A comparative study on interval arithmetic operations with intuitionistic fuzzy numbers for solving an intuitionistic fuzzy multi–objective linear programming problem

In a real world situation, whenever ambiguity exists in the modeling of intuitionistic fuzzy numbers (IFNs), interval valued intuitionistic fuzzy numbers (IVIFNs) are often used in order to represent a range of IFNs unstable from the most pessimistic evaluation to the most optimistic one. IVIFNs are...

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Veröffentlicht in:	International journal of applied mathematics and computer science Jg. 27; H. 3; S. 563 - 573
Hauptverfasser:	Vidhya, Rajendran, Irene Hepzibah, Rajkumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Zielona Góra Sciendo 01.09.2017 De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Schlagworte:	Interval arithmetic interval valued intuitionistic fuzzy arithmetic interval valued intuitionistic fuzzy multi-objective linear programming problem interval valued intuitionistic fuzzy number Linear programming Mathematical programming modified interval valued intuitionistic fuzzy arithmetic Multiple objective analysis Pareto optimum pentagonal intuitionistic fuzzy number Preempting
ISSN:	2083-8492, 1641-876X, 2083-8492
Online-Zugang:	Volltext
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Zusammenfassung:	In a real world situation, whenever ambiguity exists in the modeling of intuitionistic fuzzy numbers (IFNs), interval valued intuitionistic fuzzy numbers (IVIFNs) are often used in order to represent a range of IFNs unstable from the most pessimistic evaluation to the most optimistic one. IVIFNs are a construction which helps us to avoid such a prohibitive complexity. This paper is focused on two types of arithmetic operations on interval valued intuitionistic fuzzy numbers (IVIFNs) to solve the interval valued intuitionistic fuzzy multi-objective linear programming problem with pentagonal intuitionistic fuzzy numbers (PIFNs) by assuming different and cut values in a comparative manner. The objective functions involved in the problem are ranked by the ratio ranking method and the problem is solved by the preemptive optimization method. An illustrative example with MATLAB outputs is presented in order to clarify the potential approach.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	2083-8492 1641-876X 2083-8492
DOI:	10.1515/amcs-2017-0040