Rani Pratibha, Mishra Arunodaya Raj
Department of Mathematics, Rajiv Gandhi National Institute of Youth Development, Sriperumbudur, Tamil Nadu India.
Department of Mathematics, Government College Raigaon, Satna, MP India.
Neural Comput Appl. 2022;34(10):8051-8067. doi: 10.1007/s00521-021-06782-1. Epub 2022 Jan 21.
Fermatean fuzzy set, a generalization of the fuzzy set, is a significant way to tackle the complex uncertain information that arises in decision-analysis procedure and thus can be employed on a wider range of applications. Due to the inadequacy in accessible data, it is hard for decision experts to exactly define the belongingness grade (BG) and non-belongingness grade (NG) by crisp values. In such a situation, interval BG and interval NG are good selections. Thus, the aim of the study is to develop the doctrine of interval-valued Fermatean fuzzy sets (IVFFSs) and their fundamental operations. Next, the score and accuracy functions are proposed for interval-valued Fermatean fuzzy numbers (IVFFNs). Two aggregation operators (AOs) are developed for aggregating the IVFFSs information and discussed some axioms. Further, a weighted aggregated sum product assessment method for IVFFSs using developed AOs is introduced to handle the uncertain multi-criteria decision analysis problems. A case study of e-waste recycling partner selection is also considered to elucidate the feasibility and efficacy of the introduced framework. Finally, sensitivity and comparative analyses are given to elucidate the reliability and robustness of the obtained results.
费马模糊集是模糊集的一种推广,是处理决策分析过程中出现的复杂不确定信息的一种重要方法,因此可应用于更广泛的领域。由于可获取的数据不足,决策专家很难用精确值准确地定义隶属度(BG)和非隶属度(NG)。在这种情况下,区间BG和区间NG是不错的选择。因此,本研究的目的是发展区间值费马模糊集(IVFFS)理论及其基本运算。接下来,针对区间值费马模糊数(IVFFN)提出了得分函数和精度函数。开发了两种聚合算子(AO)来聚合IVFFS信息,并讨论了一些公理。此外,引入了一种基于所开发的AO的IVFFS加权聚合和积评估方法,以处理不确定多准则决策分析问题。还考虑了一个电子废物回收合作伙伴选择的案例研究,以阐明所介绍框架的可行性和有效性。最后,进行了敏感性和比较分析,以阐明所得结果的可靠性和稳健性。