Priorities for School Infrastructure Investment in the Face of Uncertainty: An Intuitionistic Fuzzy Multi-Criteria Decision-Making Method Employing the Frank Weighted Averaging Operator

Abstract

There is a need for a framework of decisions that is able to deal with the uncertainty and subjective nature of expert judgment as well as limited public funds. This paper presents an integrated multi-criteria decision-making approach using Intuitionistic Fuzzy Numbers and the Frank Weighted Averaging operator to prioritize school classroom building projects under a fixed capital budget. Four criteria—safety urgency, number of students affected, cost, and education impact—are measured by an IFN to reflect the membership, non-membership, and hesitancy built into expert assessments, and four candidate schools are assessed against these four criteria. The aggregation of the criteria into one fuzzy score for each alternative is done using a fuzzy operator, IFN-FWA, which is then converted to a crisp matrix using a score function. The obtained matrix is then assessed with five different MCDM methods (TOPSIS, WASPAS, VIKOR, MOORA, and CRITIC) to check the robustness of the ranking. The objective criterion weights are not subjectively assigned but are calculated with the CRITIC method, which will decrease subjectivity in the final recommendation. Although the mathematics involved in each method is different, the results consistently show that the top-ranked school is School4, followed by School2, School1, and School3, with a high level of agreement. The results validate that using the intuitionistic fuzzy aggregation proposed by Frank with multiple validated MCDM approaches can ensure the transparency, defensibility, and stability of the public infrastructure investment decision-making process under uncertainty.