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# ParadisEO-MOEO Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

eoAdditiveBinaryEpsilonIndicator< EOFitness > | Functor Additive binary epsilon indicator for eoParetoFitness
eoBinaryHypervolumeIndicator< EOFitness > | Functor Binary hypervolume indicator for eoParetoFitness
eoBinaryQualityIndicator< EOFitness > | Functor Binary quality indicator Binary performance measure to use in the replacement selection process of IBEA (Indicator-Based Evolutionary Algorithm) Of course, EOFitness needs to be an eoParetoFitness object
eoBinaryQualityIndicator< EOFitness >::Range | Private class to represent the bounds
eoIBEA< EOT, Fitness > | Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm)
eoIBEAAvgSorting< EOT, FitnessEval > | Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm) under uncertainty using averaged values for each objective Follow the idea presented in the Deb & Gupta paper "Searching for Robust Pareto-Optimal Solutions in Multi-Objective Optimization", 2005 Of course, the fitness of an individual needs to be an eoStochasticParetoFitness object
eoIBEASorting< EOT, Fitness > | Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm) without uncertainty Adapted from the Zitzler and Künzli paper "Indicator-Based Selection in Multiobjective Search" (2004) Of course, Fitness needs to be an eoParetoFitness object
eoIBEAStochSorting< EOT, FitnessEval > | Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm) under uncertainty Adapted from the Basseur and Zitzler paper "Handling Uncertainty in Indicator-Based Multiobjective Optimization" (2006) Of course, the fitness of an individual needs to be an eoStochasticParetoFitness object
eoParetoEuclidDist< EOT, DistType > |
eoParetoPhenDist< EOT, DistType > |
eoParetoSharing< EOT, worthT > |
eoParetoSharing< EOT, worthT >::dMatrix |
moeoArchive< EOT > | An archive is a secondary population that stores non-dominated solutions
moeoArchiveFitnessSavingUpdater< EOT > | This class allows to save the fitnesses of solutions contained in an archive into a file at each generation
moeoArchiveUpdater< EOT > | This class allows to update the archive at each generation with newly found non-dominated solutions
moeoBinaryMetricSavingUpdater< EOT > | 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
moeoBM< A1, A2, R > | Base class for binary metrics
moeoCombinedMOLS< EOT > | 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
moeoContributionMetric< EOT > | The contribution metric evaluates the proportion of non-dominated solutions given by a Pareto set relatively to another Pareto set
moeoDisctinctElitistReplacement< EOT, WorthT > | Same than moeoElitistReplacement except that distinct individuals are privilegied
moeoElitistReplacement< EOT, WorthT > | Keep all the best individuals (almost cut-and-pasted from eoNDPlusReplacement, (c) Maarten Keijzer, Marc Schoenauer and GeNeura Team, 2002)
moeoEntropyMetric< EOT > | The entropy gives an idea of the diversity of a Pareto set relatively to another Pareto set
moeoHybridMOLS< EOT > | 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
moeoMetric | Base class for performance metrics (also called quality indicators)
moeoMOLS< EOT > | Abstract class for local searches applied to multi-objective optimization
moeoNDSorting_II< EOT > | Fast Elitist Non-Dominant Sorting Genetic Algorithm
moeoNDSorting_II< EOT >::compare_nodes |
moeoNSGA_II< EOT > |
moeoReplacement< EOT, WorthT > | Replacement strategy for multi-objective optimization
moeoSelectOneFromPopAndArch< EOT > | Elitist selection process that consists in choosing individuals in the archive as well as in the current population
moeoSolutionUM< EOT, R, EOFitness > | Base class for unary metrics dedicated to the performance evaluation of a single solution's Pareto fitness
moeoSolutionVsSolutionBM< EOT, R, EOFitness > | Base class for binary metrics dedicated to the performance comparison between two solutions's Pareto fitnesses
moeoUM< A, R > | Base class for unary metrics
moeoVectorUM< EOT, R, EOFitness > | Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of Pareto fitnesses)
moeoVectorVsSolutionBM< EOT, R, EOFitness > | 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
moeoVectorVsVectorBM< EOT, R, EOFitness > | Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of Pareto fitnesses)