Endogenous Performance of Rail Sections in Brazil: A Novel Two-Dimensional Fuzzy-Monte Carlo Approach
Source abstract
Abstract
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.
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Research context
OpenAlex topics: Railway Engineering and Dynamics · Transport and Economic Policies · Maritime Ports and Logistics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal, Lemme, 355, Rio de Janeiro 21949-900, Brazil
Getulio Vargas Foundation, EBAPE—Brazilian School of Public and Business Administration, Rio de Janeiro 22250-900, Brazil
School of Management, University of Bradford, Bradford BD7 1DP, UK
Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan 81595-158, Iran
References (49)
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