cobyla  R Documentation 
COBYLA is an algorithm for derivativefree optimization with nonlinear inequality and equality constraints (but see below).
cobyla(
x0,
fn,
lower = NULL,
upper = NULL,
hin = NULL,
nl.info = FALSE,
control = list(),
deprecatedBehavior = TRUE,
...
)
x0 
starting point for searching the optimum. 
fn 
objective function that is to be minimized. 
lower , upper 
lower and upper bound constraints. 
hin 
function defining the inequality constraints, that is

nl.info 
logical; shall the original NLopt info be shown. 
control 
list of options, see 
deprecatedBehavior 
logical; if 
... 
additional arguments passed to the function. 
It constructs successive linear approximations of the objective function and
constraints via a simplex of n+1
points (in n
dimensions), and
optimizes these approximations in a trust region at each step.
COBYLA supports equality constraints by transforming them into two
inequality constraints. This functionality has not been added to the wrapper.
To use COBYLA with equality constraints, please use the full
nloptr
invocation.
List with components:
par 
the optimal solution found so far. 
value 
the function value corresponding to 
iter 
number of (outer) iterations, see 
convergence 
integer code indicating successful completion (> 0) or a possible error number (< 0). 
message 
character string produced by NLopt and giving additional information. 
The original code, written in Fortran by Powell, was converted in C for the SciPy project.
Hans W. Borchers
M. J. D. Powell, “A direct search optimization method that models the objective and constraint functions by linear interpolation,” in Advances in Optimization and Numerical Analysis, eds. S. Gomez and J.P. Hennart (Kluwer Academic: Dordrecht, 1994), p. 5167.
bobyqa
, newuoa
## Solve the HockSchittkowski problem no. 100 with analytic gradients
## See https://apmonitor.com/wiki/uploads/Apps/hs100.apm
x0.hs100 < c(1, 2, 0, 4, 0, 1, 1)
fn.hs100 < function(x) {(x[1]  10) ^ 2 + 5 * (x[2]  12) ^ 2 + x[3] ^ 4 +
3 * (x[4]  11) ^ 2 + 10 * x[5] ^ 6 + 7 * x[6] ^ 2 +
x[7] ^ 4  4 * x[6] * x[7]  10 * x[6]  8 * x[7]}
hin.hs100 < function(x) {c(
2 * x[1] ^ 2 + 3 * x[2] ^ 4 + x[3] + 4 * x[4] ^ 2 + 5 * x[5]  127,
7 * x[1] + 3 * x[2] + 10 * x[3] ^ 2 + x[4]  x[5]  282,
23 * x[1] + x[2] ^ 2 + 6 * x[6] ^ 2  8 * x[7]  196,
4 * x[1] ^ 2 + x[2] ^ 2  3 * x[1] * x[2] + 2 * x[3] ^ 2 + 5 * x[6] 
11 * x[7])
}
S < cobyla(x0.hs100, fn.hs100, hin = hin.hs100,
nl.info = TRUE, control = list(xtol_rel = 1e8, maxeval = 2000),
deprecatedBehavior = FALSE)
## The optimum value of the objective function should be 680.6300573
## A suitable parameter vector is roughly
## (2.330, 1.9514, 0.4775, 4.3657, 0.6245, 1.0381, 1.5942)
S
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.