Automatic Timetable Generator Using AI

Timetable generation in higher educational institutions is a constraint-heavy and repetitive process.Traditional spreadsheet-based methods are time-consuming, error-prone, and difficult to scale.This paper presents "Timely", an AI-driven automatic timetable generation system designed as a native Android application.The system leverages a Flask-based backend with Supabase integration and incorporates an intelligent AI model to generate optimized weekly timetables under real institutional constraints.The application supports professorlevel management, student-level timetable viewing, and real-time notifications through Firebase Cloud Messaging.Unlike conventional rule-based or algorithm-intensive approaches such as Genetic Algorithms or Constraint Satisfaction models, the proposed solution adopts a fine-tuned AI strategy tailored to domain-specific academic requirements.The modular architecture ensures scalability, maintainability, and real-world usability across departments.Furthermore, the system is designed to efficiently manage faculty workload distribution, subject allocation, and batch-wise practical scheduling without manual intervention.The AI engine evaluates multiple constraint combinations to produce balanced and conflict-free weekly timetables while maintaining academic structure and institutional policies.The application also allows controlled editing and publishing of schedules, ensuring flexibility in case of changes or rescheduling.By integrating mobile technology, cloud-based data management, and intelligent automation, the proposed solution significantly reduces administrative effort and enhances scheduling accuracy.The system demonstrates a practical and reliable approach toward modernizing academic timetable management through AI-driven optimization and structured system design.