Endogenous Performance of Rail Sections in Brazil: A Novel Two-Dimensional Fuzzy-Monte Carlo Approach

This paper investigates the endogenous source of railway performance in Brazil by focusing on several rail sections. A novel Two-Dimensional Fuzzy-Monte Carlo Analysis (2DFMC) approach is proposed including a multi-attribute decision-making (MADM) model based on type-2 fuzzy sets (T2FS) and a Stochastic Structural Relationship Programming (SSRP) Model based on neural networks. Results suggest that the level of inclination of the rail operators to use the bottlenecked rail sections influences the measurement of idleness, in a chained effect. It is suggested that the balance and coordination among bottleneck, minimum curve radius, and installed capacity are prerequisites to improve railway performance.

Automated summary

This paper investigates the endogenous source of railway performance in Brazil with a focus on multiple rail sections. A new Two-Dimensional Fuzzy-Monte Carlo Analysis (2DFMC) approach is proposed, which includes a multi-attribute decision-making (MADM) model based on type-2 fuzzy sets (T2FS) and a Stochastic Structural Relationship Programming (SSRP) Model based on neural networks. The results suggest that the inclination of rail operators to use bottlenecked rail sections has a chained effect on the measurement of idleness. It is recommended that balancing and coordinating bottleneck, minimum curve radius, and installed capacity are prerequisites for improving railway performance.