Multi-criteria decision-making (MCDM) methods deeply assist decision-makers in evaluating and analyzing input data as accurately as possible in the area of safety and reliability. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be used to rank a set of alternatives based on the different types of criteria. However, this method still needs to be improved; fuzzy set theory and its corresponding extensions are bold in the line of TOPSIS improvement. In this study, the original form of TOPSIS method is extended using Pythagorean fuzzy-based Chebyshev distance measures. Pythagorean fuzzy set has better reflection compared to the conventional fuzzy set theory and Chebyshev distance measures can provide more accurate results, which are used to compute the separation measures in the TOPSIS method. Therefore, the novel improved TOPSIS methods have been developed underlying the ideal of Pythagorean fuzzy-based Chebyshev distance measures. The developed method is applied on a humanitarian case-study to show the efficiency of the approach in an emergency response situation. Results show that the proposed method is efficiently applicable in real-life decision-making situations.

多标准决策 (MCDM) 方法可深入帮助决策者在安全性和可靠性领域尽可能准确地评估和分析输入数据。通过与理想解决方案的相似性 (TOPSIS) 进行偏好排序的技术可用于根据不同类型的标准对一组备选方案进行排名。但是，这种方法还有待改进；模糊集理论及其相应的扩展在 TOPSIS 改进方面是大胆的。在本研究中，TOPSIS 方法的原始形式使用基于勾股模糊的切比雪夫距离测度进行了扩展。与传统的模糊集理论相比，勾股模糊集具有更好的反映，切比雪夫距离测度可以提供更准确的结果，用于计算TOPSIS方法中的分离测度。所以，新的改进的 TOPSIS 方法是在基于勾股模糊的切比雪夫距离测量的理想基础上开发的。开发的方法应用于人道主义案例研究，以展示该方法在紧急响应情况下的效率。结果表明，所提出的方法有效地适用于现实生活中的决策情况。