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indicates that no variable are raised to higher powers, such as squares. Connaissance this class, the problems involve minimizing (pépite maximizing) a linear impartiale function whose variables are real numbers that are constrained to satisfy a system of linear equalities and inequalities. Another grave class of optimization is known as nonlinear programming. In nonlinear programming the variable are real numbers, and the impartiale pépite some of the constraints are nonlinear functions (possibly involving squares, jardin roots, trigonometric functions, or products of the capricieux). Both linear and nonlinear programming are discussed in this rubrique.
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More recently there ha been much interest in solving large linear problems with special structures—conscience example, corporate models and national organisation models that are multistaged, are dynamic, and exhibit a hierarchical charpente.
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