check_f

This function checks the input <code>f</code>.

internal

An implementation of the variable neighborhood trust region
algorithm Bierlaire et al. (2009) "A Heuristic for Nonlinear Global
Optimization" <doi:10.1287/ijoc.1090.0343>.

Lennart Oelschläger

vntrs

Variable Neighborhood Trust Region Search

check_f function

<dl><dt>f</dt>
<dd>A function that computes value, gradient, and Hessian of the function to be
optimized and returns them as a named list with elements <code>value</code>,
<code>gradient</code>, and <code>hessian</code>.</dd>
<dt>npar</dt>
<dd>The number of parameters of <code>f</code>.</dd>
<dt>controls</dt>
<dd>Either <code>NULL</code> or a named list with the following elements. Missing
elements are set to the default values in parentheses.<ul>
<li><code>init_runs</code> (<code>5</code>):
The number of initial searches.</li>
<li><code>init_min</code> (<code>-1</code>):
The minimum argument value for the random initialization.</li>
<li><code>init_max</code> (<code>1</code>):
The maximum argument value for the random initialization.</li>
<li><code>init_iterlim</code> (<code>20</code>):
The number of iterations for the initial searches.</li>
<li><code>neighborhoods</code> (<code>5</code>):
The number of nested neighborhoods.</li>
<li><code>neighbors</code> (<code>5</code>):
The number of neighbors in each neighborhood.</li>
<li><code>beta</code> (<code>0.05</code>):
A non-negative weight factor to account for the function's curvature in the
selection of the neighbors. If <code>beta = 0</code>, the curvature is ignored.
The higher the value, the higher the probability of selecting a neighbor in
the direction of the highest function curvature.</li>
<li><code>iterlim</code> (<code>1000</code>):
The maximum number of iterations to be performed before the local search is
terminated.</li>
<li><code>tolerance</code> (<code>1e-6</code>):
A positive scalar giving the tolerance for comparing different optimal
arguments for equality.</li>
<li><code>time_limit</code> (<code>NULL</code>):
The time limit in seconds for the algorithm.</li>
</ul></dd></dl>

Arguments

Check function — check_f

<dl>

<dt>f</dt>
<dd>A function that computes value, gradient, and Hessian of the function to be
optimized and returns them as a named list with elements <code>value</code>,
<code>gradient</code>, and <code>hessian</code>.</dd>


<dt>npar</dt>
<dd>The number of parameters of <code>f</code>.</dd>


<dt>controls</dt>
<dd>Either <code>NULL</code> or a named list with the following elements. Missing
elements are set to the default values in parentheses.<ul>
<li><code>init_runs</code> (<code>5</code>):
The number of initial searches.</li>
<li><code>init_min</code> (<code>-1</code>):
The minimum argument value for the random initialization.</li>
<li><code>init_max</code> (<code>1</code>):
The maximum argument value for the random initialization.</li>
<li><code>init_iterlim</code> (<code>20</code>):
The number of iterations for the initial searches.</li>
<li><code>neighborhoods</code> (<code>5</code>):
The number of nested neighborhoods.</li>
<li><code>neighbors</code> (<code>5</code>):
The number of neighbors in each neighborhood.</li>
<li><code>beta</code> (<code>0.05</code>):
A non-negative weight factor to account for the function's curvature in the
selection of the neighbors. If <code>beta = 0</code>, the curvature is ignored.
The higher the value, the higher the probability of selecting a neighbor in
the direction of the highest function curvature.</li>
<li><code>iterlim</code> (<code>1000</code>):
The maximum number of iterations to be performed before the local search is
terminated.</li>
<li><code>tolerance</code> (<code>1e-6</code>):
A positive scalar giving the tolerance for comparing different optimal
arguments for equality.</li>
<li><code>time_limit</code> (<code>NULL</code>):
The time limit in seconds for the algorithm.</li>
</ul></dd>

</dl>

check_f: Check function

Description

Usage

Value

Arguments