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MOEADr  

Component-Wise MOEA/D Implementation
View on CRAN: Click here


Download and install MOEADr package within the R console
Install from CRAN:
install.packages("MOEADr")

Install from Github:
library("remotes")
install_github("cran/MOEADr")

Install by package version:
library("remotes")
install_version("MOEADr", "1.1.3")



Attach the package and use:
library("MOEADr")
Maintained by
Felipe Campelo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-03-16
Latest Update: 2023-01-08
Description:
Modular implementation of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) [Zhang and Li (2007), ] 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 [].
How to cite:
Felipe Campelo (2017). MOEADr: Component-Wise MOEA/D Implementation. R package version 1.1.3, https://cran.r-project.org/web/packages/MOEADr. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.2.0 (2017-03-16 08:44), 0.2.1 (2017-03-20 06:22), 1.0.0 (2017-08-20 21:51), 1.1.0 (2017-10-24 09:15), 1.1.1 (2020-02-17 21:20)
Other packages that cited MOEADr R package
View MOEADr citation profile
Other R packages that MOEADr depends, imports, suggests or enhances
Complete documentation for MOEADr
Functions, R codes and Examples using the MOEADr R package
Some associated functions: box_constraints . calcIGD . check_stop_criteria . constraint_none . constraint_penalty . constraint_vbr . create_population . decomposition_msld . decomposition_sld . decomposition_uniform . define_neighborhood . evaluate_population . example_problem . find_nondominated_points . generate_weights . get_constraint_methods . get_decomposition_methods . get_localsearch_methods . get_scalarization_methods . get_stop_criteria . get_update_methods . get_variation_operators . ls_dvls . ls_tpqa . make_vectorized_smoof . moead . order_neighborhood . perform_variation . plot.moead . preset_moead . print.moead . print_progress . scalarization_awt . scalarization_ipbi . scalarization_pbi . scalarization_ws . scalarization_wt . scalarize_values . scale_objectives . stop_maxeval . stop_maxiter . stop_maxtime . summary.moead . unitary_constraints . update_population . updt_best . updt_restricted . updt_standard . variation_binrec . variation_diffmut . variation_localsearch . variation_none . variation_polymut . variation_sbx . variation_truncate . 
Some associated R codes: calcIGD.R . check_stop_criteria.R . constraint_none.R . constraint_penalty.R . constraint_vbr.R . create_population.R . decomposition_msld.R . decomposition_sld.R . decomposition_uniform.R . define_neighborhood.R . evaluate_population.R . example_problem.R . find_nondominated_points.R . generate_weights.R . get_constraint_methods.R . get_decomposition_methods.R . get_localsearch_methods.R . get_scalarization_methods.R . get_stop_criteria.R . get_update_methods.R . get_variation_operators.R . ls_dvls.R . ls_tpqa.R . make_vectorized_smoof.R . moead.R . order_neigborhood.R . perform_variation.R . plot_moead.R . preset_moead.R . print_moead.R . print_progress.R . sample_constraints.R . scalarization_awt.R . scalarization_ipbi.R . scalarization_pbi.R . scalarization_ws.R . scalarization_wt.R . scalarize_values.R . scale_objectives.R . stop_maxeval.R . stop_maxiter.R . stop_maxtime.R . summary_moead.R . update_population.R . updt_best.R . updt_restricted.R . updt_standard.R . utils.R . variation_binrec.R . variation_diffmut.R . variation_localsearch.R . variation_none.R . variation_polymut.R . variation_sbx.R . variation_truncate.R .  Full MOEADr package functions and examples
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