computeInvertedGenerationalDistance

Helper to compute the Inverted Generational Distance (IGD) between two sets
of points.

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

computeInvertedGenerationalDistance function

<dl><dt>A</dt>
<dd>[<code>matrix</code>] 
First point set (each column corresponds to a point).</dd>
<dt>B</dt>
<dd>[<code>matrix</code>] 
Second point set (each column corresponds to a point).</dd>
<dt>p</dt>
<dd>[<code>numeric(1)</code>] 
Parameter p of the average Hausdoff metric.
Default is 1.</dd>
<dt>normalize</dt>
<dd>[<code>logical(1)</code>] 
Should the front be normalized on basis of <code>B</code>?
Default is <code>FALSE</code>.</dd>
<dt>dist.fun</dt>
<dd>[<code>matrix</code>] 
Distance function to compute distance between points x and y. Expects a single
numeric vector d with the coordinate-wise differences di = (xi - yi).
Default is <code>computeEuclideanDist</code>.</dd></dl>

Arguments

Computes Inverted Generational Distance. — computeInvertedGenerationalDistance

<dl>

<dt>A</dt>
<dd>[<code>matrix</code>] 
First point set (each column corresponds to a point).</dd>


<dt>B</dt>
<dd>[<code>matrix</code>] 
Second point set (each column corresponds to a point).</dd>


<dt>p</dt>
<dd>[<code>numeric(1)</code>] 
Parameter p of the average Hausdoff metric.
Default is 1.</dd>


<dt>normalize</dt>
<dd>[<code>logical(1)</code>] 
Should the front be normalized on basis of <code>B</code>?
Default is <code>FALSE</code>.</dd>


<dt>dist.fun</dt>
<dd>[<code>matrix</code>] 
Distance function to compute distance between points x and y. Expects a single
numeric vector d with the coordinate-wise differences di = (xi - yi).
Default is <code>computeEuclideanDist</code>.</dd>

</dl>

computeInvertedGenerationalDistance: Computes Inverted Generational Distance.

Description

Usage

Value

Arguments