Examples
Examples
Try the starting example
- JSON Review slots [paper ID,slot ID,eligible reviewer IDs]
- [["P1","1",["A","B"]],["P1","2",["A","B"]],["P2","1",["A","B"]]]
- JSON Reviewer total capacities [reviewer ID,count]
- [["A",2],["B",2]]
- Review assignments [paper,slot,reviewer]
- [["P1","1","A"],["P1","2","B"],["P2","1","A"]]
- Uncovered [paper,slot]
- []
- Assigned slot count
- 3
Try another scenario
- JSON Review slots [paper ID,slot ID,eligible reviewer IDs]
- [["P1","1",["A","B"]],["P1","2",["A","B"]],["P2","1",["A","B"]]]
- JSON Reviewer total capacities [reviewer ID,count]
- [["A",1],["B",1]]
- Review assignments [paper,slot,reviewer]
- [["P1","1","A"],["P1","2","B"]]
- Uncovered [paper,slot]
- [["P2","1"]]
- Assigned slot count
- 2
Calculation method
Calculation method
Review assignments [paper,slot,reviewer]
Exact backtracking maximizes assigned slots then minimizes sum squared reviewer loads; lexical assignment tie-break.
Uncovered [paper,slot]
Slots absent from selected exact assignment.
Assigned slot count
Number of assigned reviews.
Symbols and units
- a
- JSON Review slots [paper ID,slot ID,eligible reviewer IDs]
- b
- JSON Reviewer total capacities [reviewer ID,count]
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- Expertise/conflict eligibility supplied; distinct reviewers per paper enforced. Exact maximum coverage followed by balanced load objective within stated small bounds. Supported limits: At most 10 review slots, 6 reviewers, maximum 4 eligible reviewers per slot.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.