DOI: https://doi.org/10.21456/vol6iss2pp133-143

Metode Simulated Annealing untuk Optimasi Penjadwalan Perkuliahan Perguruan Tinggi

*Wiktasari Sari  -  Universitas Islam Sultan Agung, Indonesia
Jatmiko Endro Suseno  -  Universitas Islam Sultan Agung
Open Access Copyright (c) 2016 JURNAL SISTEM INFORMASI BISNIS

Citation Format:
Abstract

Course scheduling an assignment of courses and lecturers in the available time slots involving certain restrictions. Simulated annealing is a heuristic method can be used as search method and provide acceptable solutions with good results. The research aims to make scheduling courses at the college using simulated annealing using five variables data that lecturer courses, the time slot is comprised of the day and the time period and class room. The research has two objective functions to be generated, the first is the assignment of a lecturer on courses that will be of teaching, second lecturers and their assignment course on the time slot and the room available. The objective function is calculated by taking into account the restrictions involved to produce the optimal solution. The validation is performed by testing to simulated annealing method with an varian average of 77.791% of the data variance can reach a solution with a standard deviation of 3.931509. In this research given the method of solution in the use of the remaining search space to be reused by the data that is unallocated.

Note: This article has supplementary file(s).

Fulltext View|Download |  Research Results
Metode Simulated Annealing untuk Optimasi Penjadwalan Perkuliahan Perguruan Tinggi
Subject
Type Research Results
  Download (1MB)    Indexing metadata
Keywords: Scheduling; Timetabling; Simulated annealing; Heuristic; Objective function; Constraint

Article Metrics:

Article Info
Section: Research Articles
Language : EN
Recent articles
Metode Simulated Annealing untuk Optimasi Penjadwalan Perkuliahan Perguruan Tinggi Algoritma K-Means Clustering Untuk Pengelompokan Ayat Al Quran Pada Terjemahan Bahasa Indonesia Evaluasi Kinerja Organisasi Publik Dengan Menggunakan Pendekatan Balanced Scorecard dan Analytic Network Process Penerapan Green Supply Chain Management Untuk Peningkatan Kinerja Keuangan Perusahaan More recent articles
Most cited articles
Metode Jaringan Syaraf Tiruan Untuk Prediksi Performa Mahasiswa Pada Pembelajaran Berbasis Problem Based Learning (PBL) Penerapan Model Human Computer Interaction (HCI) Dalam Analisis Sistem Informasi Sistem Informasi Geografis Berbasis Web untuk Pemetaan Sebaran Alumni Menggunakan Metode K-Means Sistem Pendukung Keputusan Penilaian Proposal Kegiatan PNPM MPd Menggunakan Metode Profile Matching dan Analytic Hierarchy Process (AHP) Kajian Data Mining Customer Relationship Management pada Lembaga Keuangan Mikro More cited articles
  1. Babei, H., Karimpour, J., Hadidi, A., 2015. A survey of approaches for university course timetabling problem, Computers & Industrial Engineering 86, 43–59
  2. Basir, N., Ismail, W., Norwawi,. 2013. A Simulated Annealing for Tahmidi course Timetabling, Procedia Technology 11, 437 – 445
  3. Cacchiani, V., Caprara, A., Roberti, R., Toth, R., 2013. A new lower bound for curriculum-based course timetabling, Computers & Operations Research 40, 2466-2477
  4. Chamber, L.D., 1998. Practical Handbook of Genetic Algorithms: Complex Coding Systems, Volume 3, New York: CRC Press
  5. Chibante, R., 2010. Simulated Annealing Theory with Applications, Rijeka: Sciyo
  6. Daskalaki, S., Birbas, T., Housos, E., 2004. An integer programming formulation for a case study in university timetabling, European Journal of Operational Research 153, 117–135
  7. Fong, C.W., Asmuni, H., McCollum, B., McMullan, P., Omatu, S., 2014. A new hybrid imperialist swarm-based optimization algorithm for university timetabling problems, Information Sciences 283, 1–21
  8. Gunawan, A., Ng, K.M., Poh, K.L., 2012. A hybridized Lagrangian relaxation and simulated annealing method for the course timetabling problem, Computers& Operations Research 39, 3074–3088
  9. Kalivas, J.H., 1995. Adaption of simulated annealing to chemical optimization problems, Elsevier: Amsterdam
  10. Mu, C.H., Xie, J., Liu, Y., Chen, F., Liu, Y., Jiao, L.C., 2015. Memetic algorithm with simulated annealing strategy and tightnessgreedy optimization for community detection in networks, Applied Soft Computing 34, 485–501
  11. Yamit, Zulian. 2011. Manajemen Produksi & Operasi. Yogyakarta: Ekonisia

Last update:

  1. Optimizing Practical Room Scheduling Using Genetic Algorithms: A Timetabling Case Study at Telkom University

    Auliya Nur Pratama, Ekky Novriza Alam, Sinung Suakanto. 2024 4th International Conference on Electronic and Electrical Engineering and Intelligent System (ICE3IS), 2024. doi: 10.1109/ICE3IS62977.2024.10776011

Last update: 2025-07-26 16:11:35

No citation recorded.