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This lecture covers the Simplex Algorithm, focusing on computing reduced costs, determining optimality, unbounded costs, and degenerate problems. It explains the process of updating the basis, pivot columns, and rows, as well as interpreting the tableau and maintaining feasibility. The instructor demonstrates the algorithm through examples, showcasing the steps involved in finding an initial BFS and efficiently computing the basis matrix. The lecture concludes with a discussion on termination conditions and the importance of maintaining a feasible set throughout the algorithm.