Allocation Of Thesis Supervisor Using Genetic Algorithm

Ratna Dewi Hidayaturrachmah, syaiful anam

Abstract


Allocation of thesis supervisor is a way to determine the students’ thesis supervisor, so the students get the appropriate supervisor and the number of students guided by each supervisor does not exceed the maximum capacity. Allocation of thesis supervisor is not an easy taskbecause each supervisor has a capacity of the students that have to be guided and the supervisors major should be in accordance with the student's major in project.Allocation of thesis supervisor is an optimization problem that minimizes the number of mismatches between supervisor’s major and student’s project, and the number of supervisors whose guidance exceeds the maximum capacity.One of the methods that can be used to solve this problem is genetic algorithm.Genetic algorithm can solve optimization problems well on complex or even difficult mathematical models.The crossover operator is one of the operator that determines the success of the genetic algorithm.The commonly used crossover operator is the one cut point crossover operator, while after previous studies the position crossover operator is a crossover operator that developed to resolve the scheduling issues.Therefore, this research compares crossover position operator and the crossover one cut point operator to solve the problem of the thesis supervisor allocation. According to the results of the experiments, the genetic algorithm using crossover one cut point operators get better results in allocation of thesis supervisor rather than genetic algorithm with a position crossover operator.

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