Analysis Of Course Distribution Scheduling For Lecturers Using Genetic Algorithms And Constraint Satisfaction Methods At Batam University - Sony Putra; Muhammad Iqbal; Andysah Putera Utama Siahaan (SEAN Institute, 2024)
Optimal course scheduling is a significant challenge in university academic management, especially in allocating courses to lecturers efficiently. This study aims to analyze the application of Genetic Algorithm and Constraint Satisfaction Method in optimizing the scheduling of course distribution at Batam University. Genetic Algorithm is used to find the optimal solution through the evolution process, while the Constraint Satisfaction method is used to ensure that all scheduling constraints, such as the availability of lecturers, classrooms, and time, are met. This research method involves collecting data on course schedules, lecturer preferences, and classroom capacity. Furthermore, the implementation of the algorithm is carried out through computer simulations with population, mutation, and crossover parameters that are set to achieve the optimal solution. Based on the results of this study, the optimization achieved includes several important aspects. First, there were no schedule conflicts (zero conflicts) between courses, classrooms, and lecturers. Second, in terms of time efficiency, the automatic scheduling process runs faster than the manual method. Furthermore, the utilization of resources such as rooms and time has been used optimally, while the teaching load of lecturers is well distributed without any excess. Finally, constraint satisfaction has been achieved, where all constraints, such as no scheduling conflicts in space, lecturers, and time, have been successfully met.