simple_ga/simple_ga.html

<html>

  <head>
    <title>
      SIMPLE_GA - A Simple Genetic Algorithm
    </title>
  </head>

  <body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">

    <h1 align = "center">
      SIMPLE_GA <br> A Simple Genetic Algorithm
    </h1>

    <hr>

    <p>
      <b>SIMPLE_GA</b>
      is a C++ program which
      implements a simple genetic algorithm,
      by Dennis Cormier and Sita Raghavan.
    </p>

    <p>
      Here, we consider the task of constrained optimization of a scalar function.
      That is, we have a function F(X), where X is an M-vector satisfying simple
      constraints for each component I:
      <pre>
        X_MIN[I] <= X[I] <= X_MAX[I]
      </pre>
      and, subject to those constraints, we seek a vector X which maximizes
      the value F(X).
    </p>

    <p>
      In the example given here, the spatial dimension M is 3, the function
      F(X) is X[1]^2 - X[1]*X[2] + X[3], and the constraints are
      <pre>
        0 <= X[1] <= 5
        0 <= X[2] <= 5
       -2 <= X[3] <= 2
      </pre>
      The correct solution is [5,0,2].
    </p>

    <h3 align = "center">
      Licensing:
    </h3>

    <p>
      The computer code and data files made available on this web page 
      are distributed under
      <a href = "../../txt/gnu_lgpl.txt">the GNU LGPL license.</a>
    </p>

    <h3 align = "center">
      Languages:
    </h3>

    <p>
      <b>SIMPLE_GA</b> is available in
      <a href = "../../cpp_src/simple_ga/simple_ga.html">a C++ version</a>.
    </p>

    <h3 align = "center">
      Related Programs and Data:
    </h3>

    <p>
      <a href = "../../m_src/image_match_genetic/image_match_genetic.html">
      IMAGE_MATCH_GENETIC</a>,
      a MATLAB program which
      tries to match a 256x256 JPEG image by blending 32 colored rectangles,
      using ideas from genetic algorithms,
      based on an example by Nick Berry.
    </p>

    <h3 align = "center">
      Author:
    </h3>

    <p>
      Original version by Dennis Cormier, Sita Raghavan.
      This C++ version by John Burkardt.
    </p>

    <h3 align = "center">
      Reference:
    </h3>

    <p>
      <ol>
        <li>
          Zbigniew Michalewicz,<br>
          Genetic Algorithms + Data Structures = Evolution Programs,<br>
          Third Edition,<br>
          Springer, 1996,<br>
          ISBN: 3-540-60676-9,<br>
          LC: QA76.618.M53.
        </li>
      </ol>
    </p>

    <h3 align = "center">
      Source Code:
    </h3>

    <p>
      <ul>
        <li>
          <a href = "simple_ga.cpp">simple_ga.cpp</a>, the source code.
        </li>
        <li>
          <a href = "simple_ga.sh">simple_ga.sh</a>,
          commands to compile and load the source code.
        </li>
      </ul>
    </p>

    <h3 align = "center">
      Examples and Tests:
    </h3>

    <p>
      <ul>
        <li>
          <a href = "simple_ga_input.txt">simple_ga_input.txt</a>, an input file.
        </li>
        <li>
          <a href = "simple_ga_output.txt">simple_ga_output.txt</a>, the output file.
        </li>
      </ul>
    </p>

    <h3 align = "center">
      List of Routines:
    </h3>

    <p>
      <ul>
        <li>
          <b>MAIN</b> supervises the genetic algorithm.
        </li>
        <li>
          <b>CROSSOVER</b> selects two parents for the single point crossover.
        </li>
        <li>
          <b>ELITIST</b> stores the best member of the previous generation.
        </li>
        <li>
          <b>EVALUATE</b> implements the user-defined valuation function
        </li>
        <li>
          <b>I4_UNIFORM_AB</b> returns a scaled pseudorandom I4 between A and B.
        </li>
        <li>
          <b>INITIALIZE</b> initializes the genes within the variables bounds. 
        </li>
        <li>
          <b>KEEP_THE_BEST</b> keeps track of the best member of the population. 
        </li>
        <li>
          <b>MUTATE</b> performs a random uniform mutation. 
        </li>
        <li>
          <b>R8_UNIFORM_AB</b> returns a scaled pseudorandom R8.
        </li>
        <li>
          <b>REPORT</b> reports progress of the simulation. 
        </li>
        <li>
          <b>SELECTOR</b> is the selection function.
        </li>
        <li>
          <b>TIMESTAMP</b> prints the current YMDHMS date as a time stamp.
        </li>
        <li>
          <b>XOVER</b> performs crossover of the two selected parents. 
        </li>
      </ul>
    </p>

    <p>
      You can go up one level to <a href = "../cpp_src.html">
      the C++ source codes</a>.
    </p>

    <hr>

    <i>
      Last revised on 28 April 2014.
    </i>

    <!-- John Burkardt -->

  </body>

</html>