Optimizing Class Scheduling: A Genetic Algorithm Approach for Smart Scheduling and Builder System

Developing a timetable takes a lot of effort and time from educators. To reduce the challenges encountered while creating a timetable, several methods are employed, including genetic, heuristic, and resource scheduling. Several strategies are used in these algorithms with the goal of increasing the search operation's cooperation. The goal of this research is to develop an ideal time management system to deal with this problem. The suggested system will accept a variety of inputs, such as topics, faculty members, work load, period, etc., and based on these inputs, it will build feasible timetables. Thus, an application-based architecture is ultimately provided as a GA-based solution to flexible timetabling issues in educational establishments. In comparison to the conventional method, this study advances the field of computerized systems for timetable execution in terms of clashes between courses and instructor availability, resource utilization, and stakeholder satisfaction.