Linear Programming

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The original linear programming had been first manufactured by Leonid Kantorovich in 1939. Leonid Kantorovich produced the earliest thready programming problems found in 1939 for employ during World Conflict IIto plan costs and returns inside order to keep costs down to the armed service and increase loss for the enemy. Typically the method was retained secret until 1947 when George M. Dantzig published typically the simplex method and John von Neumann developed the theory of duality as a geradlinig optimization solution, and applied it in the field of game theory. Postwar, many industries found its use in their daily planning. More formally, linear programming is a technique for the optimization of a geradlinig objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polyhedron, which is a set defined as typically the intersection of finitely many half places, everyone of which is usually defined by way of a linear inequality. Its aim function is actually a real-valued affine function identified on this polyhedron.

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