A New Approach for Solving Fully Fuzzy Linear Systems | Zendy

Amit Kumar | Zendy; Neetu Neetu | Zendy; Abhinav Bansal | Zendy

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A New Approach for Solving Fully Fuzzy Linear Systems

Author(s) -

Amit Kumar,

Neetu Neetu,

Abhinav Bansal

Publication year - 2011

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2011/943161

Subject(s) - fuzzy logic , fuzzy number , mathematical optimization , constraint (computer aided design) , mathematics , fuzzy associative matrix , defuzzification , linear programming , computer science , fuzzy set operations , fuzzy control system , scope (computer science) , fuzzy set , artificial intelligence , geometry , programming language

Several authors have proposed different methods to find the solution of fully fuzzy linear systems (FFLSs) that is, fuzzy linear system with fuzzy coefficients involving fuzzy variables. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are nonnegative fuzzy numbers. In this paper a new method is proposed to solve an FFLS with arbitrary coefficients and arbitrary solution vector, that is, there is no restriction on the elements that have been used in the FFLS. The primary objective of this paper is thus to introduce the concept and a computational method for solving FFLS with no non negative constraint on the parameters. The method incorporates the principles of linear programming in solving an FFLS with arbitrary coefficients and is not only easier to understand but also widens the scope of fuzzy linear equations in scientific applications. To show the advantages of the proposed method over existing methods we solve three FFLSs

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