Fast non-dominated sorting algorithm.
Interface to ecr similar to the optim function.
Result object.
Parallelization in ecr
EMOA performance indicators
Computation of EMOA performance indicators.
computeInvertedGenerationalDistance
Computes Inverted Generational Distance.
Check for pareto dominance.
Functions for the calculation of the dominated hypervolume (contribution).
Dominance relation check.
Filter approximation sets by duplicate objective vectors.
generatesMultipleChildren
Does the recombinator generate multiple children?
Extract fitness values from Pareto archive.
Computes the fitness value(s) for each individual of a given set.
Extract individuals from Pareto archive.
Helper function to build initial population.
Number of children
Helper functions for offspring generation
getNumberOfParentsNeededForMating
Number of parents needed for mating
Check if ecr operator supports given representation.
Access the logged statistics.
getSupportedRepresentations
Get supported representations.
Construct evolutionary operator.
Generate stopping condition.
Explode/implode data frame column(s).
Control object generator.
mcMST
Initialize a log object.
Get size of Pareto-archive.
Insertion mutator.
Inversion mutator.
Check if given function is an ecr operator.
Initialize Pareto Archive.
Access to logged population fitness.
Gaussian mutator.
Bitplip mutator.
Factory method for monitor objects.
Access to logged populations.
Scramble mutator.
Swap mutator.
Plot heatmap.
Construct a recombination operator.
Construct a selection operator.
Formatter for table cells of LaTeX tables.
Uniform mutator.
Creates an optimization task.
Visualize three-objective Pareto-front approximations.
Generate line plot of logged statistics.
Draw scatterplot of Pareto-front approximation
Plot distribution of EMOA indicators.
Constructor for EMOA indicators.
Population generators
Construct a mutation operator.
Jump mutator.
Uniform crossover recombinator.
(mu + lambda) selection
Simulated Binary Crossover (SBX) recombinator.
Register operators to control object.
Visualize bi-objective Pareto-front approximations.
Roulette-wheel / fitness-proportional selector.
Simple (naive) selector.
One-point crossover recombinator.
Polynomial mutation.
Ordered-Crossover (OX) recombinator.
Partially-Mapped-Crossover (PMX) recombinator.
Implementation of the NSGA-II EMOA algorithm by Deb.
Normalize approximations set(s).
Default monitor.
Convert matrix to Pareto front data frame.
Sort Pareto-front approximation by objective.
Stopping conditions
Implementation of the SMS-EMOA by Emmerich et al.
Dominated Hypervolume selector.
Simple selector.
Indermediate recombinator.
Check if one set is better than another.
Fitness transformation / scaling.
Combine multiple data frames into a single data.frame.
Update Pareto Archive.
Update the log.
Set up parameters for evolutionary operator.
k-Tournament selector.
Reference point approximations.
Wrap the individuals constructed by a recombination operator.
Transform to long format.
Rank Selection Operator
Export results of statistical tests to LaTeX table(s).
Non-dominated sorting selector.
Select individuals.
Determine which points of a set are (non)dominated.
Grouping helpers
Helper function to estimate reference points.
Assign group membership based on another group membership.
Compute the crowding distance of a set of points.
Helper function to estimate reference set(s).
computeGenerationalDistance
Computes Generational Distance.
Ranking of approximation sets.
Implementation of the NSGA-II EMOA algorithm by Deb.
computeAverageHausdorffDistance
Average Hausdorff Distance computation.
computeDistanceFromPointToSetOfPoints
Computes distance between a single point and set of points.