nlminb2: Nonlinear programming with nonlinear constraints.

In ROI: R Optimization Infrastructure

Nonlinear programming with nonlinear constraints.

Description

This function was contributed by Diethelm Wuertz.

Usage

nlminb2(
  start,
  objective,
  eqFun = NULL,
  leqFun = NULL,
  lower = -Inf,
  upper = Inf,
  gradient = NULL,
  hessian = NULL,
  control = list()
)

Arguments

start	numeric vector of start values.
objective	the function to be minimized f(x).
eqFun	functions specifying equal constraints of the form h_i(x) = 0. Default: NULL (no equal constraints).
leqFun	functions specifying less equal constraints of the form g_i(x) <= 0. Default: NULL (no less equal constraints).
lower	a numeric representing lower variable bounds. Repeated as needed. Default: -Inf.
upper	a numeric representing upper variable bounds. Repeated as needed. Default: Inf.
gradient	gradient of f(x). Default: NULL (no gradiant information).
hessian	hessian of f(x). Default: NULL (no hessian provided).
control	a list of control parameters. See nlminb() for details. The parameter "scale" is set here in contrast to nlminb() .

Value

list()

Author(s)

Diethelm Wuertz

Examples

## Equal constraint function
eval_g0_eq <- function( x, params = c(1,1,-1)) {
       return( params[1]*x^2 + params[2]*x + params[3] )
   }
eval_f0 <- function( x, ... ) {
       return( 1 )
   }

ROI documentation built on April 21, 2023, 1:11 a.m.