# nloptr-package

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Percentile

##### R interface to NLopt

nloptr is an R interface to NLopt, a free/open-source library for nonlinear optimization started by Steven G. Johnson, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. The NLopt library is available under the GNU Lesser General Public License (LGPL), and the copyrights are owned by a variety of authors. Most of the information here has been taken from http://ab-initio.mit.edu/nlopt{the NLopt website}, where more details are available.

NLopt addresses general nonlinear optimization problems of the form:

min f(x) x in R^n

s.t. g(x)

Keywords
optimize, interface
##### Details

ll{ Package: nloptr Type: Package Version: 0.8.2 Date: 2011-06-09 License: L-GPL LazyLoad: yes }

##### Note

See ?nloptr for more examples.

##### References

Steven G. Johnson, The NLopt nonlinear-optimization package, http://ab-initio.mit.edu/nlopt

##### See Also

optim nlm nlminb Rsolnp ssolnp

##### Aliases
• nloptr-package
##### Examples
# Example problem, number 71 from the Hock-Schittkowsky test suite.
#
# \min_{x} x1*x4*(x1 + x2 + x3) + x3
# s.t.
#    x1*x2*x3*x4 >= 25
#    x1^2 + x2^2 + x3^2 + x4^2 = 40
#    1 <= x1,x2,x3,x4 <= 5
#
# we re-write the inequality as
#   25 - x1*x2*x3*x4 <= 0
#
# and the equality as
#   x1^2 + x2^2 + x3^2 + x4^2 - 40 = 0
#
# x0 = (1,5,5,1)
#
# optimal solution = (1.00000000, 4.74299963, 3.82114998, 1.37940829)

library('nloptr')

#
# f(x) = x1*x4*(x1 + x2 + x3) + x3
#
eval_f <- function( x ) {
return( list( "objective" = x*x*(x + x + x) + x,
"gradient" = c( x * x + x * (x + x + x),
x * x,
x * x + 1.0,
x * (x + x + x) ) ) )
}

# constraint functions
# inequalities
eval_g_ineq <- function( x ) {
constr <- c( 25 - x * x * x * x )

grad   <- c( -x*x*x,
-x*x*x,
-x*x*x,
-x*x*x )
return( list( "constraints"=constr, "jacobian"=grad ) )
}

# equalities
eval_g_eq <- function( x ) {
constr <- c( x^2 + x^2 + x^2 + x^2 - 40 )

grad   <- c(  2.0*x,
2.0*x,
2.0*x,
2.0*x )
return( list( "constraints"=constr, "jacobian"=grad ) )
}

# initial values
x0 <- c( 1, 5, 5, 1 )

# lower and upper bounds of control
lb <- c( 1, 1, 1, 1 )
ub <- c( 5, 5, 5, 5 )

local_opts <- list( "algorithm" = "NLOPT_LD_MMA",
"xtol_rel"  = 1.0e-7 )
opts <- list( "algorithm" = "NLOPT_LD_AUGLAG",
"xtol_rel"  = 1.0e-7,
"maxeval"   = 1000,
"local_opts" = local_opts )

res <- nloptr( x0=x0,
eval_f=eval_f,
lb=lb,
ub=ub,
eval_g_ineq=eval_g_ineq,
eval_g_eq=eval_g_eq,
opts=opts)
print( res )
Documentation reproduced from package nloptr, version 0.8.4, License: LGPL

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