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legrand b08dfed4b1 MOEO full import
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<title>ParadisEO-MOEO: Class List</title>
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<h1>ParadisEO-MOEO Class List</h1>Here are the classes, structs, unions and interfaces with brief descriptions:<table>
<tr><td class="indexkey"><a class="el" href="classmoeoArchive.html">moeoArchive&lt; EOT &gt;</a></td><td class="indexvalue">An archive is a secondary population that stores non-dominated solutions </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoArchiveFitnessSavingUpdater.html">moeoArchiveFitnessSavingUpdater&lt; EOT &gt;</a></td><td class="indexvalue">This class allows to save the fitnesses of solutions contained in an archive into a file at each generation </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoArchiveUpdater.html">moeoArchiveUpdater&lt; EOT &gt;</a></td><td class="indexvalue">This class allows to update the archive at each generation with newly found non-dominated solutions </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoBinaryMetricSavingUpdater.html">moeoBinaryMetricSavingUpdater&lt; EOT &gt;</a></td><td class="indexvalue">This class allows to save the progression of a binary metric comparing the fitness values of the current population (or archive) with the fitness values of the population (or archive) of the generation (n-1) into a file </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoBM.html">moeoBM&lt; A1, A2, R &gt;</a></td><td class="indexvalue">Base class for binary metrics </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoCombinedMOLS.html">moeoCombinedMOLS&lt; EOT &gt;</a></td><td class="indexvalue">This class allows to embed a set of local searches that are sequentially applied, and so working and updating the same archive of non-dominated solutions </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoContributionMetric.html">moeoContributionMetric&lt; EOT &gt;</a></td><td class="indexvalue">The contribution metric evaluates the proportion of non-dominated solutions given by a Pareto set relatively to another Pareto set </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoDisctinctElitistReplacement.html">moeoDisctinctElitistReplacement&lt; EOT, WorthT &gt;</a></td><td class="indexvalue">Same than <a class="el" href="classmoeoElitistReplacement.html">moeoElitistReplacement</a> except that distinct individuals are privilegied </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoElitistReplacement.html">moeoElitistReplacement&lt; EOT, WorthT &gt;</a></td><td class="indexvalue">Keep all the best individuals (almost cut-and-pasted from eoNDPlusReplacement, (c) Maarten Keijzer, Marc Schoenauer and GeNeura Team, 2002) </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoEntropyMetric.html">moeoEntropyMetric&lt; EOT &gt;</a></td><td class="indexvalue">The entropy gives an idea of the diversity of a Pareto set relatively to another Pareto set </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoHybridMOLS.html">moeoHybridMOLS&lt; EOT &gt;</a></td><td class="indexvalue">This class allows to apply a multi-objective local search to a number of selected individuals contained in the archive at every generation until a stopping criteria is verified </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoMetric.html">moeoMetric</a></td><td class="indexvalue">Base class for performance metrics (also called quality indicators) </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoMOLS.html">moeoMOLS&lt; EOT &gt;</a></td><td class="indexvalue">Abstract class for local searches applied to multi-objective optimization </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoReplacement.html">moeoReplacement&lt; EOT, WorthT &gt;</a></td><td class="indexvalue">Replacement strategy for multi-objective optimization </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoSelectOneFromPopAndArch.html">moeoSelectOneFromPopAndArch&lt; EOT &gt;</a></td><td class="indexvalue">Elitist selection process that consists in choosing individuals in the archive as well as in the current population </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoSolutionUM.html">moeoSolutionUM&lt; EOT, R, EOFitness &gt;</a></td><td class="indexvalue">Base class for unary metrics dedicated to the performance evaluation of a single solution's Pareto fitness </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoSolutionVsSolutionBM.html">moeoSolutionVsSolutionBM&lt; EOT, R, EOFitness &gt;</a></td><td class="indexvalue">Base class for binary metrics dedicated to the performance comparison between two solutions's Pareto fitnesses </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoUM.html">moeoUM&lt; A, R &gt;</a></td><td class="indexvalue">Base class for unary metrics </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoVectorUM.html">moeoVectorUM&lt; EOT, R, EOFitness &gt;</a></td><td class="indexvalue">Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of Pareto fitnesses) </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoVectorVsSolutionBM.html">moeoVectorVsSolutionBM&lt; EOT, R, EOFitness &gt;</a></td><td class="indexvalue">Base class for binary metrics dedicated to the performance comparison between a Pareto set (a vector of Pareto fitnesses) and a single solution's Pareto fitness </td></tr>
<tr><td class="indexkey"><a class="el" href="classmoeoVectorVsVectorBM.html">moeoVectorVsVectorBM&lt; EOT, R, EOFitness &gt;</a></td><td class="indexvalue">Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of Pareto fitnesses) </td></tr>
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