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Research on railway emergency resource scheduling strategy under multiple uncertainty coupling.

Jianping Sun¹, Yuyang Wan¹, Guangle Lu¹

¹School of Transportation Engineering, East China Jiaotong University, Nanchang, China.

|May 19, 2026

Summary

This study optimizes railway emergency resource scheduling under uncertainty using interval fuzzy credibility-constrained programming and the VEPSO algorithm. The novel approach enhances efficiency and solution quality for dynamic scheduling strategies.

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Area of Science:

Operations Research
Railway Engineering
Optimization Theory

Background:

Railway emergency resource scheduling faces significant uncertainty from various sources.
Existing models often struggle to adequately address complex fuzzy and random variables.
Accurate and efficient scheduling is critical for minimizing response times and costs.

Purpose of the Study:

To develop a robust optimization framework for railway emergency resource scheduling under multiple uncertainties.
To minimize both scheduling time and cost while ensuring high demand fulfillment credibility.
To introduce an improved algorithm for efficiently finding Pareto-optimal solutions.

Main Methods:

Utilized interval numbers for scheduling time uncertainty and fuzzy-random variables for resource demand.
Integrated interval programming with fuzzy credibility constraints into a unified optimization model.
Developed a constrained, multi-objective, variable neighborhood search algorithm (VEPSO) for efficient solution finding.

Main Results:

The VEPSO algorithm demonstrated superior convergence efficiency and solution quality compared to PSO, NSGA-II, VEGA, and MOEA/D.
Achieved an average of 385 convergence iterations (26% lower than MOEA/D) with a 93.3% success rate and 0.983 demand fulfillment credibility.
Sensitivity analysis confirmed model robustness, showing stable, approximately linear responses to demand variations.

Conclusions:

The proposed interval fuzzy credibility-constrained programming model and VEPSO algorithm effectively handle uncertainties in railway emergency scheduling.
The satisfaction evaluation method provides a quantitative basis for dynamic strategy adjustments.
Offers significant theoretical and practical value for decision support in uncertain railway environments.