Optimasi Penjadwalan Mata Pelajaran pada Kurikulum 2013 dengan menggunakan Hibridisasi Algoritme Genetika dan Simulated Annealing (Studi Kasus: SMA Negeri 6 Surabaya) - Priscillia Vinda Gunawan; Imam Cholissodin; Bayu Rahayudi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Scheduling is one of the computational problems that is not easily solved. For solving it must be prepared systematically, by maximizing resources and time available effectively and efficiently. Scheduling problems can occur in various fields, including education. SMA Negeri 6 Surabaya is one of the high schools in Surabaya that has problems finding the right time slot with a limited number of teachers and there are some constraints that must be met in the scheduling of subjects. One method that can be used in the scheduling of subjects is to use genetic algorithm hybridization and simulated annealing (GA-SA) because GA has the weakness of early convergence and possibly stuck in local optimum, then SA is given as a solution to cover the weakness of GA and able to survive on a local optimum. The algorithm hybridization process is done with the first step in GA using chromosome representation of integer numbers, one-cut point crossover, reciprocal exchange mutation, and elitism selection. In the second step, a simulated annealing process is done using neighborhood move. The results given are scheduling the subjects by meeting the existing constraints. Based on the research, the optimum parameters are the number of generation 270, the population 90, the combination of cr and mr are 0.3 and 0.7 with the average fitness value of 0.999000.