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Unformatted text preview: CO350 Linear Programming Chapter 7: The TwoPhase Method 13th June 2005 Chapter 7: The TwoPhase Method 1 Recap In the past week and a half, we learned the simplex method and its relation with duality . By now, you should know how to • solve an LP problem given an initial feasible basis; • give a proof of optimality/unboundedness from the final tableau; • compute/read a dual optimal solution from an optimal tableau; • relate dual optimal solution with shadow prices in the case of nondegeneracy. Chapter 7: The TwoPhase Method 2 Motivation Consider the LP ( P ) max c T x s.t. Ax = b x ≥ We have assumed that a feasible basis is always given. But in practice, it is usually not easy to spot a feasible basis. Duality theory says: optimal solutions to ( P ) and its dual are solutions to Ax = b, x ≥ A T y ≥ c c T x b T y = 0 So, finding feasible solution is as hard as solving L P. Twophase method: an algorithm that solves ( P ) in two phases, where • in Phase 1, we solve an auxiliary LP problem to either get a feasible basis or conclude that ( P ) is infeasible. • in Phase 2, we solve ( P ) starting from the feasible basis found in Phase 1....
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This note was uploaded on 06/11/2011 for the course C 350 taught by Professor Wolkowicz during the Fall '97 term at Waterloo.
 Fall '97
 Wolkowicz

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