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<title>Genetic Algorithm Library: source/CouplingOperations.h File Reference</title>
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<h1>source/CouplingOperations.h File Reference</h1>This file contains declaration of classes that implement coupling operations. <a href="#_details">More...</a>
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<code>#include "<a class="el" href="_population_operations_8h.html">PopulationOperations.h</a>"</code><br>
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<tr><td colspan="2"><br><h2>Namespaces</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">namespace </td><td class="memItemRight" valign="bottom"><a class="el" href="namespace_population.html">Population</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">namespace </td><td class="memItemRight" valign="bottom"><a class="el" href="namespace_population_1_1_coupling_operations.html">Population::CouplingOperations</a></td></tr>
<tr><td colspan="2"><br><h2>Classes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_simple_coupling.html">Population::CouplingOperations::GaSimpleCoupling</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight"><code><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_simple_coupling.html" title="GaSimpleCoupling coupling takes first two parents and it produces two child using...">GaSimpleCoupling</a></code> coupling takes first two parents and it produces two child using crossover operations, and each parent is bound to one child, then it takes next two parents, and so on... If all parents are used, but more children should be produced, this coupling operation wraps-around parent counter and starts from beginning until enough children is produced. This coupling use <a class="el" href="class_population_1_1_ga_coupling_params.html" title="This class is base for parameters of coupling operation.">GaCouplingParams</a> class for parameters. <a href="class_population_1_1_coupling_operations_1_1_ga_simple_coupling.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_mulitple_crossover_coupling_params.html">Population::CouplingOperations::GaMulitpleCrossoverCouplingParams</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">This class should be used (directly or by inheritance) by coupling operations which produce more then one child per parent pair before it chooses best child. <a href="class_population_1_1_coupling_operations_1_1_ga_mulitple_crossover_coupling_params.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_cross_coupling.html">Population::CouplingOperations::GaCrossCoupling</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight"><code><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_cross_coupling.html" title="GaCrossCoupling coupling takes first parents sequentially from selection result set...">GaCrossCoupling</a></code> coupling takes first parents sequentially from selection result set, and second parents are the ones who are right below the first. If all parents are used, but more children should be produced, this coupling operation wraps-around parent counter and starts from beginning until enough children is produced. When two parents are chosen this operation produces specified number of children using crossover operation and then it chooses child with best fitness value among produced children and first parent is bound to it. This coupling use GaMultipleCrossoverCouplingParams class for parameters. <a href="class_population_1_1_coupling_operations_1_1_ga_cross_coupling.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_inverse_coupling.html">Population::CouplingOperations::GaInverseCoupling</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight"><code><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_inverse_coupling.html" title="GaInverseCoupling coupling takes first parents sequentially from selection results...">GaInverseCoupling</a></code> coupling takes first parents sequentially from selection results, and second parents are the ones who are at the distance from the last chromosome in selection results which is equal to distance of first parent form first chromosome in result set. If all parents are used, but more children should be produced, this coupling operation wraps-around parent counter and starts from beginning until enough children is produced. When two parents are chosen this operation produces specified number of children using crossover operation and then it chooses child with best fitness value among produced children and first parent is bound to it. This coupling use GaMultipleCrossoverCouplingParams class for parameters. <a href="class_population_1_1_coupling_operations_1_1_ga_inverse_coupling.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_random_coupling.html">Population::CouplingOperations::GaRandomCoupling</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight"><code><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_random_coupling.html" title="GaRandomCoupling coupling takes first parents sequentially from selection result...">GaRandomCoupling</a></code> coupling takes first parents sequentially from selection result set, and second parents are chosen randomly. If all parents are used as firs parent, but more children should be produced, this coupling operation wraps-around parent counter for the first parent and starts from beginning until enough children is produced. When two parents are chosen this operation produces specified number of children using crossover operation and then it chooses child with best fitness value among produced children and first parent is bound to it. This coupling use GaMultipleCrossoverCouplingParams class for parameters. <a href="class_population_1_1_coupling_operations_1_1_ga_random_coupling.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_best_always_coupling.html">Population::CouplingOperations::GaBestAlwaysCoupling</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight"><code><a class="el" href="class_population_1_1_coupling_operations_1_1_ga_best_always_coupling.html" title="GaBestAlwaysCoupling coupling always takes chromosome with the best fitness value...">GaBestAlwaysCoupling</a></code> coupling always takes chromosome with the best fitness value from selection result set, and the second parents are sequentially taken from. If all parents are used, but more children should be produced, this coupling operation wraps-around parent counter for second the parents and starts from beginning until enough children is produced. When two parents are chosen this operation produces specified number of children using crossover operation and then it chooses child with best fitness value among produced children and the second parent is bound to it. This coupling use GaMultipleCrossoverCouplingParams class for parameters. <a href="class_population_1_1_coupling_operations_1_1_ga_best_always_coupling.html#_details">More...</a><br></td></tr>
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<hr><a name="_details"></a><h2>Detailed Description</h2>
This file contains declaration of classes that implement coupling operations.
<p>
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<br/><a href="http://www.coolsoft-sd.com/ProductVersion.aspx?vid=9">Genetic Algorithm Library</a><br/><a href="http://www.coolsoft-sd.com/">Coolsoft Software Development</a>
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