Finding the numerical compensation in multiple criteria decision-making problems under fuzzy environment

Gupta, Mayank; Mohanty, B. K.

doi:10.1080/00207721.2016.1252990

Cited by 2 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some works are available [11,24] that incorporate the level of tranquillity in decision making when the decision function is stated as a fuzzy set. However, the methodologies in [11,24] are unsuitable when the alternatives are evaluated in HFLVs. To our knowledge, there is no method available in the literature that derives tranquillity in decisions with HFLV data.…”

Section: Tranquillity and Anxiety In Hfltsmentioning

confidence: 99%

See 1 more Smart Citation

Set-valued Rough Set in Multi-Attribute Decision Making with Interactive Attributes

Mohanty

Aggarwal

2023

Preprint

View full text Add to dashboard Cite

The proposed work introduces a new methodology for solving Multiple Attribute Decision Making (MADM) problems in which the alternatives are assessed as hesitant fuzzy linguistic value (HFLV) over the attributes. The proposed MADM problem is exhibited as a rough set model with set-valued data as HFLVs. A similarity measure is defined in the set-valued information system that aids to remove the irrelevant or redundant attributes. The uncertainty due to hesitancy in HFLVs and the linked anxiety of the decision-maker therein are derived in our work after introducing the concept of the tranquility (or anxiety) in HFLTS. The proposed work introduces a new aggregation operator, Indexed Choquet Integral (ICI) that (a) aggregates the interactive attributes, (b) incorporates the decision-maker’s level of tranquility in the aggregation process, and c) estimates the weights and capacity weights of the attributes after assimilating the level of tranquilities appropriately. A comparative analysis of our paper with similar works is made and the advantages in our work are shown. The procedure introduced in the proposed work is demonstrated through a numerical example.

show abstract