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Another mathematical program with the property that its objective is always a bound on the original mathematical program, called the primal. Suppose the dual is LaTeX: \min \{ F(y): y \in Y\}. Then, LaTeX: F(y) \ge f(x) for all feasible LaTeX: x in the primal and all LaTeX: y in Y. This immediately implies that if the primal is feasible, the dual cannot be unbounded, and vice versa: if the dual is feasible, the primal cannot be unbounded. It also implies that if the dual is unbounded, the primal must be infeasible (and vice versa). A dual provides a sufficiency test for optimality, for if feasible LaTeX: x and LaTeX: y can be found such that LaTeX: f(x)=F(y), it follows that LaTeX: x is optimal in the primal and LaTeX: y is optimal in the dual. Weak duality is when this sufficient condition is all that can be guaranteed. Strong duality is when a finite optimal value to one problem ensures the existence of an optimal solution to the other and that their optimal objective values are equal. There are particular duals of significance.

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