Cui Yanlin
Gansu Institute of Natural Resources Planning and Research, Lanzhou, 730000, Gansu, China.
Sci Rep. 2025 May 30;15(1):19048. doi: 10.1038/s41598-025-03181-7.
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.
以可持续规划发展和利用城市土地是一项具有挑战性的任务。在优化城市土地使用规划中，本文研究了一种基于层次分析法（AHP）并结合直觉模糊集（IFS）的多准则决策（MCDM）算法的决策框架。该模型考虑了几个因素，包括基础设施需求、社会影响、经济可行性和环境可持续性，以应对城市土地开发中固有的复杂性和不确定性。IFS框架是模糊集的一种更广义且更优越的形式。它可以在区间[公式：见文本]范围内以隶属度（DoM）和非隶属度（DoNM）的形式表达信息的两个方面。为解决此类情况，我们旨在开发基于AHP以及Sugeno - weber三角模（TNM）和三角余模（TCNM）的聚合算子（AO），即直觉模糊Sugeno - weber加权平均（IFSWWA）算子。给出了AHP和导出的AO的MCDM算法，包括为城市土地开发利用选择最佳方案的实际数值示例的求解。为突出所提方法的重要性，我们将其与现有方法进行比较。然后，我们讨论了一些可靠的结论。
