A New Algorithm on Pythagorean Fuzzy-Based Multi-Criteria Decision-Making and Its Application

Abstract

The rapid growth in information technology (IT) and the implementation of IT tools has aided hospitals in delivering healthcare at an unprecedented pace. However, without the proper knowledge and understanding of software tools, healthcare establishments may find it difficult to select the best hospital management system software solution for their business. In this paper, a problem based on multi-criteria decision-making (MCDM) is modelled to identify the best hospital management software on the basis of a thorough analysis of every aspect of the healthcare needs and required software competencies, so that hospitals can select a robust hospital management software system. This article presents an extended MCDM method for estimating and selecting robust hospital management system alternatives using the Pythagorean fuzzy method based on the removal effects of criteria (MEREC) and stepwise weight assessment ratio analysis (SWARA). To do this, the objective weights and subjective weights are assessed by the MEREC and SWARA models, and the measurement alternatives and ranking according to compromise solution (MARCOS) method determines the order of preference of the alternatives on the basis of the Pythagorean fuzzy set. Moreover, after in-depth analysis of every aspect of healthcare needs and required software competencies in India, the proposed method is designed to identify the best hospital management software tool, so that the hospital can choose a robust hospital management system. Comparative discussion is presented to exhibit the rationality and sustainability of the established approach to prioritize hospital management software options.

Evaluation of Enterprise Decarbonization Scheme Based on Grey-MEREC-MAIRCA Hybrid MCDM Method

“…The MARCOS method was employed for evaluations, and the obtained results were compared with ranks determined by TOPSIS, ARAS, MABAC, SAW, WASPAS, CoCoSo, and EDAS methods. Chaurasiya and Jain [53] applied the Pythagorean fuzzy MEREC method along with the SWARA weighting method using the MARCOS method to evaluate a hospital management system. Some industrial applications of the MEREC are presented as paramount to the reduction in carbon; Keshavarz-Ghorabaee [54] combined the SWARA and MEREC methods to determine the weights and assess the distribution center of a detergent and hygienic company.…”

New Pythagorean Fuzzification Based on Survey Responses to Rank Learning Approach

“…A novel normalisation score function for PFN is presented that minimises information loss while accounting for uncertainty. The suggested combined weight framework is based on the MEREC and SWARA weighted extensive approaches, and it is both objective and subjective (6) .…”

“…The study's findings will help decisionmakers understand what the student minds require. A survey questionnaire designed for the planned study was completed by 132 students from various grade levels (6)(7)(8)(9)(10)(11)(12) and schools. The COVID-19 epidemic phase led to the adoption of several fresh policies by the Tamilnadu government to improve the way that children learn.…”