Demand-based timetabling for a rapid rail transit line in the Philippines using integer linear programming
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ID: 286834
2025
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Abstract
The continuous growth of rail transport networks in the Philippines signals the need to improve railway operations. One strategy for this is adapting a non-periodic timetable that allows operators to peg their train schedule to passenger demand. In this study, we created three integer linear programming models minimizing total passenger waiting time to formulate timetables catering to dynamic passenger demand for the Light Rail Transit Line 1 (LRT-1). These models include a base model that integrated Yin et al. (2017)'s methodology while defining scheduled trips, a second model allowing the deployment of trains at both ends, and a third model not requiring the maximum number of trips for deployment while keeping the characteristics of the first two models. Small-scale simulations with varying numbers of stations, trains, and time horizons were run with the three models to assess the models' reactiveness to fluctuating demand and their ability to solve bigger problems. Models 2 and 3 worked best in capturing demand fluctuations, with Model 3 being particularly applicable in more constrained problems. However, these models run into problems in finding an optimal solution when demand increases or when the scale of the problem is widened. As such, the researchers recommend that the time-space network approach be used when railway systems are doing targeted assessments of a number of stations only, and that alternative representations of railway networks be explored to better suit a large rail line such as LRT-1.
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| Authors | Palomares, Kristine Grace P. |
| Journal | Malay Journal |
| Year | 2025 |
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