Optimization Techniques for Decision-making and Information Security

A New Algorithm for Solving Fully Fuzzy Linear Programming Problems using the Lexicographic Method

Author(s): Anil Kumar Nishad*, Gunjan Agarwal, S. R. Singh and Gajraj Singh

Pp: 48-61 (14)

DOI: 10.2174/9789815196320124030007

* (Excluding Mailing and Handling)


In the current situation, ranking a general fuzzy number is a difficult task, and various ranking methods have been developed, but no perfect ranking method exists. To solve fully fuzzy linear programming problems, many ranking functions have been developed and implemented in the literature. However, all of these methods have some limitations. In this chapter, we propose a new method for comparing two triangular fuzzy numbers in a generalised form. The Ezzati method [1] has been expanded upon using the suggested approach to handle fully fuzzy linear programming issues (FFLPP). The implementation of the developed algorithm has been illustrated through numerical illustrations. The proposed algorithm has been applied to a transportation problem in light of extensive testing, and it has been discovered that it is effective and generally offers a better solution.

Keywords: Fully fuzzy linear programming problem (FFLPP), Triangular fuzzy number (TFN), Ranking function, Dummy fuzzy variable.

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