Design And Development of a Web-Based Course Scheduling Information System Using a Genetic Algorithm Implementation

Purpose:This study develops a web-based course timetabling system using a genetic algorithm and evaluates the algorithm configuration and system functionality.Methodology:The research adopts Design Science Research and Waterfall software development. Tests covered 817 courses from 18 programs, five parameter scenarios, 498 unit tests, and 14 black-box scenarios.Findings:A population of 50, crossover rate of 0.8, and mutation rate of 0.01 achieved feasible schedules in all repeated tests across the three program sizes. All 14 black-box scenarios produced the expected results.Implications:The system supports prototype academic scheduling across study programs, although some testing attributes were synthetic and operational validation is still needed.