What type of study is this?

This is a Experimental Study study.

September 23, 2025Open Access

An Optimized Machine Learning Model for Automating Academic Scheduling

BGBrinda GaneshUniversity of Maryland, College Park PGPatricia GeorgeAmerican University of Antigua HMH P Muruli

Key Points

The optimized model automates academic scheduling, leading to more accurate timetables and fewer human errors.
Utilizing a genetic algorithm resulted in significant time savings in the timetable development process.
Traditional scheduling methods require extensive manual work, often leading to inefficiencies and errors.
The integration of machine learning simplifies the scheduling process for schools and colleges, enhancing overall productivity.

Abstract

Timetable development is a complex and lengthy task that might require lots of effort and attention to the details. Timetables can be useful in many ways such as planning academic programs in schools & colleges, establishing study timetables and transport timetables. Conventional procedures to develop timetables take much manual work and do not work without errors. The problem of incompatibility is overcome in this paper by employing a Genetic Algorithm (GA) in timetable design. With the application of GA, it is possible to make accurate and efficient schedules and to make minimum human errors and save time which is taken in the process.

Ask AI

Helpful

Bookmark

View Full Paper