Performance Improvement of Genetic Algorithm Based Exam Seating Solution by Parameter Optimization

Exam seat allocation becomes a complex problem concerning the increasing number of students, subjects, exams, departments, and rooms in higher institution. The requirements constraints this demonstrate similar characteristics to extensively researched exam timetabling problems. They are planning limited capacity effectively efficiently. Additionally, seating requires arrangement reduce cheating incidents. In literature, several genetic algorithm-based methods were recommended prevent students that have friendship from sitting close during exams while providing best session arrangement. We improved performance algorithm by parameter optimization new elitism method increase saturation rate accuracy. has been tested on real-world data set represents high potential for realization high-quality compatible with real world.