In mathematics, nonlinear programming (NLP), also known as nonlinear optimization, is the process of solving an optimization problem where some of the constraints are not linear equalities or the objective function is not a linear function. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear.
x1≥0x2≥0x12+x22≥1x12+x22≤2
with an objective function to be maximized
f(𝐱)=x1x2+x2x3
where 1</sub>, ''x''<sub>2</sub>, ''x''<sub>3</sub>)"}},"i":0}}]}'/>
x = (x1, x2, x3).
ISBN 0-486-43227-0.
Bazaraa, Mokhtar S. and Shetty, C. M. (1979). Nonlinear programming. Theory and algorithms. John Wiley & Sons. Luenberger, David G.; Ye, Yinyu (2008). Linear and nonlinear programming. International Series in Operations Research & Management Science. Vol. 116 (Third ed.). New York: Springer. pp. xiv+546. ISBN 978-0-387-74502-2. MR 2423726.
Nocedal, Jorge and Wright, Stephen J. (1999). Numerical Optimization. Springer. FranceProgrammation non linéaire</span>"}]]}'>BnF datanelineární programování</span>"}]]}'>Czech RepublicIsrael | Other | |
|---|