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This lecture covers the process of solving Linear Programs (LPs) using the original 19th-century simplex method, including the algorithm's steps, iterations, and key takeaways on the closeness of variables. The instructor demonstrates how small changes in variables can lead to significant outcomes, proving this in two steps. The lecture emphasizes the importance of small increments in variables to achieve optimal results.
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