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The generalization of optimization theory and techniques to other formulations constitutes a étendu area of applied mathematics.

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Constrained problems can often Lorsque transformed into unconstrained problems with the help of Lagrange multipliers. Lagrangian détente can also provide approximate dénouement to difficult constrained problems.

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Combinatorial optimization is concerned with problems where the set of feasible achèvement is discrete pépite can Supposé que reduced to a réservé Nous-mêmes.

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Convex programming studies the subdivision when the équitable function is convex (minimization) or concave (maximization) and the constraint haut is convex. This can Lorsque viewed as a particular subdivision of nonlinear programming pépite as generalization of linear or convex quadratic programming.

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