Key takeaways
- Automatic timetabling means validated data, solver generation, then planner control, not a single unattended button.
- Hard and soft constraints, infeasibility reports, waiting area, pin, and regenerate keep rules explicit.
- Pre-solve validation explains missing data and conflicts before generation runs.
- Planning and published timetables share one Smootables model end to end.
What does automatic school timetabling actually involve?
Automatic school timetabling means a constraint solver places lessons into periods from a validated plan. It is not one unattended button. In Smootables, the real work surrounds that solve: correct data, rules that match school policy, and planner edits afterwards.
Smootables is designed around that workflow. The solver is fast, but the value is in pre-solve validation, the infeasibility reports when generation cannot succeed, and the editing tools that keep planners in control afterwards. Spreadsheet workflows and separate generators often leave those steps to manual cleanup.
For the full end-to-end process with Smootables steps at each stage, see how to create a school timetable.
How does Smootables generate a timetable, step by step?
From a validated school year plan in Smootables, the constraint solver produces a feasible period timetable in four stages. Each stage is inspectable: validation first, then constraint reading, then placement, then an editable result with a waiting area.
- Pre-generation validation explains missing data, impossible workloads, capacity issues, and likely infeasibility before you wait for a solve.
- Constraints are read from the planning model: teacher and room conflicts, capacity, availability, weekly loads, lunch and break rules, pinned lessons, dependencies, and resource compatibility.
- The solver places lessons across the period, respecting hard constraints and optimizing against configurable soft preferences.
- Results are presented as an editable timetable, with a waiting area for lessons that could not be placed under the current rules.
How does automatic timetabling in Smootables compare to solver-only tools?
Buyers often compare AI-powered school timetabling, standalone generators, spreadsheet workflows, and planning-first platforms. The table contrasts a solver-only approach prepared in spreadsheets with Smootables, where validation, generation, and editing share one model.
| Dimension | Solver-only tools / spreadsheets | Smootables |
|---|---|---|
| Before the solve | Generation runs on whatever data is entered; errors surface as failed solves | Pre-solve validation explains missing data and impossible workloads first |
| Constraints | Hard rules configured per project; soft preferences vary by tool | Hard and soft constraints read from the shared planning model |
| When no solution exists | Silent no-result or a cryptic failure to interpret | Infeasibility report naming the conflicting constraints and likely fixes |
| After the solve | Re-run or hand-edit; exports drift from the source data | Drag-and-drop, pin, split and merge, regenerate around locks, version history |
| Unplaced lessons | Block the run or quietly disappear | Held in a waiting area to resolve manually or relax a rule |
| Data flow | Re-import between spreadsheet, generator, and publishing tool | One Smootables model from plan to published timetable |
Which constraints does the Smootables solver understand?
Smootables separates rules into hard constraints the solver must satisfy and soft constraints it optimizes, then surfaces problems through pre-solve checks and infeasibility reports. The four cards below summarize what the engine reads from your plan, using one shared model for planning and generation.
Hard constraints
Teacher conflicts, room conflicts, group conflicts, optional student conflicts, availability, capacity, weekly loads, lunch, breaks, pinned lessons, dependencies, and resource compatibility.
Soft constraints
Gap hours, balance across days, preferred times, teacher preferences, student experience, room quality, and school-specific priorities you can re-weight.
Pre-solve checks
Validation flags impossible workloads, missing teachers or rooms, and capacity problems before the solver runs, so planners do not spend time interpreting opaque failures.
Infeasibility reports
When a timetable cannot work as configured, Smootables explains why and suggests concrete fixes instead of returning a silent no-result.
What can planners change after the solve?
A solver result is rarely the final timetable. Planners move lessons, swap teachers, split a workshop, or pin a lesson and regenerate the rest, with control that is hard to maintain in spreadsheet grids or disconnected generators. Smootables supports drag-and-drop edits, swaps, split and merge, pin and regenerate, slot insight before a drop, undo and redo, version history, and timetable branches so you can compare alternatives instead of overwriting a working draft.
Lessons that cannot be placed under the current rules go to a waiting area instead of stopping generation. Planners resolve them manually, relax a constraint, or send them back to the Smootables solver after adjusting the plan. Undo, redo, version history, and branches let planners compare alternatives safely without re-keying data between tools.
Questions about automatic timetabling
Does the AI generate the timetable on its own?
No. Generation is based on solving a mathematical multi-constraint optimization problem using algorithms, not AI-only. The AI assistant helps planners describe what they want in natural language, make large plan and timetable changes effortlessly, explain tradeoffs, and run scenario comparisons.
What happens if no feasible timetable exists?
You get an infeasibility report instead of a broken result. The report explains which constraints conflict, which resources are over-committed, and what changes would make a solve possible. Many infeasibility cases are caught earlier by pre-solve validation.
Can we pin parts of the timetable?
Yes. Pinned lessons are treated as hard constraints during regeneration, so you can lock placements you have agreed and let the solver work around them. Locked resources, branches, and version history make it safe to experiment.
Does it handle vocational constraints?
Yes. Smootables is vocational college timetable software designed for schools whose timetables involve workshops, specialist rooms, equipment, mixed cohorts, off-site or workplace learning, and individual student pathways, not only standard class periods.
How is Smootables different from generation-first timetable tools?
Generation-first tools focus on setting constraints, running the solver, and refining the result. Smootables starts with the school year plan: courses, teachers, workloads, and rules all live in one workspace. You validate before you generate, catch staffing problems early, and regenerate without exporting data to a separate tool. If planning, workload visibility, and individual student pathways matter as much as the final schedule, Smootables is built for that workflow.