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Replace genetic algorithm ASCII-art with a real figure
Author: Jürgen Purtz Discussion: https://postgr.es/m/c6027f7a-78ea-8453-0837-09903ba5fd9b@purtz.de
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‎doc/src/sgml/geqo.sgml

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Through simulation of the evolutionary operations <firstterm>recombination</firstterm>,
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<firstterm>mutation</firstterm>, and
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<firstterm>selection</firstterm> new generations of search points are found
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that show a higher average fitness than their ancestors.
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that show a higher average fitness than their ancestors. <xref linkend="geqo-figure"/>
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illustrates these steps.
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</para>
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<figure id="geqo-figure">
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<title>Structure of a Genetic Algorithm</title>
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<mediaobject>
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<imageobject>
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<imagedata fileref="images/genetic-algorithm.svg" format="SVG" width="100%"/>
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</imageobject>
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</mediaobject>
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</figure>
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<para>
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According to the <systemitem class="resource">comp.ai.genetic</systemitem> <acronym>FAQ</acronym> it cannot be stressed too
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strongly that a <acronym>GA</acronym> is not a pure random search for a solution to a
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problem. A <acronym>GA</acronym> uses stochastic processes, but the result is distinctly
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non-random (better than random).
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</para>
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<figure id="geqo-diagram">
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<title>Structured Diagram of a Genetic Algorithm</title>
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<informaltable frame="none">
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<tgroup cols="2">
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<tbody>
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<row>
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<entry>P(t)</entry>
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<entry>generation of ancestors at a time t</entry>
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</row>
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<row>
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<entry>P''(t)</entry>
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<entry>generation of descendants at a time t</entry>
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</row>
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</tbody>
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</tgroup>
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</informaltable>
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<literallayout class="monospaced">
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+=========================================+
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|&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt; Algorithm GA &lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;&lt;|
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+=========================================+
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| INITIALIZE t := 0 |
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+=========================================+
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| INITIALIZE P(t) |
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+=========================================+
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| evaluate FITNESS of P(t) |
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+=========================================+
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| while not STOPPING CRITERION do |
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| +-------------------------------------+
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| | P'(t) := RECOMBINATION{P(t)} |
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| +-------------------------------------+
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| | P''(t) := MUTATION{P'(t)} |
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| +-------------------------------------+
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| | P(t+1) := SELECTION{P''(t) + P(t)} |
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| +-------------------------------------+
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| | evaluate FITNESS of P''(t) |
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| +-------------------------------------+
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| | t := t + 1 |
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+===+=====================================+
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</literallayout>
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</figure>
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</sect1>
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<sect1 id="geqo-pg-intro">

‎doc/src/sgml/images/Makefile

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# see README in this directory about image handling
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ALL_IMAGES = \
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genetic-algorithm.svg \
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gin.svg \
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pagelayout.svg
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‎doc/src/sgml/images/genetic-algorithm.gv

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digraph {
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layout=dot;
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// default values
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node [shape=box, label="", fontname="sans-serif", style=filled, fillcolor=white, fontsize=8];
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graph [fontname="sans-serif"]; // must be specified separately
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edge [fontname="sans-serif"]; // must be specified separately
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// an unobtrusive background color
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pad="1.0, 0.5";
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bgcolor=whitesmoke;
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// layout of edges and nodes
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splines=ortho;
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nodesep=0.3;
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ranksep=0.3;
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// nodes
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a1[label="INITIALIZE t := 0"];
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a2[label="INITIALIZE P(t)"];
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a3[label="evaluate FITNESS of P(t)"];
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a4[shape="diamond", label="STOPPING CRITERION"; width=4];
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// connect 'end' node with 'a9' node (bottom of figure)
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{
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rank=same;
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a9[label="t := t + 1"];
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// end-symbol similar to UML notation
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end[shape=doublecircle, label="end", width=0.5];
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}
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a5[label="P'(t) := RECOMBINATION{P(t)}"];
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a6[label="P''(t) := MUTATION{P'(t)}"];
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a7[label="P(t+1) := SELECTION{P''(t) + P(t)}"];
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a8[label="evaluate FITNESS of P''(t)"];
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// edges
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a1 -> a2 -> a3 -> a4;
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a4 -> a5[xlabel="false ", fontsize=10];
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a4 -> end[xlabel="true ", fontsize=10];
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a5 -> a6 -> a7 -> a8 -> a9;
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a4 -> a9 [dir=back];
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// explain the notation
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expl [shape=plaintext, fontsize=10, width=3.2, fillcolor=whitesmoke,
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label="P(t): generation of ancestors at a time t\lP''(t): generation of descendants at a time t\l"];
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}

‎doc/src/sgml/images/genetic-algorithm.svg

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