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Variable neighborhood trust region search

Source: R/vntrs.R
vntrs.Rd

This function performs variable neighborhood trust region search.

Usage

vntrs(
  f,
  npar,
  minimize = TRUE,
  init_runs = 5L,
  init_min = -1,
  init_max = 1,
  init_iterlim = 20L,
  neighborhoods = 5L,
  neighbors = 5L,
  beta = 0.05,
  iterlim = 100L,
  tolerance = 1e-06,
  inferior_tolerance = 1e-06,
  time_limit = NULL,
  cores = 1L,
  lower = NULL,
  upper = NULL,
  collect_all = FALSE,
  quiet = TRUE
)

Arguments

f

[function]
A function, returning either

  • a numeric objective value or

  • a list with element value and optional gradient and hessian components

for a numeric parameter vector. Missing derivatives are approximated by finite differences.

npar

[integer(1)]
The number of parameters of f.

minimize

[logical(1)]
Minimize f?

init_runs

[integer(1)]
Number of random starting points for the initialization stage.

init_min, init_max

[numeric(1)]
Lower and upper bound for the uniform sampling range during initialization.

init_iterlim

[integer(1)]
Maximum iterations of the trust-region method during initialization.

neighborhoods

[integer(1)]
Number of neighborhood expansions to perform.

neighbors

[integer(1)]
Number of neighboring points drawn in each neighborhood.

beta

[numeric(1)]
Non-negative scaling factor that controls the neighborhood expansion.

iterlim

[integer(1)]
Maximum iterations of the trust-region method during the main search.

tolerance

[numeric(1)]
Minimum distance between optima candidates to consider them distinct.

inferior_tolerance

[numeric(1)]
Maximum allowed difference from the best known objective value when deciding if a local optimum should be discarded early.

time_limit

[integer(1) | NULL]
Optional time limit (in seconds) for the search. If reached, the search stops early with a warning.

cores

[integer(1)]
Number of CPU cores used for parallel evaluation.

lower, upper

[numeric(npar) | NULL]
Optional lower and upper parameter bounds.

collect_all

[logical(1)]
Keep every converged local optimum even if it is inferior to the best known solution and disable early stopping?

quiet

[logical(1)]
Suppress messages?

Value

A data.frame summarizing the identified optima or NULL if none could be determined.

References

Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" doi:10.1287/ijoc.1090.0343 .

Examples

rosenbrock <- function(x) 100 * (x[2] - x[1]^2)^2 + (1 - x[1])^2
vntrs(f = rosenbrock, npar = 2)
#>   p1 p2        value global
#> 1  1  1 5.916025e-20   TRUE