managing risk in tunneling projects: a fuzzy topsis approach for improved decision-making

Risk assessment is a critical task in tunneling projects, yet classical methods often fail to adequately manage the inherent uncertainties of expert judgments. this paper presents a comparative risk analysis using two multi-criteria decision-making techniques: classical topsis and fuzzy topsis. the study first establishes a baseline risk ranking using the classical topsis method, which relies on crisp numerical inputs. it then applies the fuzzy topsis method to the same dataset, leveraging fuzzy set theory to model the linguistic ambiguity and uncertainty in expert evaluations. the methodologies are applied to a case study of a tunnel construction project, assessing 17 distinct risks across 11 criteria. the results demonstrate that while both methods identify similar high-priority risks, the final rankings differ. the fuzzy topsis model, by incorporating uncertainty, provides a more robust and nuanced prioritization, identifying owner risks (r10) and site/environment risks (r5) as more critical than the classical method did. this study concludes that the fuzzy topsis approach is a superior and more reliable tool for decision-makers, offering a more realistic framework for managing the complex risks in tunneling projects.

managing risk in tunneling projects: a fuzzy topsis approach for improved decision-making

risk assessment is a critical task in tunneling projects, yet classical methods often fail to adequately manage the inherent uncertainties of expert judgments. this paper presents a comparative risk analysis using two multi-criteria decision-making techniques: classical topsis and fuzzy topsis. the study first establishes a baseline risk ranking using the classical topsis method, which relies on crisp numerical inputs. it then applies the fuzzy topsis method to the same dataset, leveraging fuzzy set theory to model the linguistic ambiguity and uncertainty in expert evaluations. the methodologies are applied to a case study of a tunnel construction project, assessing 17 distinct risks across 11 criteria. the results demonstrate that while both methods identify similar high-priority risks, the final rankings differ. the fuzzy topsis model, by incorporating uncertainty, provides a more robust and nuanced prioritization, identifying owner risks (r10) and site/environment risks (r5) as more critical than the classical method did. this study concludes that the fuzzy topsis approach is a superior and more reliable tool for decision-makers, offering a more realistic framework for managing the complex risks in tunneling projects.