Description Usage Arguments Value References Examples
This function performs variable neighborhood trust region search.
1 
f 
A function that computes value, gradient, and Hessian of the function to be
optimized and returns them as a named list with elements 
npar 
The number of parameters of 
minimize 
If 
controls 
Either

quiet 
If 
seed 
Set a seed for the sampling of the random starting points. 
A data frame. Each row contains information of an identified optimum. The
first npar
columns "p1"
,...,"p<npar>"
store the argument
values, the next column "value"
has the optimal function values and
the last column "global"
contains TRUE
for global optima and
FALSE
for local optima.
Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" doi: 10.1287/ijoc.1090.0343.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  rosenbrock = function(x) {
stopifnot(is.numeric(x))
stopifnot(length(x) == 2)
f = expression(100 * (x2  x1^2)^2 + (1  x1)^2)
g1 = D(f, "x1")
g2 = D(f, "x2")
h11 = D(g1, "x1")
h12 = D(g1, "x2")
h22 = D(g2, "x2")
x1 = x[1]
x2 = x[2]
f = eval(f)
g = c(eval(g1), eval(g2))
h = rbind(c(eval(h11), eval(h12)), c(eval(h12), eval(h22)))
list(value = f, gradient = g, hessian = h)
}
vntrs(f = rosenbrock, npar = 2, seed = 1, controls = list(neighborhoods = 1))

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