PROJECT OVERVIEW

The goal of this project is to develop an automated system for generating university timetables while minimizing scheduling conflicts and optimizing resource utilization.  Each module consists of 3 lectures, 1 tutorial, and 1 practical per week, and multiple student groups need to be accommodated across different time slots and venues without clashes. To achieve this, advanced optimization algorithms such as Genetic Algorithms will be explored to efficiently allocate modules, groups, and venues. The system will consider constraints like room capacity, faculty availability, and module dependencies to generate feasible schedules. The project will involve data pre-processing, understanding existing scheduling methods, and implementing an algorithm that dynamically adjusts based on input constraints. The expected outcome is a flexible, scalable system that can automate timetable creation while improving scheduling efficiency.