mleary / committee_assigment

committee_assigment

The goal of committee_assigment is to expedite the creation of balanced committee assignments given a handful of constraints.

This is achieved by using the {GA} package to run a genetic algorithim and optimize committee assignments.

Objectives & Constraints

The main objective is to create balanced committee assignments that represent the overall population as whole. This means controlling for certain variables, such as gender, occupation, region, etc.

The largest constraint are:

• Gender (ensure balanced gender representation)
  • Goal is 50% Female / 50% Male (this was a basic demo that ignores other gender identities (i.e. non-binary))
• Job (ensure each Job role is equally represented)
  • Goal is 25% each category
  • Large penalty applied if any Job is less than 15% of committee
• Region (ensure representation from each region, try to balance it)
  • Goal is 9% per region
  • Large penalty applied if any region is not represented at all

Using this repo

This project was setup with the {checkpoint} for package versioning. It’s not perfect but it works. You can activate the checkpoint folder by running the utils\project_setup.R file. More details on project development environment is listed belowin the Session Info section.

The utils\ga_helpers.R file has all the functions used in genetic algorithim.

The utils\generate_fake_data.R file is a temp file purely for development. It, as the name suggests, generates fake data to demo how the process could work.

Session Info

sessionInfo()
#> R version 4.0.2 (2020-06-22)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 19041)
#> 
#> Matrix products: default
#> 
#> locale:
#> [1] LC_COLLATE=English_United States.1252 
#> [2] LC_CTYPE=English_United States.1252   
#> [3] LC_MONETARY=English_United States.1252
#> [4] LC_NUMERIC=C                          
#> [5] LC_TIME=English_United States.1252    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  [1] compiler_4.0.2  magrittr_2.0.1  tools_4.0.2     htmltools_0.5.0
#>  [5] yaml_2.2.1      stringi_1.4.6   rmarkdown_2.3   knitr_1.30     
#>  [9] stringr_1.4.0   xfun_0.18       digest_0.6.25   rlang_0.4.9    
#> [13] evaluate_0.14