Package 'vntrs'

Title: Variable Neighborhood Trust Region Search
Description: Implements the variable neighborhood trust region search (VNTRS) algorithm for nonlinear global optimization, following Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" <doi:10.1287/ijoc.1090.0343>. The method combines neighborhood exploration with a trust-region framework to search the solution space efficiently. It can terminate a local search early when the iterates converge toward a previously visited local optimum or when further improvement within the current region is unlikely. The algorithm can also be used to identify multiple local optima.
Authors: Lennart Oelschläger [aut, cre] (ORCID: <https://orcid.org/0000-0001-5421-9313>)
Maintainer: Lennart Oelschläger <[email protected]>
License: GPL-3
Version: 0.2.1
Built: 2026-05-07 16:15:53 UTC
Source: https://github.com/loelschlaeger/vntrs

Help Index

Variable neighborhood trust region search

Description

Run the variable neighborhood trust region search algorithm.

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 that accepts a numeric parameter vector and returns either

  • a numeric objective value, or

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

Missing derivatives are approximated by finite differences.
npar

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

[logical(1)]
If TRUE, minimize f; otherwise, maximize it.
init_runs

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

[numeric(1)]
Lower and upper bounds for the uniform initialization range.
init_iterlim

[integer(1)]
Maximum trust-region iterations during initialization.
neighborhoods

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

[integer(1)]
Number of trial points sampled in each neighborhood.
beta

[numeric(1)]
Non-negative scaling factor for neighborhood expansion.
iterlim

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

[numeric(1)]
Minimum Euclidean distance for two optima to be treated as distinct.
inferior_tolerance

[numeric(1)]
Maximum objective-value gap from the best known solution before a local optimum is discarded early.
time_limit

[numeric(1) | NULL]
Optional time limit in seconds. 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. Use NULL for unbounded dimensions.
collect_all

[logical(1)]
If TRUE, keep all converged local optima and disable early stopping for optima that are inferior to the best known solution.
quiet

[logical(1)]
If TRUE, suppress progress 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)