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  "body": "\n## Summary\n\nLinear programming is the optimization of a linear function over the set of solutions of finitely many linear inequalities.\nThe feasible set is a convex polyhedron.\nWhen an optimum exists, it is attained on a face, and at a vertex when the polyhedron has vertices.\nEach linear program has a dual program.\nIf one of the two has an optimal solution, so does the other, with the same optimal value; this is tied to [[Farkas' lemma|FYZC634H2D]].\nLinear programs are solved in practice by the [[simplex algorithm|MH272QHWPM]] and by interior point methods.\nThe ellipsoid method and interior point methods solve them in polynomial time.\n\n## Explanations\n\n### L1 human\n\nA factory makes two products, each using some amounts of limited resources, and earns some profit on each.\nHow much of each should it make to earn the most?\nThe limits are straight-line conditions, so the allowed plans form a polygon, and the best plan is found at one of its corners.\nLinear programming is the study of such problems, with any number of variables and conditions.\n",
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