Journal of Applied Mathematics

Two Weighted Fuzzy Goal Programming Methods to Solve Multiobjective Goal Programming Problem

Mousumi Gupta and Debasish Bhattacharjee

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We propose two new methods to find the solution of fuzzy goal programming (FGP) problem by weighting method. Here, the relative weights represent the relative importance of the objective functions. The proposed methods involve one additional goal constraint by introducing only underdeviation variables to the fuzzy operator λ (resp., 1-λ), which is more efficient than some well-known existing methods such as those proposed by Zimmermann, Hannan, Tiwari, and Mohamed. Mohamed proposed that every fuzzy linear program has an equivalent weighted linear goal program where the weights are restricted as the reciprocals of the admissible violation constants. But the above proposition of Mohamed is not always true. Furthermore, the proposed methods are easy to apply in real-life situations which give better solution in the sense that the objective values are sufficiently closer to their aspiration levels. Finally, for illustration, two real examples are used to demonstrate the correctness and usefulness of the proposed methods.

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J. Appl. Math., Volume 2012 (2012), Article ID 796028, 20 pages.

First available in Project Euclid: 14 December 2012

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Gupta, Mousumi; Bhattacharjee, Debasish. Two Weighted Fuzzy Goal Programming Methods to Solve Multiobjective Goal Programming Problem. J. Appl. Math. 2012 (2012), Article ID 796028, 20 pages. doi:10.1155/2012/796028.

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