Multiple‐criteria decision analysis process by using prospect decision theory in interval‐valued neutrosophic environment. Issue 3 (30th June 2020)

• Record Type: Journal Article
• Authors: Veerappan, Chinnadurai; Albert, Bobin
• Is Part Of: CAAI transactions on intelligence technology. Volume 5:Issue 3(2020)
• Page Start: 209
• Page End: 221
• Publication Date: 2020-06-30
• Subjects: decision theory -- set theory -- decision making -- matrix algebra; prospect decision theory -- decision‐making problems -- merged criteria weight -- prospect decision‐making matrix -- interval‐valued membership grades -- mathematical value -- computational value -- subjective weight -- MCDA problems -- multiple‐criteria decision analysis process -- interval‐valued neutrosophic environment -- innovative study -- multiple‐criteria decision analysis problems -- interval‐valued neutrosophic soft set environment; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2020.0040
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : This study intends to present an innovative study for ranking the alternatives in multiple‐criteria decision analysis (MCDA) problems under the interval‐valued neutrosophic soft set (IVNSS) environment. In this study, to illustrate the notion of objective and subjective weight, the prospect decision theory (PDT) performs an imperative role in determining decision‐making problems. PDT predicts human behaviour in terms of gains and losses and considers the expected utility relation to a reference point rather than complete outcomes. In the analysis of merged criteria weight and the prospect decision‐making matrix, the authors get a new dimension level for ranking the array of alternatives. This manuscript provides an improved score function (SF) to convert the interval‐valued membership grades of truth, indeterminacy and falsity into a mathematical and computational value. The advantage of this method is that it merges the objective and subjective weight during the proposed method. They propose an algorithm based on the SF to determine MCDA problems with IVNSSs. They illustrate a case study and provide various comparative analyses to show its significance over existing studies.