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ecr (version 2.1.1)

Evolutionary Computation in R

Description

Framework for building evolutionary algorithms for both single- and multi-objective continuous or discrete optimization problems. A set of predefined evolutionary building blocks and operators is included. Moreover, the user can easily set up custom objective functions, operators, building blocks and representations sticking to few conventions. The package allows both a black-box approach for standard tasks (plug-and-play style) and a much more flexible white-box approach where the evolutionary cycle is written by hand.

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Install

install.packages('ecr')

Monthly Downloads

320

Version

2.1.1

License

GPL-3

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Maintainer

Last Published

March 8th, 2023

Functions in ecr (2.1.1)

doNondominatedSorting

Fast non-dominated sorting algorithm.
ecr

Interface to ecr similar to the optim function.
ecr_result

Result object.
ecr_parallelization

Parallelization in ecr
emoaIndEps

EMOA performance indicators
computeIndicators

Computation of EMOA performance indicators.
computeInvertedGenerationalDistance

Computes Inverted Generational Distance.
dominated

Check for pareto dominance.
computeHV

Functions for the calculation of the dominated hypervolume (contribution).
dominates

Dominance relation check.
filterDuplicated

Filter approximation sets by duplicate objective vectors.
generatesMultipleChildren

Does the recombinator generate multiple children?
getFront

Extract fitness values from Pareto archive.
evaluateFitness

Computes the fitness value(s) for each individual of a given set.
getIndividuals

Extract individuals from Pareto archive.
initPopulation

Helper function to build initial population.
getNumberOfChildren

Number of children
generateOffspring

Helper functions for offspring generation
getNumberOfParentsNeededForMating

Number of parents needed for mating
is.supported

Check if ecr operator supports given representation.
getStatistics

Access the logged statistics.
getSupportedRepresentations

Get supported representations.
makeOperator

Construct evolutionary operator.
makeTerminator

Generate stopping condition.
explode

Explode/implode data frame column(s).
initECRControl

Control object generator.
mcMST

mcMST
initLogger

Initialize a log object.
getSize

Get size of Pareto-archive.
mutInsertion

Insertion mutator.
mutInversion

Inversion mutator.
isEcrOperator

Check if given function is an ecr operator.
initParetoArchive

Initialize Pareto Archive.
getPopulationFitness

Access to logged population fitness.
mutGauss

Gaussian mutator.
mutBitflip

Bitplip mutator.
makeECRMonitor

Factory method for monitor objects.
getPopulations

Access to logged populations.
mutScramble

Scramble mutator.
mutSwap

Swap mutator.
plotHeatmap

Plot heatmap.
makeRecombinator

Construct a recombination operator.
makeSelector

Construct a selection operator.
niceCellFormater

Formatter for table cells of LaTeX tables.
mutUniform

Uniform mutator.
makeOptimizationTask

Creates an optimization task.
plotScatter3d

Visualize three-objective Pareto-front approximations.
plotStatistics

Generate line plot of logged statistics.
plotFront

Draw scatterplot of Pareto-front approximation
plotDistribution

Plot distribution of EMOA indicators.
makeEMOAIndicator

Constructor for EMOA indicators.
generators

Population generators
makeMutator

Construct a mutation operator.
mutJump

Jump mutator.
recUnifCrossover

Uniform crossover recombinator.
replace

(mu + lambda) selection
recSBX

Simulated Binary Crossover (SBX) recombinator.
registerECROperator

Register operators to control object.
plotScatter2d

Visualize bi-objective Pareto-front approximations.
selRoulette

Roulette-wheel / fitness-proportional selector.
selSimple

Simple (naive) selector.
recCrossover

One-point crossover recombinator.
mutPolynomial

Polynomial mutation.
recOX

Ordered-Crossover (OX) recombinator.
recPMX

Partially-Mapped-Crossover (PMX) recombinator.
nsga2

Implementation of the NSGA-II EMOA algorithm by Deb.
normalize

Normalize approximations set(s).
setupECRDefaultMonitor

Default monitor.
toParetoDf

Convert matrix to Pareto front data frame.
sortByObjective

Sort Pareto-front approximation by objective.
stoppingConditions

Stopping conditions
smsemoa

Implementation of the SMS-EMOA by Emmerich et al.
selDomHV

Dominated Hypervolume selector.
selGreedy

Simple selector.
recIntermediate

Indermediate recombinator.
setDominates

Check if one set is better than another.
transformFitness

Fitness transformation / scaling.
reduceToSingleDataFrame

Combine multiple data frames into a single data.frame.
updateParetoArchive

Update Pareto Archive.
updateLogger

Update the log.
setup

Set up parameters for evolutionary operator.
selTournament

k-Tournament selector.
approximateNadirPoint

Reference point approximations.
wrapChildren

Wrap the individuals constructed by a recombination operator.
toGG

Transform to long format.
selRanking

Rank Selection Operator
toLatex

Export results of statistical tests to LaTeX table(s).
selNondom

Non-dominated sorting selector.
select

Select individuals.
which.dominated

Determine which points of a set are (non)dominated.
addUnionGroup

Grouping helpers
approximateRefPoints

Helper function to estimate reference points.
categorize

Assign group membership based on another group membership.
computeCrowdingDistance

Compute the crowding distance of a set of points.
approximateRefSets

Helper function to estimate reference set(s).
computeGenerationalDistance

Computes Generational Distance.
computeDominanceRanking

Ranking of approximation sets.
asemoa

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.