Multi-Objective Optimization For Proportional Tuition Fees Assessment Using Non-Dominated Sorting Genetic Algorithm II (NSGA II)

Proportional tuition fees assessment (in Indonesian language called Uang Kuliah Tunggal in abbreviated UKT) is multi-objective optimization problem. The objectives are minimizing distance between UKT's price and the financial ability of the student, and maximizing university's income. The constraints are total of student's UKT price does not below the projection about minimum faculty's income, and constraint from the minister that number of student in category I and II is 5% per study program. The optimization was done by non-dominated sorting genetic algorithm II (NSGA II). The method that we proposed succeed to optimize the UKT's assessment problem. The evaluation shows that for 100 student data, the best result occurred when the number of population is 1000 or more, maximum iteration is 150, and uniform crossover and random exchange mutation is the best genetic operator with Cr 0.9 and Mr 0.1.