March 1, 2022

Quantitative Risk Assessment of Rail Infrastructure Projects Using Monte Carlo Simulation and Fuzzy Logic

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Quantitative risk assessment shows how effective Monte Carlo simulation is in managing various project risks.
Findings reveal that 47% of studies prefer Monte Carlo simulation, while fuzzy logic is preferred by 33% for its handling of imprecise data.
Analysis primarily employed Monte Carlo simulation, with a focus on triangular and PERT distributions, revealing dependence modeling limitations.
Sensitivity analysis was included by 64% of studies, yet global approaches were only adopted by 21% highlighting methodological gaps.

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Systematic review quantifies risks in rail construction projects, indicating MCS is the most utilized method.

Md. Sakib Hasan Hriday (2022) studied this question.

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