computeCrowdingDistance

The crowding distance is a measure of spread of solutions in the
approximation of the Pareto front. It is used, e.g., in the NSGA-II algorithm
as a second selection criterion.

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

computeCrowdingDistance function

<dl><dt>x</dt>
<dd>[<code>matrix</code>] 
Numeric matrix with each column representing a point.</dd></dl>

Arguments

Compute the crowding distance of a set of points. — computeCrowdingDistance

<dl>

<dt>x</dt>
<dd>[<code>matrix</code>] 
Numeric matrix with each column representing a point.</dd>

</dl>

computeCrowdingDistance: Compute the crowding distance of a set of points.

Description

Usage

Value

Arguments

References