Free Merit & Preference Placement Allocator
Turn a rank list and preference sheets into a defensible posting list in seconds. Allocate ranked candidates to vacancies by merit and ordered preference across medical internships, postgraduate rotations, teacher postings, and limited-seat programmes — with quota, couples, capacity, and rotation rules. Import CSV or Excel; export PDF, Excel, or CSV. See our companion guide on how to allocate placements by merit and preference.
Runs entirely in your browser · No login · No data uploaded
Start from a coherent rule bundle with matching sample data, or start blank.
Paste CSV/Excel-XML with a header row, or upload a file. Columns auto-map.
Each vacancy needs an ID, a name, and a capacity. Location/Group/Cutoff power the rules.
Long format CandidateID,PreferenceOrder,VacancyID or wide CandidateID,Pref1,Pref2,…. Auto-detected.
How to break candidates that share the same merit rank or score.
Capacity is always enforced. Add rules below; order matters and is reorderable.
Load a scenario or import your three tables, then click Run Allocation to generate a posting list with a full audit trail.
How to Allocate Placements in 3 Steps
Follow these steps to get results in under a minute
Free Placement Allocation Engine — FAQ
What is a placement allocation engine?
How do I use the placement allocation tool?
Is this placement allocation tool free?
Who should use this placement allocation tool?
How do I export the allocation results?
How Placement Allocation Engine Compares
vs spreadsheets, manual processes, and paid platforms
| Feature | UniCloud360 Placement Allocation Engine | Manual Spreadsheet | Generic Lottery Tool | Custom-Built Script |
|---|---|---|---|---|
| Merit + ordered preference | Rank-respecting passes | Manual sort & lookup | Random only | Must code it |
| Configurable rule sets | 10 rule types, reorderable | Formula spaghetti | None | Hard-coded per run |
| Couples / spouse linking | Co-location pass | Manual rework | No | Complex to code |
| Quota reservations | Count or % with rollover | Helper columns | No | Custom logic |
| Multi-period rotations | Per-period timetable | Many sheets | No | State management |
| Stable (Gale–Shapley) matching | Built in | Not possible | No | Algorithm needed |
| Audit trail / explainability | Per-candidate trace | No record | No | Usually none |
| CSV + Excel + PDF export | All three + audit log | Save-as only | CSV maybe | DIY |
| Runs offline / no login | In your browser | Local file | Depends | Local script |
| Cost | Free forever | Time-intensive | Often paid | Developer time |
What Allocation Teams Are Saying
Trusted by lecturers and students across Sri Lankan universities
"The couples rule alone saved us a weekend of manual rework. Both partners landed at the same hospital from the lower-ranked partner's list, exactly per our policy, and the audit trail proved it to the board."
"We used to build the posting list in a spreadsheet over a weekend. Now it is a few seconds, and the run signature means two officers get the identical result and can prove it."
"Quota reservations with rollover were the dealbreaker for us. Reserved seats fill first, unfilled ones roll to open merit, and every step is explained per candidate."
"Deferred acceptance gave us a stable matching for our internship-to-employer round, and the optimal mode let us compare how much overall satisfaction we gain versus strict rank priority."
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How merit-and-preference allocation works
The three mechanisms behind the engine — and the couples rule worked example.
Serial dictatorship (merit-serial)
Candidates are processed strictly in merit-rank order. Each candidate walks their own preference list from top to bottom and takes the first vacancy that still has capacity and that they are eligible for. It is deterministic, easy to defend, and is the procedure used by most posting exercises.
Deferred acceptance (Gale–Shapley)
When vacancies also rank candidates, candidate-proposing deferred acceptance produces a stable matching: no candidate–vacancy pair would both rather be matched to each other than to their current assignment. Free candidates propose down their list; each vacancy tentatively holds its best proposers up to capacity and releases the rest.
Optimal assignment (utilitarian)
Instead of strict rank priority, optimal assignment minimises the total preference cost across everyone — the sum of the chosen preference positions. It maximises overall satisfaction but may hand a lower-ranked candidate a better slot than a higher-ranked one, so only use it when policy permits.
The couples rule — worked example
Two partners are linked (say ranks 14 and 130). The pair is processed at the better rank (14), but both are allocated together from the lower-ranked partner's preference list (rank 130) and to the same location. The audit records the combined-preference logic so the outcome is explainable.