Course scheduling optimization using genetic algorithm and tabu search

Jurnal Teknologi dan Sistem Komputer

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Title Course scheduling optimization using genetic algorithm and tabu search
Optimasi proses penjadwalan mata kuliah menggunakan algoritme genetika dan pencarian tabu
 
Creator Amrulloh, Arif
Sela, Enny Itje
 
Subject optimization; courses scheduling; genetic algorithms; tabu search
optimasi; penjadwalan mata kuliah; algoritme genetika; pencarian tabu
 
Description Scheduling courses in higher education often face problems, such as the clashes of teachers' schedules, rooms, and students' schedules. This study proposes course scheduling optimization using genetic algorithms and taboo search. The genetic algorithm produces the best generation of chromosomes composed of lecturer, day, and hour genes. The Tabu search method is used for the lecture rooms division. Scheduling is carried out for the Informatics faculty with four study programs, 65 lecturers, 93 courses, 265 lecturer assignments, and 65 classes. The process of generating 265 schedules took 561 seconds without any scheduling clashes. The genetic algorithms and taboo searches can process quite many course schedules faster than the manual method.
Penjadwalan mata kuliah merupakan permasalahan yang sering terjadi pada perguruan tinggi, di antaranya adalah bentrok waktu mengajar dosen, ruangan dan kelas mahasiswa. Kajian ini mengusulkan optimasi penjadwalan mata kuliah menggunakan algoritme genetika dan pencarian tabu. Algoritme genetika berfungsi untuk menghasilkan generasi terbaik kromosom yang tersusun atas gen dosen, hari, dan jam. Pencarian tabu digunakan untuk pembagian ruang perkuliahan. Penjadwalan dilakukan di fakultas Informatika yang mempunyai empat program studi dengan 65 dosen, 93 mata kuliah, 265 penugasan dosen, dan 65 kelas. Proses pembangkitan 265 jadwal membutuhkan waktu selama 561 detik dan tidak ada bentrok yang terjadi. Kombinasi algoritme genetika dan pencarian tabu dapat memproses jadwal mata kuliah yang cukup banyak dengan lebih cepat daripada cara manual.
 
Publisher Departemen Teknik Komputer, Fakultas Teknik, Universitas Diponegoro
 
Date 2021-06-17
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier https://jtsiskom.undip.ac.id/article/view/14137
10.14710/jtsiskom.2021.14137
 
Source Jurnal Teknologi dan Sistem Komputer; Volume 9, Issue 3, Year 2021 (July 2021); 157-166
Jurnal Teknologi dan Sistem Komputer; Volume 9, Issue 3, Year 2021 (July 2021); 157-166
2338-0403
 
Language ind
 
Relation https://jtsiskom.undip.ac.id/article/view/14137/12696
https://jtsiskom.undip.ac.id/article/downloadSuppFile/14137/661
 
Rights Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
https://creativecommons.org/licenses/by-sa/4.0
 

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