TimeWeaver is an intelligent academic scheduling platform that automatically generates conflict-free timetables while optimizing faculty workload, classroom usage, and institutional constraints.
It transforms complex manual scheduling into an efficient, transparent, and error-free process.
- ✅ Automated conflict-free timetable generation
- ✅ Supports theory classes, labs, electives, and multi-section courses
- ✅ Faculty workload balancing
- ✅ Classroom & resource capacity optimization
- ✅ Real-world institutional constraints handling
- ✅ Unified optimization engine (constraints + optimization logic)
- ✅ Interactive timetable visualization
- ✅ Scalable and modular system design
TimeWeaver uses a single unified optimization engine that:
- Models institutional rules as constraints
- Applies optimization logic to generate feasible schedules
- Automatically detects and resolves conflicts
- Ensures balanced faculty workload distribution
The frontend includes a Visualization Module to clearly display timetables and workload allocation.
| Layer | Technology |
|---|---|
| Frontend | HTML, CSS, JavaScript |
| Backend | Python (Flask) |
| Database | MongoDB |
| Optimization | Constraint-based & heuristic scheduling |
| Deployment | Docker (optional) |
The project follows standard software engineering practices and includes:
- Use Case Diagram
- Class Diagram
- Sequence Diagram (MoB)
- Activity / Deployment Diagram
These diagrams help understand system flow, architecture, and interactions.
TimeWeaver/ │── frontend/ │ ├── index.html │ ├── styles.css │ └── scripts.js │ │── backend/ │ ├── app.py │ ├── scheduler/ │ │ └── optimization_engine.py │ └── models/ │ │── database/ │ └── schema.json │ │── uml/ │ └── diagrams/ │ │── README.md
- Universities & colleges
- Academic coordinators
- Faculty workload planners
- Institutions with complex scheduling requirements
- AI-based predictive scheduling
- Role-based access (Admin, Faculty)
- Export timetables as PDF / Excel
- Real-time constraint updates
- Cloud deployment
Anush Rithvic
Computer Science Undergraduate
Passionate about building scalable, impactful systems
If you find this project useful, please give it a ⭐ on GitHub!