Abstract: Automated Timetable Generators (ATGs) have emerged as essential tools in educational institutions to simplify scheduling and resource allocation. These systems replace manual planning with intelligent, algorithm-driven scheduling that minimizes human error and resource conflicts. This paper surveys the current technologies, algorithms, and challenges in automated timetable systems. It explores various approaches, from rule-based systems to AI-powered models, and identifies gaps in existing solutions such as scalability, user flexibility, and real-time conflict resolution. The survey aims to guide future enhancements for adaptive, scalable, and institution-friendly timetable solutions.
Keywords: Timetable Generator, Conflict Detection, Scheduling Algorithms, Educational Technology, Automation.
|
DOI:
10.17148/IJARCCE.2025.14540
