Package: MOEADr 1.1.3

MOEADr: Component-Wise MOEA/D Implementation

Modular implementation of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) [Zhang and Li (2007), <doi:10.1109/TEVC.2007.892759>] for quick assembling and testing of new algorithmic components, as well as easy replication of published MOEA/D proposals. The full framework is documented in a paper published in the Journal of Statistical Software [<doi:10.18637/jss.v092.i06>].

Authors:Felipe Campelo [aut, cre], Lucas Batista [com], Claus Aranha [aut]

MOEADr_1.1.3.tar.gz
MOEADr_1.1.3.zip(r-4.5)MOEADr_1.1.3.zip(r-4.4)MOEADr_1.1.3.zip(r-4.3)
MOEADr_1.1.3.tgz(r-4.4-any)MOEADr_1.1.3.tgz(r-4.3-any)
MOEADr_1.1.3.tar.gz(r-4.5-noble)MOEADr_1.1.3.tar.gz(r-4.4-noble)
MOEADr_1.1.3.tgz(r-4.4-emscripten)MOEADr_1.1.3.tgz(r-4.3-emscripten)
MOEADr.pdf |MOEADr.html✨
MOEADr/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/fcampelo/moeadr/issues

On CRAN:

moeadmultiobjective-optimization

52 exports 20 stars 2.06 score 2 dependencies 40 scripts 214 downloads

Last updated 2 years agofrom:0ac9b1962e. Checks:OK: 3 NOTE: 4. Indexed: yes.

Exports:box_constraintscalcIGDcheck_stop_criteriaconstraint_noneconstraint_penaltyconstraint_vbrcreate_populationdecomposition_mslddecomposition_slddecomposition_uniformdefine_neighborhoodevaluate_populationexample_problemfind_nondominated_pointsgenerate_weightsget_constraint_methodsget_decomposition_methodsget_localsearch_methodsget_scalarization_methodsget_stop_criteriaget_update_methodsget_variation_operatorsls_dvlsls_tpqamake_vectorized_smoofmoeadorder_neighborhoodperform_variationpreset_moeadprint_progressscalarization_awtscalarization_ipbiscalarization_pbiscalarization_wsscalarization_wtscalarize_valuesscale_objectivesstop_maxevalstop_maxiterstop_maxtimeunitary_constraintsupdate_populationupdt_bestupdt_restrictedupdt_standardvariation_binrecvariation_diffmutvariation_localsearchvariation_nonevariation_polymutvariation_sbxvariation_truncate

Dependencies:assertthatFNN