<![CDATA[SMEs in Indonesia face significant challenges in optimizing their production due to limited resources, particularly in terms of time and labor. This study proposes the application of the Modified Wolfe Simplex Method to optimize the production of two main fashion products—shirts and trousers—within a clothing SME. The method employs principles of linear programming, Lagrangian functions, and Karush-Kuhn-Tucker (KKT) optimality conditions to identify efficient and strategic solutions. The main objective of this research is to determine the optimal production combination to maximize profit under time constraints in cutting and sewing processes. Production data were analyzed using an iterative Simplex approach, enhanced by Wolfe’s modification to explore system sensitivity to changes in resource availability. The results show that the optimal production consists of 8 shirts and 12 trousers, yielding a maximum profit of IDR 1,440,000. The Lagrange multipliers λ₁ = 8/19 and λ₂ = 18/19 indicate the potential for additional profit if work capacity is increased by one unit in each process. The shadow prices of the constraints further suggest opportunities for increased profitability through capacity expansion. This study concludes that the method is effective in supporting data-driven production decision-making. Future research is recommended to accommodate more variables and integrate digital systems for continuous optimization. Keywords: Simplex Method, Wolfe, Production Optimization, Linear Programming, MSMEs.]]>
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