<p>Sustainability assessments of urban infrastructure projects are essential for ensuring environmental, economic, and social resilience. The fuzzy analytic hierarchy process (FAHP) framework offers a robust method to evaluate such projects, incorporating expert judgment and handling uncertainty through fuzzy numbers. In this approach, experts assess sustainability criteria through pairwise comparisons, with fuzzy weights assigned to factors such as resource efficiency (0.22), ecological impact (0.14), and energy use (0.11). The final sustainability score for an urban underground infrastructure project in Sanya, China, was calculated to be 0.545, reflecting a balanced performance across the assessed criteria. Using FAHP allows for integrating diverse expert opinions, providing decision-makers with a clear, actionable sustainability score while accounting for the inherent uncertainties in expert assessments.</p>

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Sustainability evaluation of urban underground infrastructure: mitigating marine and coastal environmental impacts using fuzzy analytic hierarchy process (FAHP)

  • Tianyin Li,
  • Zhengru Li,
  • Xiaoyu Zhang,
  • Yang Yu,
  • M. Mehdi Shafieezadeh

摘要

Sustainability assessments of urban infrastructure projects are essential for ensuring environmental, economic, and social resilience. The fuzzy analytic hierarchy process (FAHP) framework offers a robust method to evaluate such projects, incorporating expert judgment and handling uncertainty through fuzzy numbers. In this approach, experts assess sustainability criteria through pairwise comparisons, with fuzzy weights assigned to factors such as resource efficiency (0.22), ecological impact (0.14), and energy use (0.11). The final sustainability score for an urban underground infrastructure project in Sanya, China, was calculated to be 0.545, reflecting a balanced performance across the assessed criteria. Using FAHP allows for integrating diverse expert opinions, providing decision-makers with a clear, actionable sustainability score while accounting for the inherent uncertainties in expert assessments.