ez_moga.pl - Easy implementation of a very primitive multiobjective optimization algorithm
prompt% ./ez_moga.pl <population> <number of generations>
prompt% perl p_peaks.pl <bits> <peaks> <population> <number of generations> Shows the values of the two floating-point components of the chromosome and finally the best value and fitness reached, which should be as close to 1 as possible.
A simple example of how to run an Evolutionary algorithm based on Algorithm::Evolutionary. Tries to find the max of the bidimensional Tide , and outputs the x and y coordinates, along with fitness. Best fitness is close to 1. Around 50 generations should be enough, but default is population and number of generations equal to 100.
Contributed by Pedro Castillo Valdivieso, modified by J. J. Merelo
This file is released under the GPL. See the LICENSE file included in this distribution, or go to http://www.fsf.org/licenses/gpl.txt CVS Info: $Date: 2009/11/17 19:19:41 $ $Header: /media/Backup/Repos/opeal/opeal/Algorithm-Evolutionary/examples/ez_moga.pl,v 3.1 2009/11/17 19:19:41 jmerelo Exp $ $Author: jmerelo $ $Revision: 3.1 $ $Name $