Research pick: Like a flame to a moth - "Moth flame optimisation based timetabling tool for educational course timetabling"

Many algorithms have been inspired by natural behaviour, such as the foraging of ants, the swarming of bees, the flocking of birds, even the oceanic journeys of whales. Such algorithms stand on evolution’s shoulders to allow modern science to see further than it might with algorithms based on non-natural approaches. Researchers have now turned to the light-seeking behaviour of various species of nocturnal moth to help them solve an academic problem.

Putting together a university timetable, to schedule courses, lectures, and other academic activities, has long been one of higher education’s most intricate administrative challenges. The task requires balancing limited resources such as classrooms, laboratories, and the availability of instructors, as well as the students themselves. For large institutions, manually constructing an optimal timetable is often impractical, and even small errors can cascade into significant inefficiencies.

Research in the International Journal of Innovation and Learning has proposed a computational approach that could streamline this complex process. The study introduces an automated timetabling tool, AMFOT, which uses a discrete moth flame optimization (MFO) algorithm. MFO is a type of nature-inspired computational method, drawing on the navigational behaviour of nocturnal moths many of which will move towards a light source although rarely following a direct path. The algorithm seeks out the optimal solutions to complex problems in a similar way.

Specifically, the new algorithm seeks out solutions, the optimal timetable, that satisfies all the hard constraints, non-negotiable rules such as avoiding overlapping classes or double-booked resources, while also accommodating soft constraints, which are merely desirable outcomes, flexible preferences, such as minimizing the distance students must travel between classes.

The researchers then tested AMFOT using real-world scheduling scenarios from a local university. They were able to produce timetables that met the required constraints, and in many cases, they outperformed schedules produced by another computational method known as the crow search algorithm. The new algorithm takes into account student travel time and so not only boosts convenience and safety of students, but aligns with sustainability goals by promoting more efficient campus operations.

Kuntasup, M., Pongcharoen, P. and Thepphakorn, T. (2025) ‘Moth flame optimisation based timetabling tool for educational course timetabling’, Int. J. Innovation and Learning, Vol. 38, No. 3, pp.282–300.