Package: grouper 0.7.3

grouper: Optimal Group Assignment and Workload Allocation

Integer programming models to assign students to groups by maximising diversity or topic preferences, and to allocate multi-role teaching workloads while balancing role demand, preferences, fairness, and cohort protection.

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

grouper_0.7.3.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
grouper/json (API)

# Install 'grouper' in R:
install.packages('grouper', repos = c('https://zimmy313.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:

6.10 score 18 scripts 251 downloads 19 exports 24 dependencies

Last updated from:1f8eb72060. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK482
source / vignettesOK184
linux-release-x86_64OK144
macos-release-arm64OK217
macos-oldrel-arm64OK184
windows-develOK96
windows-releaseOK106
windows-oldrelOK111
wasm-releaseOK114

Exports:%>%assign_groupsassign_jobcompute_diversityconvert_pref_matextract_infoextract_multirole_infoextract_params_yamlextract_phd_infoextract_student_infoget_group_pref_scoreprepare_diversity_modelprepare_modelprepare_multirole_modelprepare_phd_modelprepare_preference_modelsolve_assignmentsummary_dbasummary_pba

Dependencies:cliclusterdata.tabledplyrfastmapgenericsgluelatticelazyevallifecyclelistcompmagrittrMatrixomprpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithryaml

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
Rendered fromb-diversity-skill.Rmdusingknitr::rmarkdown

Last update: 2026-07-06
Started: 2025-06-27

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 | Multi-role Workload Assignment | Full TA and GR workflow | Single-semester
Rendered fromd-sanity-checks.Rmdusingknitr::rmarkdown

Last update: 2026-07-06
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
Rendered fromc-subgroups-preference.Rmdusingknitr::rmarkdown

Last update: 2026-07-06
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 | Diversity-Based Assignment | Preference-Based Assignment | Multi-role Workload Allocation | Function organisation | References
Rendered froma-related-work.Rmdusingknitr::rmarkdown

Last update: 2026-06-18
Started: 2025-06-27

Multi-role Workload Allocation
Model introduction | Model formulation | Objective function | Demand satisfaction | Role-specific workload spread | Annual workload equality | Protected-cohort soft upper bounds | Optional current-semester workload bounds | Package interface | Semester history and capacity | E-allocation scoring | Role-specific terms | Keeping the model small
Rendered frome-phd-workload.Rmdusingknitr::rmarkdown

Last update: 2026-06-18
Started: 2026-04-28

Readme and manuals

Help Manual

Help pageTopics
Assigns model result to the original data frame.assign_groups
Convert workload allocation to a manual-style wide tableassign_job
Compute total pairwise diversity for a set of studentscompute_diversity
Convert a preference matrix to rank-based scoresconvert_pref_mat
DBA Group Composition Data Example 001dba_gc_ex001
DBA Group Composition Data Example 003dba_gc_ex003
DBA Group Composition Data Example 004dba_gc_ex004
Extract model inputs (wrapper)extract_info
Extract inputs for the multi-role workload allocation modelextract_multirole_info
Extract parameters from a YAML fileextract_params_yaml
Extract student informationextract_student_info
Look up a group's preference score for a topic-subtopic combinationget_group_pref_score
Multi-role Demand Matrix Example 001multirole_demand_ex001
Multi-role Preference Matrix Example 001multirole_prefmat_ex001
Multi-role Individual Data Example 001multirole_students_ex001
PBA Group Composition Data Example 002pba_gc_ex002
PBA Group Preference Data Example 002pba_prefmat_ex002
Prepare the diversity-based assignment modelprepare_diversity_model
Initialise optimisation model (wrapper)prepare_model
Prepare the multi-role workload allocation modelprepare_multirole_model
Prepare the preference-based assignment modelprepare_preference_model
Solve a prepared model and post-process the assignmentsolve_assignment
Summarise a DBA result by topic-repetition groupsummary_dba
Summarise a PBA result by topic-subtopic-repetition groupsummary_pba