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All Journal ASEAN Journal of Systems Engineering Majalah Forum Teknik UGM Jurnal Teknoin Seminar Nasional Aplikasi Teknologi Informasi (SNATI) J@TI (TEKNIK INDUSTRI) Jurnal Teknosains Journal of Indonesian Economy and Business Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Angkasa: Jurnal Ilmiah Bidang Teknologi International Journal of Supply Chain Management International Journal of Industrial Engineering and Engineering Management JURNAL TEKNIK INDUSTRI Prosiding Seminar Nasional Teknik Industri
Nur Aini Masruroh
Fakultas Teknik, Jurusan Teknik Mesin Dan Industri, Universitas Gadjah Mada Jl. Grafika 2, Kampus UGM, Yogyakarta 55281
Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Techniques for Improving Genetic Algorithms in Solving Operating Room Scheduling Problems: An Integrative Review Yuniartha, Deny Ratna; Normasari, Nur Mayke E.; Waluyo, Joko; Masruroh, Nur Aini; Herliansyah, Muhammad Kusumawan
International Journal of Industrial Engineering and Engineering Management Vol. 6 No. 1 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v6i1.8903

Abstract

Operating room scheduling is a complex process that involves various resources and takes the interests of many parties into consideration. The genetic algorithm is the frequently used metaheuristic algorithm to solve a large-size operating room scheduling problem. Many techniques have been developed to improve the genetic algorithms' performance in dealing with the operating room scheduling complexity. In this paper, we survey available literature to identify improvement techniques used at each stage of the genetic algorithm and capture the underlying problems. This review provides a mapping of improvement techniques in genetic algorithms correlating with the considered problems. The results can be employed by other researchers as a guide for future research in integrating a genetic algorithm or other population-based metaheuristic algorithm with a recent heuristic algorithm following the future directions of operating room scheduling research.
Co-Authors Anggita Virgiana Prasetyorini Anggita Virgiana Prasetyorini, Anggita Virgiana Anna Maria Sri Asih Annisa Dewi Akbari, Annisa Dewi Ari Ariangga Orranius Putra Patarru Aris Prasetiyo Asgar Ali Budi Hartono Deny Ratna Yuniartha Desy Wartati Dinda Safitri Ramadhani Dzakiyah Widyaningrum Hari Agung Yuniarto Indah Puspitasari Irwan Aufi Istikomah, Sintha Jecky, Jecky Joko Waluyo Joko Wintoko Kusnanto Kusnanto Miranda, Suci Mirwan Ushada Muhammad Kusumawan Herliansyah Niken Siwi Pamungkas Nur Mayke Eka Normasari Pramuditha, Zita Iga Putri Vicky Hapsari Rochim Bakti Cahyono Rony Arjuna Safira, Aretha Setiawan, Fran Setiawan, Fran Subagyo . Susana Evayanti Titis Wijayanto Trifandi Lasalewo Yang, Chao Lung Zita Iga Pramuditha