A New 2-Tuple Linguistic Approach for Unbalanced Linguistic Term Sets

The linguistic terms in a balanced linguistic term set describing qualitative data are symmetrical around the central linguistic word. With the growing complexity of the problems, the symmetric linguistic term set appears to be confined. This work examines the multiple criteria group decision-making problems where decision-makers employ a 2-tuple unbalanced linguistic term set to provide entries of alternativecriteria matrices. We adopt a data envelopment analysis (DEA) method and create a linear programming model to evaluate alternative-criteria weights for each decision-maker. The value function from prospect theory models the non-rational aspect of risk in criteria.The values of prospect gain and prospect loss on cost and benefit criteria are computed and used to create a DEA model that evaluates the weights of each criterion on each alternative. Finally, the entropy values of the cross-efficiency scores deliver a ranking of the alter-I. Khan (corresponding author)

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“…The multiplicative unbalanced 2-tuple linguistic term (MU2LT) set is introduced by Malhotra and Gupta (2020a).…”

Section: Unbalanced Linguistic Term Setmentioning

confidence: 99%

“…and the following procedure Malhotra and Gupta (2020a) is used to compute σ L , σ R , d L , and d R .…”

Section: Unbalanced Linguistic Term Setmentioning

confidence: 99%