Package: mco 1.17

mco: Multiple Criteria Optimization Algorithms and Related Functions

A collection of function to solve multiple criteria optimization problems using genetic algorithms (NSGA-II). Also included is a collection of test functions.

Authors:Olaf Mersmann [aut, cre], Heike Trautmann [ctb], Detlef Steuer [ctb], Bernd Bischl [ctb], Kalyanmoy Deb [cph]

mco_1.17.tar.gz
mco_1.17.zip(r-4.5)mco_1.17.zip(r-4.4)mco_1.17.zip(r-4.3)
mco_1.17.tgz(r-4.4-x86_64)mco_1.17.tgz(r-4.4-arm64)mco_1.17.tgz(r-4.3-x86_64)mco_1.17.tgz(r-4.3-arm64)
mco_1.17.tar.gz(r-4.5-noble)mco_1.17.tar.gz(r-4.4-noble)
mco_1.17.tgz(r-4.4-emscripten)mco_1.17.tgz(r-4.3-emscripten)
mco.pdf |mco.html
mco/json (API)

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

Peer review:

Bug tracker:https://github.com/olafmersmann/mco/issues

On CRAN:

35 exports 9 stars 3.69 score 0 dependencies 15 dependents 6 mentions 104 scripts 3.1k downloads

Last updated 29 days agofrom:2c4c9401fa. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 19 2024
R-4.5-win-x86_64OKAug 19 2024
R-4.5-linux-x86_64OKAug 19 2024
R-4.4-win-x86_64OKAug 19 2024
R-4.4-mac-x86_64OKAug 19 2024
R-4.4-mac-aarch64OKAug 19 2024
R-4.3-win-x86_64OKAug 19 2024
R-4.3-mac-x86_64OKAug 19 2024
R-4.3-mac-aarch64OKAug 19 2024

Exports:belegundubelegundu.constrbinh1binh2binh2.constrbinh3deb3dominatedHypervolumeepsilonIndicatorfonseca1fonseca2generalizedSpreadgenerationalDistancegiannahanne1hanne1.constrhanne2hanne2.constrhanne3hanne3.constrhanne4hanne4.constrhanne5hanne5.constrjimenezjimenez.constrnormalizeFrontnsga2paretoFilterparetoFrontparetoSetvntzdt1zdt2zdt3

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
MCO test problemsbelegundu belegundu.constr binh1 binh2 binh2.constr binh3 deb3 fonseca1 fonseca2 gianna hanne1 hanne1.constr hanne2 hanne2.constr hanne3 hanne3.constr hanne4 hanne4.constr hanne5 hanne5.constr jimenez jimenez.constr vnt zdt1 zdt2 zdt3
Quality measures for MCO solutionsdominatedHypervolume epsilonIndicator generalizedSpread generationalDistance
Normalize a pareto frontnormalizeFront
NSGA II MOEAnsga2
Pareto Front and pareto set gettersparetoFilter paretoFront paretoSet