Research Article An Approach of Decision-Making under the Framework of Fermatean Fuzzy Sets Muhammad Sarwar Sindhu, 1 Imran Siddique , 2 Muhammad Ahsan, 1 Fahd Jarad , 3,4,5 and Taner Altunok 6 1 Virtual University of Pakistan, Lahore 54770, Pakistan 2 Department of Mathematics, University of Management and Technology, Lahore 54770, Pakistan 3 Department of Mathematics, Cankaya University, Etimesgut, Ankara, Turkey 4 Department of Mathematics, King Abdulaziz University, Jeddah, Saudi Arabia 5 Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan 6 Department of Industrial Engineering, Konya Food and Agriculture University, Meram, Konya, Turkey Correspondence should be addressed to Imran Siddique; imransmsrazi@gmail.com and Fahd Jarad; fahd@cankaya.edu.tr Received 21 January 2022; Revised 3 March 2022; Accepted 21 June 2022; Published 8 July 2022 Academic Editor: Gianpaolo Di Bona Copyright © 2022 Muhammad Sarwar Sindhu et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Because of its influence on various elements of human life experiences and conditions, the building industry is a significant business. In the recent past, environmental considerations have been incorporated in the design and planning stages of building supply chains. e process of evaluating and selecting suppliers is one of the most important issues in supply chain management. A multicriteria decision-making (MCDM) problem can be utilized to handle such issues. e goal of this research is to present a new and efficient technique for selecting suppliers with ambiguous data. e suggested methodology’s structure is based on technology for order of preference by similarity to ideal solution (TOPSIS), with Fermatean fuzzy sets (F r FSs) employed to cope with information uncertainty. In this article, authors modified the distance between F r FSs to propose the similarity measure and implemented it to form the MCDM model to resolve the vague and uncertain data. Moreover, we used this similarity measure to choose the optimal alternative. A practical example for alternative selection is provided, along with a comparison of the acquired findings to existing approach. Finally, to strengthen the outcome obtained through the proposed model, sensitivity analysis and time complexity analysis are performed. 1. Introduction In real-world situations, we frequently encounter tasks and activities that necessitate the usage of decision-making (DM g ) procedures. DM g may be viewed as a problem- solving process that yields an ideal, or at the very least reasonable, solution. In general, DM g is a mental and reasoning process that leads to choose an ideal option from a collection of possible alternatives in a DM g circumstance. TOPSIS is a valuable method for MCDM issues in the real world. Hwang and Yoon [1] first proposed this strategy in 1981, with Yoon continuing the process in 1987. TOPSIS rates options and determines the best compromise between them and the ideal solution. TOPSIS is an effective approach for ranking and picking a number of generally recognized alternatives using distance metrics that is both practical and helpful. TOPSIS is the best compromise choice, having the lowest distance from the positive-ideal solution and the greatest distance from the negative-ideal solution [2–4]. So far, TOPSIS has been thoroughly investigated by explorers and experts, and it has been successfully applied to a wide range of DM g situations [5–8]. e DM g procedure demands the analysis of a small number of possibilities stated in terms of evaluative criteria for the most part. Instead, when analyzing all of the criteria at once, the issue may be to rank these possibilities in terms Hindawi Mathematical Problems in Engineering Volume 2022, Article ID 8442123, 9 pages https://doi.org/10.1155/2022/8442123