TWO SQUARE DETERMINANT APPROACH FOR SOLVING SIMPLEX METHOD, BY JERVIN ZON'LOBO.

This study presents the Two Square Determinant Approach for solving the Simplex Method, an alternative mathematical technique for solving linear programming problems. The method, attributed to Jervin Zon'Lobo, utilizes determinant-based computations and Cramer’s Rule to obtain optimal solutions without the need for iterative simplex tables. The research aims to simplify the process of solving optimization problems, particularly for systems involving two decision variables. The study adopts an analytical methodology, where selected linear programming problems are solved using the Two Square Determinant Approach and compared with results obtained from the conventional Simplex Method. Findings reveal that the determinant approach provides accurate results with reduced computational steps for small-scale problems. It enhances clarity and reduces the complexity associated with pivot operations in the simplex method. However, the study also identifies limitations of the approach, especially when applied to problems involving more than two variables, where determinant calculations become cumbersome. The research concludes that the Two Square Determinant Approach is an effective and efficient alternative for solving simple linear programming problems and serves as a valuable instructional tool in understanding optimization techniques. The study recommends the use of this method in teaching linear programming at introductory levels and suggests further research to extend its application to more complex optimization models.