Interval rough integrated SWARA-ELECTRE model: An application to machine tool remanufacturing

Abstract

Rough set theory is an efficient and flexible tool for the removal of unnecessary or irrelevant attributes present in the evaluation process and interval rough numbers (IRNs) are designed to effectively treat the inherited uncertainty in human assessments in the multi-criteria decision making (MCDM) problems. In the ELECTRE (ELimination and Choice Expressing REality) family of MCDM techniques, the options that are outranked by others are eliminated in order to present the most accurate and feasible set of actions or solutions to the core problem. In order to deal with the subjectivity and unpredictability in judgements made by experts without much prior knowledge, membership functions, or other changes, this research study offers an innovative MCDM methodology that integrates interval rough numbers, Step-wise Weight Assessment Ratio Analysis (SWARA), and the ELECTRE I method (named as IRN SWARA ELECTRE I Model). To examine the uncertainty in linguistic terms, IRNs are employed, but intervals rather than single fixed values are used. Three kinds of interval rough concordance and discordance sets are defined to build the proposed strategy. The criteria weights are computed by employing effective and simplified technique of interval rough SWARA having the ability to deal with preference ratings in the form of IRNs. The applicability of the proposed methodology is demonstrated by solving a case study related to assessment of machine tool remanufacturing models. To elaborate the authenticity, rationality, out-performance, and efficacy of findings, a comprehensive comparative study as well as sensitivity analysis are conducted.