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Manual Reference Pages  -  ALGORITHM::EVOLUTIONARY::FITNESS::P_PEAKS (3)

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NAME

Algorithm::Evolutionary::Fitness::P_Peaks - P Peaks problem generator

CONTENTS

SYNOPSIS



    my $number_of_peaks = 100;
    my $number_of_bits = 32;
    my $p_peaks = Algorithm::Evolutionary::Fitness::P_Peaks->new( $number_of_peaks, $number_of_bits );



DESCRIPTION

P_Peaks fitness function; optimizes the distance to the closest in a series of peaks. The P-Peaks problem was proposed by Kennedy and Spears in



  @conference{kennedy1998matching,
  title={{Matching algorithms to problems: an experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator}},
  author={Kennedy, J. and Spears, W.M.},
  booktitle={Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on},
  pages={78--83},
  isbn={0780348699},
  year={1998},
  organization={IEEE}
 }



And the optimum is 1.0. By default, result is cached, so be careful when working with long strings and/or big populations

METHODS

new( CW$peaks, CW$bits )

Creates a new instance of the problem, with the said number of bits and peaks.

random_string()

Returns random string in the same style than the peaks. Useful for testing.

_really_apply( CW$string )

Applies the instantiated problem to a chromosome. Intended for internal use.

p_peaks( CW$string )

Returns the distance to the closest bitstring

Copyright



  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



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perl v5.20.3 ALGORITHM::EVOLUTIONARY::FITNESS::P_PEAKS (3) 2014-10-25

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