Gradient algorithm of Geoffrion can solve problems related to linear and non-linear optimizations, provided that decision maker can determine its utility function out of “n” existent goals. However, this diagnosis of utility function doesn’t need its objectivity and direct calculations for the function, but only needs position information of decision maker to continue calculations. Gradient method, due to high convergence speed, has lots of applications in optimization issues. In this article, firstly, gradient method from Geoffrion is described and then some changes are considered due to fuzzy logic. . fuzzy approach is as the mediator between the decision maker and analyst. A problem is solved through these two methods to enable results be compared with each other. Results show that these two are similar with each other in number of steps. However, in the second step of algorithm, using fuzzy logic causes higher speed. Estimation of W, by using fuzzy logic, was easier compared to its previous method

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