Algorithms for possibility linguistic single-valued neutrosophic decision-making based on COPRAS and aggregation operators with new information measures. (May 2019)

• Record Type: Journal Article
• Authors: Garg, Harish; Nancy,
• Is Part Of: Measurement. Volume 138(2019)
• Page Start: 278
• Page End: 290
• Publication Date: 2019-05
• Subjects: Possibility linguistic single-valued neutrosophic set -- Information measure -- Aggregation operator -- COPRAS method -- Distance and entropy measures -- Group decision making process; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.02.031
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Construct a concept of possibility linguistic single-valued neutrosophic set (PLSVNS). We initiate a new axiomatic definition of PLSVN distance measure to compute objective weights. COPRAS method and aggregation operators (AOs) are proposed for PLSVNSs. Two algorithms based on COPRAS and AOs to solve the multi-criteria group decision-making problem are proposed. The effectiveness and feasibility of two algorithms are demonstrated by a numerical example. Abstract: The objective of this work is to introduce the concept of the possibility linguistic single-valued neutrosophic set (PLSVNS) for better dealing with the imprecise and uncertain information during the decision-making process. The prominent characteristics of this set are that it considers two distinctive sorts of information such as the membership, indeterminacy, non-membership degrees, and their corresponding possibility degree. In it, first, we stated some operational laws, score and accuracy functions, comparison laws between the pairs of the set. Then, we define weighted averaging and geometric aggregation operators (AOs) to collaborate the PLSVNSs into a single one. Further, we present two algorithms based on a complex proportional assessment (COPRAS) method and AOs based method under PLSVNS information to solve the decision-making problems. In these methods, the information related to weights of decision makers and criteria is determined with the help of a distance and entropy measures. Finally, a practical real-life example is provided to expose the materialness and the viability of our work.