Vol.9, No.1, February 2020.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science


A Custom-based Crossover Technique in Genetic Algorithm for Course Scheduling Problem


Ni Gusti Ayu Harry Saptarini, Putu Indah Ciptayani, Ida Bagus Irawan Purnama


© 2020 Putu Indah Ciptayani, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 1, Pages 386‐392, ISSN 2217-8309, DOI: 10.18421/TEM91-53, February 2020.


Received: 16 November 2019.

Revised:   29 January 2020.
Accepted:  05 February 2020.
Published: 28 February 2020.




Genetic algorithm is widely used in scheduling, which crossover is one of the important operators. This paper aims to propose a custom crossover technique in genetic algorithm to solve the course scheduling problem. This technique proposes only one offspring on each crossover by choosing the best gene from each parent. The result shows that the proposed technique can be applied to solve the scheduling problem which is better compared to the one-point and two-point crossover with the best fitness value 0.0049. Its best fitness after the convergence state is more stable than two other techniques.


Keywords –combinatoric problem, course scheduling, custom crossover, genetic algorithm, timetable.



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