Subject Scheduling Using Genetic Algorithms (Case Study: SMK Negeri 1 Labang-Madura-Indonesia)

Author:

Sari Rochman Eka Mala,Syakur Muhammad Ali,Imamah ,Rachmad Aeri

Abstract

Abstract The manually scheduling system is considered less effective and efficient because it requires a long time. Problems will become more complex if the number of components or data used is increasing. The schedule is expected not only not to experience clashes, but also to adjust to some limitations that must be met. Genetic Algorithm is one of the heuristic search algorithms that are very well used in solving optimization problems. The problem of scheduling genetic algorithms is considered to have good performance in finding the optimal solution. Genetic Algorithms implement an evolutionary process by randomly producing chromosomes from each population These chromosomes produce a solution to the problem raised, namely scheduling subjects. The conclusion of this study is to be able to arrange the schedule of subjects efficiently, by overcoming obstacles such as clashing schedules without eliminating the constraints that must be met.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference9 articles.

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3. Comparison Performance of Genetic Algorithm and Ant Colony Optimization in Course Scheduling Optimizing;Ahmad Ashari;Scientific Journal of Informatics,2016

4. Optimized Job Scheduling Approach based on Genetic Algorithms in Smart Grid Environment;Albalas;International Journal of Communication Networks and Information Security (IJCNIS),2017

5. A GENETIC ALGORITHM-BASED APPROACH FOR OPTIMIZATION OF SCHEDULING IN JOB SHOP ENVIRONMENT;Ritwik;Journal of Advanced Manufacturing Systems,2011

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