Ranking the sustainability performance of pavements: An intuitionistic fuzzy decision making method

In this research, we proposed a fuzzy multi-criteria decision making method which is applied for ranking the life cycle sustainability performance of different pavement alternatives constructed with hot-mix and warm-mix asphalt mixtures. This method consisted of four different techniques such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to select the best pavement alternative, the intuitionistic fuzzy entropy method to identify the importance of phases and criteria, the intuitionistic fuzzy weighted geometric averaging operator to establish a sub-decision making matrix based on weights of attribute, and the intuitionistic fuzzy weighted arithmetic averaging operator to build a super decision matrix depending on weights of different life cycle phases. Based on research findings, a synthetic wax-type warm-mix asphalt additive is selected as the best alternative among the pavement alternatives. In addition, conventional hot-mix asphalt is found to be the second best option compared to other mixtures.