performance_metrics

generational_distance

Functions to evaluate the quality of the results obtained by the algorithms, evaluating their diversity and convergence, providing or not some parameters to compare.

The 'rmoo' package is a framework for multi- and many-objective
optimization, which allows researchers and users versatility
in parameter configuration, as well as tools for analysis, replication
and visualization of results. The 'rmoo' package was built as a fork of
the 'GA' package by Luca Scrucca(2017) <DOI:10.32614/RJ-2017-008> and
implementing the Non-Dominated Sorting Genetic Algorithms proposed
by K. Deb's.

Francisco Benitez

rmoo

Multi-Objective Optimization in R

Diego P. Pinto-Roa

performance_metrics function

<dl> <dt>front</dt>
<dd>a N×M matrix where N is the number of points and M is the number of objectives.</dd>
 <dt>true_pareto_front</dt>
<dd>a N×M matrix where N is the number of points and M is the number of objectives.</dd>
 <dt>p</dt>
<dd>is the power in which the normalized distance is calculated.</dd>
 <dt>inverted</dt>
<dd>if TRUE then computes IGD.</dd>
 <dt>plus</dt>
<dd>if TRUE then computes the GD+.</dd></dl>

Arguments

Author

Objective Values performance metrics — performance_metrics

<dl>

 <dt>front</dt>
<dd>a N×M matrix where N is the number of points and M is the number of objectives.</dd>


 <dt>true_pareto_front</dt>
<dd>a N×M matrix where N is the number of points and M is the number of objectives.</dd>


 <dt>p</dt>
<dd>is the power in which the normalized distance is calculated.</dd>


 <dt>inverted</dt>
<dd>if TRUE then computes IGD.</dd>


 <dt>plus</dt>
<dd>if TRUE then computes the GD+.</dd>

</dl>

performance_metrics: Objective Values performance metrics

Description

Usage

Value

Arguments

Author

References