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📅 AI-Powered Time Table Generator — Web Application

📅 AI-Powered Time Table Generator — Web Application

Time Table Generator

Efficient scheduling made easy. The Time Table Generator is a powerful, professional-grade web application that automatically generates optimized timetables for academic institutions based on user-defined constraints. Whether youre a college administrator, a school scheduler, or a course coordinator, this free tool saves hours of manual planning with AI-assisted precision.

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Project Summary

Project Name Time Table Generator Web Application
Language/s Used Python (Flask), JavaScript (ReactJS)
Backend Python (Flask Framework)
Frontend ReactJS
Database No Database Used
Developer
Type Web Application

About the Time Table Generator

The system is designed using a Constraint Satisfaction Problem (CSP) model that intelligently assigns time slots and teachers based on multiple constraints provided by the user. It delivers a valid timetable with no conflicts, all within seconds.

Constraint Satisfaction Problem (CSP) Model

  • Variables: Set of available time-slots
  • Domain: Set of all subjects to be scheduled
  • Constraints:
    • No overlap between subjects
    • Grouping of subjects with multi-hour sessions
    • Respect teacher working hours
    • Avoid back-to-back scheduling of specific subjects

User Inputs

  • Course Name
  • Instructor Name
  • Number of Lectures Per Week
  • Duration per Lecture/Lab
  • Instructor Availability
  • Overall Working Days/Hours
  • Subjects that must not be scheduled consecutively

Available Features

  • Automatic conflict-free scheduling
  • CSP-based intelligent slot assignment
  • Instructor availability consideration
  • Responsive user interface (ReactJS)
  • Lightweight no external database required
  • Frontend-backend integration via REST APIs
  • Visual preview of generated timetable

How to Run This Project

  1. Download the full project using the button below.
  2. Unzip the project folder.
  3. Install Backend Dependencies: cd backend pip install -r requirements.txt python app.py
  4. Run Frontend: cd ../ npm install npm start
  5. Open your browser at .

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Source Code Available

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