Nonlinear programming: Difference between revisions
Jump to navigation
Jump to search
imported>Igor Grešovnik m (corrected link (linear)) |
imported>Igor Grešovnik m (→Mathematical formulation: vectors in bold) |
||
| Line 3: | Line 3: | ||
== Mathematical formulation == | == Mathematical formulation == | ||
A '''nonlinear programming problem''' can be stated as: | A '''nonlinear programming problem''' can be stated as: | ||
:<math>\min_{x \in X}f(x)</math> | :<math>\min_{\bold{x} \in X}f(\bold{x})</math> | ||
or | or | ||
:<math>\max_{x \in X}f(x)</math> | :<math>\max_{\bold{x} \in X}f(\bold{x})</math> | ||
where | where | ||
:<math>f: R^n \to R</math> | :<math>f: R^n \to R</math> | ||
:<math>X \subseteq R^n.</math> | :<math>X \subseteq R^n.</math> | ||
== See also == | == See also == | ||
Revision as of 13:11, 13 November 2007
In mathematics, nonlinear programming (NLP) is the process of minimization or maximization of a function of a set of real variables (termed objective function), while simultaneously satisfying a set of equalities and inequalities ( collectively termed constraints), where some of the constraints or the objective function are nonlinear.
Mathematical formulation
A nonlinear programming problem can be stated as:
or
where
