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High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)
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Introduces the Fair High School Scheduling Problem (FHSSP), extending HSSP with student preferences and envy-freeness-style constraints, and solves it with a CP-SAT integer programming model on real course-request data from a California high school.
Problem
High school course scheduling via standard IP/CP methods ignores student preferences and fairness, producing allocations students perceive as unfair.
Approach
Extends HSSP with a degree-of-interest and priority-order model and an envy constraint (student envies another if the other has a course they want more and has more courses), encoded in a binary IP solved with OR-Tools CP-SAT.
Key results
- Across six student subsets (48-50 students, 5 courses each), the IP model produced feasible HSSP solutions and optimal FHSSP solutions.
- No student envy instances occurred in any of the six groups under the fairness constraints.
- Solve times ranged from about 18.4s to 26.9s per group on an Apple M2-Max laptop.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add fairness constraints to the HSSP model | FHSSP IP model · Real course-request data, six student groups | student envy | Helped |
Limitations
- Evaluation uses artificial instructor and room data and randomized priorities and preferences, not real data for these components.
- Data is split into six small subsets of about 50 students and 5 courses each, so full-scale scalability is not demonstrated.
- Only a single school dataset is used and no comparison with existing scheduling systems or baselines is reported.
Experimental setup
Datasets: real course request data from a private California high school (295 students, 121 courses)
Benchmarks: real course request data from a private California high school (Menlo School)
Metrics: feasibility student envy count solve time
Baselines: traditional IP for HSSP constraint programming schedulers
Builds on: High School Scheduling Problem (HSSP) IP formulations market design fair matching
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