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The generalization of optimization theory and techniques to other affirmation constitutes a étendu area of applied mathematics.
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Dynamic programming is the approach to solve the stochastic optimization problem with stochastic, randomness, and unknown model parameters.
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Convex programming studies the case when the équitable function is convex (minimization) or concave (maximization) and the constraint avantage is convex. This can Lorsque viewed as a particular case of nonlinear programming pépite as generalization of linear or convex quadratic programming.