Timetable Generator Using Genetic Algorithm and Constraint Satisfaction Problem

Timetable generation in academic institutions is time consuming, complex and error-prone task due to various constrains involving faculty availability, time restrictions and scheduling conflicts. Manual scheduling often leads to inefficiencies and human errors. The system proposes an Automatic timetable generator using Optimization algorithms to address complexities. Optimization algorithms find the best solution from all possible solutions under the given constrains. It combinations several possible timetable combinations and identifies the most suitable one while satisfying essential conditions. The model is built using a hybrid CSP-GA framework that combines Constraint Programming for efficient local repair and feasibility assurance and Genetic Algorithms for global exploration of the solution space. The system models hard constraints such as Faculty availability, Room Capacity, Elimination of overlaps and exclusion of fixed break times from scheduling etc. In addition, it also considers soft constraints such as teacher preferences, minimizing idle time between classes, and distributing lectures evenly throughout the week. The system thereby focuses on benefiting the academic institutions by providing a flexible, intelligent framework capable of generating efficient timetables of varying size and complexities.