approximateRefSets

The function takes an data frame with columns at least
specified by <code>obj.cols</code> and &#8220;prob&#8221;. The reference set for
each unique problem in column &#8220;prob&#8221; is then obtained by
combining all approximation sets generated by all considered algorithms
for the corresponding problem and filtering the non-dominated solutions.

Framework for building evolutionary algorithms for both single- and multi-objective continuous or discrete optimization problems. A set of predefined evolutionary building blocks and operators is included. Moreover, the user can easily set up custom objective functions, operators, building blocks and representations sticking to few conventions. The package allows both a black-box approach for standard tasks (plug-and-play style) and a much more flexible white-box approach where the evolutionary cycle is written by hand.

Jakob Bossek

Evolutionary Computation in R

Michael H. Buselli

Wessel Dankers

Carlos M. Fonseca

Manuel Lopez-Ibanez

Luis Paquete

Joshua Knowles

Eckart Zitzler

Olaf Mersmann

approximateRefSets function

<dl><dt>df</dt>
<dd>[<code>data.frame</code>] 
Data frame with the required structure.</dd>
<dt>obj.cols</dt>
<dd>[<code>character(&gt;= 2)</code>] 
Column names of the objective functions.</dd>
<dt>as.df</dt>
<dd>[<code>logical(1)</code>] 
Should a data.frame be returned?
Default is <code>FALSE</code>. In this case a named list is returned.</dd></dl>

Arguments

Helper function to estimate reference set(s). — approximateRefSets

<dl>

<dt>df</dt>
<dd>[<code>data.frame</code>] 
Data frame with the required structure.</dd>


<dt>obj.cols</dt>
<dd>[<code>character(&gt;= 2)</code>] 
Column names of the objective functions.</dd>


<dt>as.df</dt>
<dd>[<code>logical(1)</code>] 
Should a data.frame be returned?
Default is <code>FALSE</code>. In this case a named list is returned.</dd>

</dl>

approximateRefSets: Helper function to estimate reference set(s).

Description

Usage

Value

Arguments

See Also