López Ibáñez, Cheng Bai, Joaquín Rodríguez
Railway Systems and Energy Efficiency
article

Study on Automatic Parameter Configuration to Enhance Real-Time Railway Traffic Management

Paola Pellegrini, Manuel López Ibáñez, Cheng Bai, Joaquín Rodríguez
article en

Abstract

RECIFE-MILP tackles the real-time railway traffic management problem. It relies on the solution of a mixed integer linear programming (MILP) model through a MILP solver. Mostly linked to this solver, RECIFE-MILP includes numerous configurable parameters, which can significantly influence its performance and are challenging to configure manually. Consequently, automatic parameter configuration appears as a promising option to obtain the best possible performance in a short computation time. This paper addresses two research questions: (1) Can automatic parameter configuration significantly enhance RECIFE-MILP's performance? (2) Do distinct classes of problem instances require specialized configurations? To answer these questions, we present an experimental study using irace, a state-of-the-art parameter configuration tool. Experiments on three French control areas demonstrate that automatically chosen configurations achieve significant performance gains compared to default parameter settings, achieving better performance on computation time or solution quality in more than 80 % of the 360 instances. However, the benefit of configuring RECIFE-MILP for specific classes of instances does not clearly emerge.

University of Manchester (GB), Université Gustave Eiffel (FR)
Openalex Percentile: Top 53%
Railway Systems and Energy Efficiency
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