Integrated CRITIC-TOPSIS and Monte Carlo Sensitivity Analysis for Optimal Various Natural Fibre Selection in Sustainable Building Insulation Composites to Support the Sustainable Development Goals (SDGs)

The selection of sustainable insulation materials is crucial for supporting environmentally responsible building construction in alignment with the Sustainable Development Goals (SDGs). This study proposes an integrated multi criteria decision-making approach by combining the CRITIC method for objective criteria weighting, the TOPSIS method for ranking alternatives, and Monte Carlo sensitivity analysis to assess ranking stability under uncertainty. Twelve natural fibres were evaluated based on mechanical strength, physical characteristics, and moisture resistance. The CRITIC TOPSIS integration effectively identified the most suitable fibre alternatives for insulation purposes. Sensitivity analysis validated the robustness of the model, ensuring consistent ranking outcomes across multiple simulations. This integrated approach offers a reliable and transparent framework for optimal material selection in sustainable construction practices. The study contributes to advancing sustainable building technologies while supporting SDG 9 (Industry, Innovation and Infrastructure), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production).