OptiTime: AI-Powered Faculty Scheduler for Peak Productivity

In response to the inefficiencies and limitations of manual faculty scheduling systems at educational institutions, the author develops OptiTime, an AI-powered scheduler meant to increase productivity. Existing systems have time-consuming processes, human errors, and a need for adaptability to changing academic needs. OptiTime revolutionizes faculty scheduling using artificial intelligence, data-driven approaches, and robust algorithms. OptiTime adapts to dynamic academic environments by employing a thorough technique that includes data collecting, feature engineering, algorithm selection, model training, and dynamic scheduling with reinforcement learning and evolutionary algorithms. The results and analysis propose that it has a considerable impact, with gains in scheduling efficiency, conflict resolution, and teacher satisfaction over traditional techniques. OptiTime cuts overall scheduling time from 120 to 45 hours, conflicts from 25 to 5, and room utilization from 65% to 85%. The research highlights OptiTime's transformative role in resolving the constraints of manual scheduling systems by providing a highly advanced solution for optimal faculty scheduling in educational institutions.