Exam Timetable and Room Allocation Using Genetic Algorithm

Abstract

Scheduling examinations at an institution is a very difficult task. Many things must be taken care of at that time. This is a study about Exam Timetable and Room Allocation System. This is a system based on Genetic Algorithm, this is how nature chooses the best ones. It thinks Exam Timetables as a group of codes. Then selection, crossover and mutation are applied to evolve Exam Timetables. There is a way of measuring how good the Exam Timetable is. It penalizes the Exam Timetable in case there is exam conflict or resources not enough capacity, or the exams not evenly spaced out. It rewards the Exam Timetable if it uses resources well. We measure Exam Timetable and Room Allocation System. We find that it greatly decreases the errors in scheduling. It also uses work well and resources well than current way of doing manually. The Exam Timetable and Room Allocation System can be easily adjusted to changes at an institution. It provides a foundation for adding things like assigning people to watch exams automatically and making sure the workload is fair, for the Exam Timetable and Room Allocation System. The Exam Timetable and Room Allocation System works well. Examination scheduling is something that academic institutions have to do. The Genetic Algorithm helps make the scheduling process better. It makes sure that the Exam Timetable and Room Allocation System schedules exams properly. The Exam Timetable and Room Allocation System is good, at what it does. The system is efficient. It helps institutions to manage their resources. The automated system is an improvement, over procedures.

Introduction

The text discusses the challenge of creating accurate and conflict-free exam schedules in schools and universities. Manual scheduling is time-consuming and prone to errors such as overlapping exams, poor room allocation, and unfair exam spacing for students.

To solve this, the proposed system uses a Genetic Algorithm (GA), a computer-based optimization technique inspired by evolution. The system takes inputs like student enrollments, available rooms, and time slots, and automatically generates a fair and efficient exam timetable that avoids conflicts and optimizes resource use.

The literature review shows that earlier approaches (like simulated annealing, tabu search, and basic GA models) had limitations such as poor scalability, lack of fairness, high computation time, and limited flexibility. Existing systems, often based on manual tools like spreadsheets, are inefficient and difficult to update.

The proposed GA-based system improves upon these by:

• Minimizing exam clashes and room capacity issues
• Ensuring fair distribution of exams
• Adapting to changes easily
• Automating the entire scheduling process

It works through steps such as initialization, fitness evaluation, selection, crossover, mutation, and termination to iteratively find the best timetable. The final schedule is presented through a user-friendly dashboard accessible to administrators, students, and invigilators.

Overall, the system provides a more efficient, flexible, and reliable solution for exam scheduling compared to traditional methods.

Conclusion

This paper is about a system that uses a Genetic Algorithm to make exam timetables and assign rooms for schools. The system obtains information from schools. Generates schedules that are equitable and satisfy all requirements of the schools. It does the job without errors. Utilizes rooms well about 88% of the time which is significantly better than happens when done by hand. The Genetic Algorithm was run for 500 generations to determine how effective the Genetic Algorithm was. The data demonstrates the Genetic Algorithm is quite efficient in obtaining solutions and does so quickly. There are things that can be done to make the Genetic Algorithm system better in the future. One thing to try is to use the Genetic Algorithm with search methods. This might help the Genetic Algorithm find answers faster when there is a lot of data from schools. Add a feature that automatically assigns people to watch the exams. Use the Genetic Algorithm with methods to improve it. Improve the Genetic Algorithm by using something called Reinforcement Learning to adjust its settings while the Genetic Algorithm is running. This could make the solutions the Genetic Algorithm finds better for schools. If the Genetic Algorithm system was available on the internet and could send notifications in time it would be easier for people to use the Genetic Algorithm system and would help them communicate better with schools. The Genetic Algorithm system is a solution to a problem that schools face, which is making exam timetables and assigning rooms. The results also show that the Genetic Algorithm system can handle the work of making exam timetables and assigning rooms for schools. The Genetic Algorithm system is good, at solving these problems for schools.

References

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Copyright

Copyright © 2026 Mrs. P. Sarala, Shaik Reena, Sesham Ravindra Babu, Mutyala Rakesh, Yarlagadda Sai Venkat, Remella Sai Sudha. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.