toParetoDf

Inside ecr EMOA algorithms the fitness is maintained in an \((o, n)\) matrix
where \(o\) is the number of objectives and \(n\) is the number of individuals.
This function basically transposes such a matrix and converts it into a data frame.

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

toParetoDf function

<dl><dt>x</dt>
<dd>[<code>matrix</code>] 
Matrix.</dd>
<dt>filter.dups</dt>
<dd>[<code>logical(1)</code>] 
Shall duplicates be removed?
Default is <code>FALSE</code>.</dd></dl>

Arguments

Convert matrix to Pareto front data frame. — toParetoDf

<dl>

<dt>x</dt>
<dd>[<code>matrix</code>] 
Matrix.</dd>


<dt>filter.dups</dt>
<dd>[<code>logical(1)</code>] 
Shall duplicates be removed?
Default is <code>FALSE</code>.</dd>

</dl>

toParetoDf: Convert matrix to Pareto front data frame.

Description

Usage

Value

Arguments