Optimal Group Assignment and Workload Allocation

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Documentation for package ‘grouper’ version 0.7.3

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

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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