Optimal Group Assignment and Workload Allocation


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Documentation for package ‘grouper’ version 0.7.3

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assign_groups Assigns model result to the original data frame.
assign_job Convert workload allocation to a manual-style wide table
compute_diversity Compute total pairwise diversity for a set of students
convert_pref_mat Convert a preference matrix to rank-based scores
dba_gc_ex001 DBA Group Composition Data Example 001
dba_gc_ex003 DBA Group Composition Data Example 003
dba_gc_ex004 DBA Group Composition Data Example 004
extract_info Extract model inputs (wrapper)
extract_multirole_info Extract inputs for the multi-role workload allocation model
extract_params_yaml Extract parameters from a YAML file
extract_student_info Extract student information
get_group_pref_score Look up a group's preference score for a topic-subtopic combination
multirole_demand_ex001 Multi-role Demand Matrix Example 001
multirole_prefmat_ex001 Multi-role Preference Matrix Example 001
multirole_students_ex001 Multi-role Individual Data Example 001
pba_gc_ex002 PBA Group Composition Data Example 002
pba_prefmat_ex002 PBA Group Preference Data Example 002
prepare_diversity_model Prepare the diversity-based assignment model
prepare_model Initialise optimisation model (wrapper)
prepare_multirole_model Prepare the multi-role workload allocation model
prepare_preference_model Prepare the preference-based assignment model
solve_assignment Solve a prepared model and post-process the assignment
summary_dba Summarise a DBA result by topic-repetition group
summary_pba Summarise a PBA result by topic-subtopic-repetition group