Package: moocore 0.1.2.9000

Manuel López-Ibáñez

moocore: Core Mathematical Functions for Multi-Objective Optimization

Fast implementation of mathematical operations and performance metrics for multi-objective optimization, including filtering and ranking of dominated vectors according to Pareto optimality, computation of the empirical attainment function, V.G. da Fonseca, C.M. Fonseca, A.O. Hall (2001) <doi:10.1007/3-540-44719-9_15>, hypervolume metric, C.M. Fonseca, L. Paquete, M. López-Ibáñez (2006) <doi:10.1109/CEC.2006.1688440>, epsilon indicator, inverted generational distance, and Vorob'ev threshold, expectation and deviation, M. Binois, D. Ginsbourger, O. Roustant (2015) <doi:10.1016/j.ejor.2014.07.032>, among others.

Authors:Manuel López-Ibáñez [aut, cre], Carlos Fonseca [ctb], Luís Paquete [ctb], Andreia P. Guerreiro [ctb], Mickaël Binois [ctb], Michael H. Buselli [cph], Wessel Dankers [cph], NumPy Developers [cph], Jean-Sebastien Roy [cph], Makoto Matsumoto [cph], Takuji Nishimura [cph]

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NEWS

# Install 'moocore' in R:
install.packages('moocore', repos = c('https://multi-objective.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/multi-objective/moocore/issues

Datasets:
  • CPFs - Conditional Pareto fronts obtained from Gaussian processes simulations.
  • HybridGA - Results of Hybrid GA on Vanzyl and Richmond water networks
  • SPEA2minstoptimeRichmond - Results of SPEA2 when minimising electrical cost and maximising the minimum idle time of pumps on Richmond water network.
  • SPEA2relativeRichmond - Results of SPEA2 with relative time-controlled triggers on Richmond water network.
  • SPEA2relativeVanzyl - Results of SPEA2 with relative time-controlled triggers on Vanzyl's water network.
  • tpls50x20_1_MWT - Various strategies of Two-Phase Local Search applied to the Permutation Flowshop Problem with Makespan and Weighted Tardiness objectives.

On CRAN:

5.28 score 7 stars 1 packages 7 scripts 469 downloads 29 exports 3 dependencies

Last updated 6 days agofrom:73506c0374. Checks:OK: 3 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64OKOct 31 2024
R-4.5-linux-x86_64OKOct 31 2024
R-4.4-win-x86_64NOTEOct 31 2024
R-4.4-mac-x86_64NOTEOct 31 2024
R-4.4-mac-aarch64NOTEOct 31 2024
R-4.3-win-x86_64NOTEOct 31 2024
R-4.3-mac-x86_64NOTEOct 31 2024
R-4.3-mac-aarch64NOTEOct 31 2024

Exports:as_double_matrixattsurf2dfavg_hausdorff_distchoose_eafdiffcompute_eaf_callcompute_eafdiff_calleafeaf_as_listeafdiffepsilon_additiveepsilon_multfilter_dominatedhv_contributionshypervolumeigdigd_plusis_nondominatedlargest_eafdiffnormalisepareto_rankrbind_datasetsread_datasetstotal_whv_recttransform_maximisevorobDevvorobTwhv_hypewhv_rectwrite_datasets

Dependencies:matrixStatsrbibutilsRdpack

Readme and manuals

Help Manual

Help pageTopics
Convert input to a matrix with '"double"' storage mode ('base::storage.mode()').as_double_matrix
Convert a list of attainment surfaces to a single EAF 'data.frame'.attsurf2df
Interactively choose according to empirical attainment function differenceschoose_eafdiff
Same as 'eaf()' but performs no checks and does not transform the input or the output. This function should be used by other packages that want to avoid redundant checks and transformations.compute_eaf_call
Same as 'eafdiff()' but performs no checks and does not transform the input or the output. This function should be used by other packages that want to avoid redundant checks and transformations.compute_eafdiff_call
Conditional Pareto fronts obtained from Gaussian processes simulations.CPFs
Exact computation of the EAF in 2D or 3Deaf
Convert an EAF data frame to a list of data frames, where each element of the list is one attainment surface. The function 'attsurf2df()' can be used to convert the list into a single data frame.eaf_as_list
Compute empirical attainment function differenceseafdiff
Epsilon metricepsilon epsilon_additive epsilon_mult
Hypervolume contribution of a set of pointshv_contributions
Results of Hybrid GA on Vanzyl and Richmond water networksHybridGA
Hypervolume metrichypervolume
Inverted Generational Distance (IGD and IGD+) and Averaged Hausdorff Distanceavg_hausdorff_dist igd IGDX igd_plus
Identify, remove and rank dominated points according to Pareto optimalityfilter_dominated is_nondominated pareto_rank
Identify largest EAF differenceslargest_eafdiff
Normalise pointsnormalise
Combine datasets 'x' and 'y' by row taking care of making all sets unique.rbind_datasets
Read several data setsread_datasets
Results of SPEA2 when minimising electrical cost and maximising the minimum idle time of pumps on Richmond water network.SPEA2minstoptimeRichmond
Results of SPEA2 with relative time-controlled triggers on Richmond water network.SPEA2relativeRichmond
Results of SPEA2 with relative time-controlled triggers on Vanzyl's water network.SPEA2relativeVanzyl
Various strategies of Two-Phase Local Search applied to the Permutation Flowshop Problem with Makespan and Weighted Tardiness objectives.tpls50x20_1_MWT
Transform matrix according to maximise parametertransform_maximise
Vorob'ev computationsvorobDev vorobT
Approximation of the (weighted) hypervolume by Monte-Carlo sampling (2D only)whv_hype
Compute (total) weighted hypervolume given a set of rectanglestotal_whv_rect whv_rect
Write data setswrite_datasets