Optimizing Class Scheduling for the University of Northern Philippines Using Greedy Algorithm

Manual class scheduling at the University of Northern Philippines (UNP) is characterized by inefficiencies, frequent conflicts, and delays, negatively impacting faculty and students. This research explores the development of an automated class scheduling system utilizing the greedy algorithm to address these challenges. The developed system used Agile Methodology to ensure the iterative progress and adaptability, that will allow for ongoing refinements based on the user feedback. The study evaluates current scheduling practices, identifies the appropriate technologies for automation, and designs a web-based application to minimize conflicts and optimize resource allocation. The system uses a greedy algorithm to make locally optimal decisions for globally efficient scheduling. The proposed solution will enhance scheduling accuracy, reduce manual effort, and improve operational efficiency meeting user needs. The proposed system will also manage the conflicts of schedules of the different inputs by its conflict detection and resolution functionality. The research highlights the potential benefits of automated systems in educational settings and offers recommendations for successful implementation.