Efficient fuzzy multi-criteria decision-making for optimal college location selection: A comparative study of min–max fuzzy TOPSIS approach

Q3 Mathematics Results in Control and Optimization Pub Date : 2024-04-06 DOI:10.1016/j.rico.2024.100422

Diptirekha Sahoo , Prashanta Kumar Parida , Bibudhendu Pati

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Abstract

Ranking fuzzy values is often essential in fuzzy multi-criteria decision-making (FMCDM) systems since it is established on the comparison of hazy data pairs, even though the comparison needs temporal complexity. Then to provide a fuzzy MCDM approach under min–max operations for avoiding the fuzzy comparison. By using fuzzy TOPSIS’s min and max operations, the suggested method produces two positive and negative ideal solutions of each alternative. Here, before discussing the effectiveness of the matrices between the alternatives, first to analyze the weighted strength and weakness indices from both positive and negative indices. The results of the method have been described using a straightforward case study of a proper location for creating a college. The best location can be identified using this method based on various criteria. The outcomes are also compared with the suggested method for its effectiveness. Additionally, this problem analyzes the fuzzy TOPSIS approach in an interval-valued number for greater efficiency.

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高校最佳选址的高效模糊多标准决策：最小-最大模糊 TOPSIS 方法的比较研究

在模糊多标准决策（FMCDM）系统中，模糊值排序通常是必不可少的，因为它是建立在朦胧数据对的比较之上的，尽管这种比较需要时间上的复杂性。因此，为了避免模糊比较，提供一种最小-最大运算下的模糊多标准决策方法。通过使用模糊 TOPSIS 的最小值和最大值运算，建议的方法为每个备选方案生成了正负两个理想解。在此，在讨论备选方案之间矩阵的有效性之前，首先要分析正负两个指数的加权强弱指数。该方法的结果已通过一个关于创建一所大学的合适地点的直接案例研究进行了描述。使用这种方法可以根据各种标准确定最佳地点。还将结果与建议的方法进行了比较，以确定其有效性。此外，本问题还分析了区间值数字中的模糊 TOPSIS 方法，以提高效率。

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