| Abstrakt: |
Educational institutions frequently struggle to develop a workable lecture/tutorial schedule in a major universitydepartment. In this study, an evolutionary algorithm (EA)-based method is used to resolve the university scheduling problem. Throughout the process, a chromosomal representation tailored to the task is used. In order to generate workable timetables in a fair amount of computation time, heuristics and context-based reasoning have been applied. The strategy used to accelerate convergence is clever adaptive mutation. Real data from a large university has been used to validate, test, and debate the whole course scheduling system mentioned in this paper. Higher education institutions are currently concerned about students' attendance patterns. For the faculty to construct schedules automatically, a computer-based automatic timetable generator system is required. Our ideas for the "Automatic Time Table System," which consists of many applications, have been laid out. The application's timetable generation feature helps you save time. The system's automated Excel spreadsheet is utilized to maintain a record of the teachers' availability and scheduling. Our students will find this system helpful in the twenty-first century. It takes a lot of time and labor for educational staff in universities with huge student numbers to manually create a schedule. Due to this, it commonly happens that the same professor will give numerous lectures or competing classes. Automatically generating test and class schedules will be made simpler by the availability of a timetable generator. It will be produced by the system automatically, which will also help you save time. It prevents having to manually set up and manage a schedule. The purpose of this project is to develop a simple, functional, and user-friendly application that will facilitate the construction and distribution of schedules. The genetic algorithm is themain technique used to make schedules. It helps in the development of the ideal schedule by regulating all the rules. Conflicts in scheduling are not an issue for the faculty. With inputs such teacher name, data for the rooms, labs, and subject, this system will have a user-friendly, interactive, and less complicated interface. To store all the data entered as input, the system will have a carefully constructed database. The system will have an algorithm that manages all of the database's data while taking into account both hard and soft constraints. a timetable generation technique that seeks out the optimal solution using genetic algorithms. Instead of requiring time-consuming documents, the staff and students can easily view the timetable. [ABSTRACT FROM AUTHOR] |
