Investigation of urban land development and utilization using an intelligent AHP algorithm and decision support system

The development and use of urban land with sustainable planning is a challenging task. In the optimization of urban land usage plans, this article investigates a decision-making framework based on the Analytical Hierarchy Process (AHP) combined with an intuitionistic fuzzy set (IFS) for a multi-criteria decision-making (MCDM) algorithm. The model considers several factors, including infrastructural demands, social effects, economic viability, and environmental sustainability, to manage the complexities and uncertainties inherent in urban land development. The framework of IFS is a more generalized and superior format of a fuzzy set. It can express both aspects of information in the form of degree of membership (DoM) and degree of non-membership (DoNM) under the range of interval[Formula: see text]. To address this type of situation, we aimed to develop AHP and Sugeno-weber t-norm (TNM) and t-conorm (TCNM) based aggregation operators (AOs) called intuitionistic fuzzy Sugeno-weber weighted averaging (IFSWWA) operators. The MCDM algorithm for AHP and derived AOs is presented, including the solution of real-life numerical examples for selecting the best plane for urban land development and utilization. To highlight the significance of the proposed approach, we will compare it with existing methodologies. Then, we discussed some solid conclusions.