An Advanced Approach to HFP-Soft Set Based Decision- Making in Uncertain Environment

Abstract

Uncertainty, vagueness and the representation of imperfect knowledge have been a problem in many fields of research, such as environmental science, artificial intelligence, network and communication, signal processing, machine learning, computer science, information technology, as well as medical science, economics, and engineering. Decisionmaking methods (simply, DMMs) based on hesitant fuzzy sets (HFSs) and soft sets (SSs) have recently received a lot of attention. Karamaz and Karaaslan (2021)proposed an approach to hesitant fuzzy parameterized soft set (HFPSS) based decision making using score function on hesitant fuzzy elements (HFEs) in HFPSS, with the goal of using HFSs and SSs more effectively for uncertainty issues prevalent in most real-world issues, but it has some limitations in solving HFPSS based decision-making problems (briefly, DMPs). In this study, we demonstrated with a real-life example that the Karamaz-Karaaslan DMM is insufficient to solve HFPSS based DMPs and we have proposed an advanced and adjustable DMM for solving HFPSS based DMPs in uncertain environment. Some reallife examples are provided to demonstrate the validity of our proposed modified DMM.