<![CDATA[This study presents a comparative analysis of the fuzzy simplex method and Kumar’s method in solving production optimization problems based on Fully Fuzzy Linear Programming (FFLP). Since production systems often involve uncertainty in costs, resource availability, and market demand, all model parameters are represented using Trapezoidal Fuzzy Numbers. A quantitative comparative approach was employed using simulation data with two decision variables. The optimization model was solved using both methods, with Kumar’s method utilizing the Liou–Wang ranking function. The results show that the two methods produce the same optimal decision variable values, fuzzy profit values, and number of iterations required to achieve optimality. However, Kumar’s method offers a simpler computational procedure through ranking-based pivot selection, while the fuzzy simplex method better preserves fuzzy information during the iterative process. These findings indicate that both methods are effective for solving FFLP-based production optimization problems, with differences primarily in their computational mechanisms and operational complexity.]]>
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