TimeTabler: A Software Framework for Automated Course Timetabling and Space Utilization Optimization in Resource-Constrained Institutions in Bangladesh

In universities around the world, the physical space where learning happens is often treated as a fixed resource, like a building that cannot be changed. Yet, the way that space is used is a dynamic puzzle. Administrators must fit hundreds of classes, thousands of students, and dozens of teachers into a limited number of rooms, all while ensuring that a chemistry lab is not used for a history lecture and that no teacher is scheduled to be in two places at once. This task, known as timetabling, is notoriously difficult. It is a problem of matching many moving parts against a rigid set of rules, a challenge that has long been solved by hand in many institutions. When done manually, the process is slow, prone to error, and often results in wasted space, where classrooms sit empty while other departments struggle to find a seat. In developing nations, where funding for new construction is scarce, the pressure to make the most of existing buildings is even more intense. The question facing educators is not just how to build more space, but how to organize the space they already have so that it works better for everyone.

A researcher at Shahjalal University of Science and Technology in Bangladesh has addressed this challenge by building a new kind of software tool called TimeTabler. Rather than simply proposing a new mathematical theory, the researcher created a practical, open-source computer program designed specifically for the people who manage university schedules. These administrators are often not experts in computer science, and they frequently work with older computers and without reliable internet connections. The software was built to run offline on standard desktop machines, requiring no special servers or expensive licenses. Its goal was to take the heavy lifting of scheduling away from human hands and replace it with an automated process that could find better solutions than manual methods ever could. The researcher tested this system at their own university, a setting with ten academic departments, thirty-five classrooms and laboratories, and fifty-six different groups of students.

The core of the system is an optimization engine that uses a method inspired by natural evolution, known as a genetic algorithm. Imagine a population of possible schedules, where each schedule is a complete weekly plan for the entire university. The computer generates many of these plans and then tests them against a long list of rules. Some rules are absolute, such as ensuring a teacher is never double-booked or that a student group fits into the room assigned to them. Other rules are about quality, such as avoiding scheduling classes for the same group on back-to-back days or ensuring that specialized rooms like laboratories are used for their intended purposes. The computer keeps the best-performing schedules, mixes their features together, and makes small random changes to create new, improved versions. It repeats this cycle hundreds of times, slowly evolving a set of schedules that satisfy all the strict rules while maximizing the use of available space.

When the researcher deployed TimeTabler at their university, the results showed a clear improvement over the previous manual system. Before the software was used, the university was utilizing its rooms about 52 percent of the time they were available. After the automated system generated a new schedule, that figure rose to nearly 59 percent. While this increase might seem modest, it represented a significant shift in how the university operated. More importantly, the software fixed a critical flaw in the manual process: the misuse of room types. In the old schedule, forty-seven courses were being held in rooms that were not suitable for them, such as regular lectures taking place in computer labs or auditoriums. The new system corrected every single one of these mismatches, ensuring that every class was held in the right kind of space. This change meant that specialized facilities were returned to their proper use, allowing the university to offer more laboratory-based courses without having to build new facilities.

The impact of these changes went beyond just filling rooms. By organizing the schedule more efficiently, the university was able to fit fourteen additional course sections into the same physical space. This is equivalent to adding two or three new classrooms without spending any money on construction. The software also transformed the daily work of the administrators. What used to take a team of people twelve to fifteen days of manual negotiation and spreadsheet editing was reduced to a few hours of data entry and about fifteen seconds of computer processing time for each student group. The administrators reported that the process felt fairer and more transparent, as the software applied the same rules to every department, removing the need for difficult, department-by-department arguments over who got the best rooms.

The researcher emphasizes that this success was not just about the power of the algorithm, but about the design of the tool itself. They built the software to be accessible, allowing non-technical staff to control the process and understand the trade-offs between different scheduling options. The system presented administrators with several high-quality schedule choices, each with clear metrics showing how well it performed, so they could make informed decisions based on their specific needs. This approach suggests that in resource-constrained environments, the barrier to better management is not a lack of advanced technology, but a lack of tools that are designed to fit the reality of the people using them. By bridging the gap between complex optimization theory and practical administrative work, TimeTabler demonstrates that significant improvements in efficiency and fairness can be achieved simply by organizing existing resources more intelligently.