Synergizing AI with Interval Valued Fuzzy Numbers for Advanced Multiple Criteria Decision-Making Frameworks

In an increasingly complex and uncertain world, making informed decisions is crucial for the success of construction projects. This study presents an advanced framework for multiple criteria decision-making (MCDM) that merges artificial intelligence (AI) with interval-valued fuzzy numbers to enhance project selection within the construction sector, particularly in Iran. We adopt a structured methodology to identify essential performance metrics, such as cost estimates, expected revenue, return on investment, project duration, and risk levels. By representing these criteria as interval-valued fuzzy numbers, we effectively capture the inherent uncertainty in expert opinions. Our approach utilizes the Fuzzy Analytic Hierarchy Process (AHP) to determine weights and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking alternatives. Tested on three projects, the results highlight how this integrated approach simplifies decision-making while improving project evaluations. Overall, the framework serves as a vital tool for construction firms to optimize project selection amid uncertainty.

کلیدواژه ها:

Multi-Criteria ، Decision Making ، Interval Fuzzy Number ، Artificial Intelligence