I have hard time grasping this proof which should follow from duality theorem.
Could someone elaborate on what is going on?
2026-03-29 23:42:47.1774827767
finding feasible solution to LP is equally hard as optimal solution
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Okay, If I understand it correctly...
=> If I have optimal solution to (P) then I create vector y and this combined vector $(x_1,...,x_m,y_1,...y_m)$ is feasible solution to the combined LP.
<= If I have feasible solution to combined program $w=(x_1,...,x_m,y_1,...y_m)$, then I just take x part,and it is optimal solution of (P) because in combined LP we are too maximizing $c^Tx$ subject to Ax<=b.