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There are 2 ideas elementary to duality theory. One is the fact that (for your symmetric dual) the dual of the dual linear program is the first primal linear application. Moreover, each feasible Resolution for a linear plan presents a bound over the optimum value of the target perform of its dual.

This theorem allows statisticians to draw responsible conclusions about population parameters and make correct predictions, crucial for knowledgeable choice-earning in several enterprise scenarios.

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Masking and packing LPs generally arise like a linear programming relaxation of the combinatorial problem and are important from the study of approximation algorithms.

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Furthermore, if the dual is unbounded, then the primal should be infeasible. Nevertheless, it is possible for both the dual along with the primal to be infeasible. See dual linear program for aspects and several other far more illustrations.

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