Abstract
This article is devoted to the problem of decision making under linguistic uncertainty. The effective method for modelling linguistic uncertainty is the fuzzy set theory. There are several types of fuzzy number types proposed by L. Zadeh: fuzzy type-1, fuzzy type-2, Z-numbers. Chen proposed concept of generalized fuzzy numbers. Generalized trapezoidal fuzzy numbers (GTFN) one of effective approach which can be used for modeling linguistic uncertainty. GFTN very convenient model which allow take in account second order uncertainty. GFTN are formalized and major operations are described as practical problem is considered group decision making for supplier selection. In this case the criteria assessments are expressed by experts in linguistic form. Group decision making model is presented as 2 step aggregation procedure, in first step is aggregated value of alternative by expert, in second step by criteria. Numerical example with four criteria and three alternatives are presented and solved.
Highlights
Decision making problem with imperfect information is very actual problem
The are many scientific works dedicated to applications of classical fuzzy approach which is named fuzzy type-1 proposed by L
Zadeh [2] proposed more general approach fuzzy type-2, which expands the features of classical fuzzy type-1 model
Summary
DECISION MAKING UNDER LINGUISTIC UNCERTAINTY CONDITIONS ON BASE OF GENERALIZED FUZZY NUMBERS. Of "Computer engineering department" Azerbaijan state oil and industry university, Baku, Azerbaijan Republic, ORCID ID https://orcid.org/0000-0002-0590-5437. KEYWORDS linguistic uncertanty, decision making, membership function, aggregation, multi attribute decision making, generalized fuzzy numbers
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.