University Timetable Generator using Genetic Algorithm

Overview

This project implements a timetable generation system for university courses using a genetic algorithm. It efficiently creates schedules while adhering to various constraints, optimizing for factors such as professor availability, room capacity, and course timing preferences.

Features

• Automated generation of university course timetables
• Consideration of multiple constraints:
  • Professor availability
  • Room capacity and type (classroom/lab)
  • Course timing preferences
  • Section-specific requirements
• Genetic algorithm implementation for optimization
• Conflict resolution for overlapping schedules
• Printable timetable output

Technologies Used

• Python 3.x
• PrettyTable library for formatted output

Installation

1. Ensure you have Python 3.x installed on your system.
2. Clone this repository:

   git clone https://github.com/your-username/timetable-generator-genetic-algorithm.git
   

3. Navigate to the project directory:

   cd timetable-generator-genetic-algorithm
   

4. Install required dependencies:

   pip install prettytable
   

Usage

1. Run the main script:

   python timetable_generator.py
   

2. The program will generate a timetable based on the predefined constraints and courses.
3. The best timetable will be displayed in the console.

How It Works

1. Initial Population Generation: Creates a set of random timetables.
2. Fitness Evaluation: Assesses each timetable for conflicts and constraint violations.
3. Selection: Chooses the best timetables for reproduction.
4. Crossover: Combines features from two parent timetables.
5. Mutation: Introduces random changes to maintain diversity.
6. Iteration: Repeats the process until a satisfactory timetable is found.

Customization

You can customize the timetable generation by modifying the following in the timetable_generator.py file:

• courses: Add or modify course details
• sections: Adjust section information
• professors: Update professor availability
• rooms: Change room capacities and types
• Constraints: Modify the fitness function to add or adjust constraints

Future Improvements

• GUI for easier input of courses, professors, and rooms
• Export functionality for generated timetables (e.g., CSV, PDF)
• Integration with university management systems
• Performance optimization for larger datasets

Contributing

Contributions to improve the timetable generator are welcome. Please feel free to submit a pull request or open an issue for discussion.

Contact

Ahmed Abd-ur-Rahman - i210404@nu.edu.pk

Project Link: https://github.com/Asquarer02/Timtable-using-Genetic-Algorithm