A two-stage stochastic programming approach for strategic rolling stock scheduling in passenger railway transport

Siqiao Li; Rolf van Lieshout; Patrick Stokkink

doi:10.1016/j.omega.2026.103593

May 1, 2026OmegaOpen Access

A two-stage stochastic programming approach for strategic rolling stock scheduling in passenger railway transport

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Key Points

This research focuses on improving rolling stock scheduling in passenger railway transport using a stochastic programming approach. It aims to evaluate line plans without fixed timetables while managing uncertainty.
Developed a two-stage stochastic programming model for rolling stock scheduling.
Compared flow-based and circulation-based stochastic models to analyze scheduling effectiveness under different conditions.
Provided managerial insights into fleet sizing that account for uncertainty and operational flexibility.
Demonstrated that stochastic planning significantly improves the procurement-service trade-off under demand uncertainty.
The flow-based model outperformed the circulation-based model in managing scheduling flexibility.
Insights on optimal fleet sizing were provided, enabling better resource allocation in uncertain environments.

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Implication

Evaluates rolling stock scheduling strategies under demand uncertainty, suggesting improved fleet management.

Abstract

• Rolling stock scheduling for line plan evaluation without a timetable. • Stochastic planning better manages the procurement–service trade-off under demand uncertainty. • Comparison of flow- and circulation-based stochastic models. • Managerial insights on fleet sizing under uncertainty and flexibility.

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Li et al. (2026) studied this question.

synapsesocial.com/papers/6a1a7f230307b7850943174e https://doi.org/10.1016/j.omega.2026.103593

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A two-stage stochastic programming approach for strategic rolling stock scheduling in passenger railway transport

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A two-stage stochastic programming approach for strategic rolling stock scheduling in passenger railway transport

Key Points

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Abstract

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