Final assignment exam scheduling optimization using genetic algorithms with tournament selection techniques and violated directed mutation (VDM)

Abstract

Scheduling the final assignment exam is an important process that requires careful planning to ensure smooth implementation for each student. This process involves the stages of archiving final assignment submission files, determining supervisors and examiners, as well as preparing seminar and trial schedules. However, obstacles that often arise include conflicting schedules, long execution times, and low fitness values. To overcome this problem, the genetic algorithm approach is used to optimize scheduling. This algorithm can handle complex problems with a wide search space, although it has weaknesses in selecting appropriate parameters and the time required to reach the optimal solution. Genetic algorithm optimization techniques such as violated directed mutation (VDM) and tournament selection are used in this research. Previous research shows that VDM provides better results than other methods, while tournament selection improves the desired solution. It is hoped that the use of genetic algorithms with VDM and tournament selection will overcome the problem of conflicting schedules and increase the execution speed in final project exam scheduling.