Implementation of Hybrid Genetic Algorithm for Solving the Teacher Placement Problem

Ni Komang Ayu Wirayanti (1) , Haris Sriwindono (2)
(1) Informatics Department, Sanata Dharma University, Yogyakarta,, Indonesia , Indonesia
(2) Informatics Department, Sanata Dharma University, Yogyakarta, Indonesia , Indonesia

DOI:

https://doi.org/10.18535/sshj.v9i01.1460

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Issue
Vol. 9 No. 01 (2025)
Published
2025-01-02
Keywords:
    Hybrid Genetic Algorithm, Teacher Placement, Local Search
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Abstract

The teacher placement problem is a combinatorial problem that would take a very long time to solve in a deterministic way.  In this study, the problem will be solved using a hybrid genetic algorithm, which combines genetic algorithms with local search methods.   The genetic algorithm operators used include roulette wheel selection, two point crossover, and scramble mutation.  While the local search used is reverse, insert, and swap local search. The results showed that from the three experiments using hybrid genetic algorithms, it was found that hybrid genetic algorithms were more effective than ordinary genetic algorithms.  The use of hybrid genetic algorithm with swap local search technique produces the best total minimum distance (10099.09 km) at a mutation probability ratio of 1:250, number of chromosomes 10, and number of iterations 500. The hybrid genetic algorithm can improve the placement of teachers and is expected to contribute to improving the quality of education in Magelang district where the primary data is obtained.

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Authors

Ni Komang Ayu Wirayanti
Informatics Department, Sanata Dharma University, Yogyakarta,, Indonesia
Haris Sriwindono
Informatics Department, Sanata Dharma University, Yogyakarta, Indonesia
[1]
“Implementation of Hybrid Genetic Algorithm for Solving the Teacher Placement Problem”, Soc. sci. humanities j., vol. 9, no. 01, pp. 6341–6347, Jan. 2025, doi: 10.18535/sshj.v9i01.1460.