Package: grouper 0.6.2

Mingyuan Zhang

grouper: Optimal Assignment of Students to Groups

Integer programming models to assign students to groups by maximising diversity within groups, or by maximising preference scores for topics.

Authors:Vik Gopal [aut], Kevin Lam [aut], Ju Xue [ctb], Mingyuan Zhang [aut, cre], National University of Singapore [cph]

grouper_0.6.2.tar.gz
grouper_0.6.2.zip(r-4.7)grouper_0.6.2.zip(r-4.6)grouper_0.6.2.zip(r-4.5)
grouper_0.6.2.tgz(r-4.6-any)grouper_0.6.2.tgz(r-4.5-any)
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grouper_0.6.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
grouper/json (API)

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

Bug tracker:https://github.com/zimmy313/grouper/issues

Pkgdown/docs site:https://zimmy313.github.io

Datasets:

On CRAN:

Conda:

educationglpkgurobioptimisation

6.04 score 17 scripts 161 downloads 11 exports 24 dependencies

Last updated from:e0160718a7. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING131
source / vignettesOK162
linux-release-x86_64WARNING127
macos-release-arm64WARNING125
macos-oldrel-arm64WARNING172
windows-develWARNING80
windows-releaseWARNING82
windows-oldrelWARNING69
wasm-releaseOK110

Exports:%>%assign_groupsassign_jobextract_infoextract_params_yamlextract_phd_infoextract_student_infoprepare_diversity_modelprepare_modelprepare_phd_modelprepare_preference_model

Dependencies:cliclusterdata.tabledplyrfastmapgenericsgluelatticelazyevallifecyclelistcompmagrittrMatrixomprpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithryaml

Application to simple datasets
Introduction | Diversity-Based Assignment | Dataset 001 (diversity only) | Dataset 001 (skills only) | Dataset 003 | Dataset 004 | Preference-Based Assignment | Dataset 002 | PhD Workload Assignment | Dataset 001(Year-long) | Dataset 001 (Single-semester)

Last update: 2026-05-15
Started: 2025-06-27

Related work and grouper
Introduction | Balancing staff workload and student preferences | OptAssign | Students to elective courses | Assigning students to groups based on traits | Student-to-project supervisor assignment | Automated group assignments in academic setting | Introducing grouper package | References

Last update: 2026-05-15
Started: 2025-06-27

PhD Workload Allocation
Model introduction | Objective function | Constraints | Demand satisfaction | TA spread among non-Year-1 students | Annual workload equality | Year-1 TA soft upper bound | Optional current-semester workload bounds

Last update: 2026-04-28
Started: 2026-04-28

Maximising Diversity and Balancing Skill
Model introduction | Objective function | Constraints | Group to topic-repetition combination | Defining $z_{ijtr}$ | Number of repetitions per topic | Number of students per group | Per-group skill levels | Binary and non-negativity constraints

Last update: 2025-06-27
Started: 2025-06-27

Maximising Preference
Model introduction | Objective function | Constraints | Group to topic-repetition combination | Number of repetitions per topic | Balanced number of subgroups | Number of students per subgroup | Binary and non-negativity constraints

Last update: 2025-06-27
Started: 2025-06-27