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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Charity : Jurnal Pengabdian Masyarakat E-JOINT (Electronica and Electrical Journal Of Innovation Technology) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Almufi Jurnal Pengabdian kepada Masyarakat eProceedings of Engineering Electrician : Jurnal Rekayasa dan Teknologi Elektro Journal of Computer Engineering: Progress, Application and Technology Jurnal Abdimas
Faisal Candrasyah Hasibuan
Universitas Telkom
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : Bulletin of Electrical Engineering and Informatics

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Random-guided optimizer: a metaheuristic that shifts random search to guided search through iteration Kusuma, Purba Daru; Hasibuan, Faisal Candrasyah
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6507

Abstract

This study offers a new swarm-based metaheuristic: random-guided optimizer (RGO). RGO has novel mechanics in shifting the random motion into a guided motion strategy during the iteration. In RGO, the iteration is divided into three equal size phases. In the first phase, the unit walks randomly inside the search space to tackle the local optimal problem earlier. In the second phase, each unit uses a unit selected randomly among the population as a reference in conducting the guided motion. In the third phase, each unit conducts guided motion toward or surpasses the best unit. Through simulation, RGO successfully finds the acceptable solution for 23 benchmark functions. Moreover, RGO successfully finds the global optimal solution for four functions: Branin, Goldstein-Price, Six Hump Camel, and Schwefel 2.22. RGO also outperforms slime mold algorithm (SMA), pelican optimization algorithm (POA), golden search optimizer (GSO), and northern goshawk optimizer (NGO) in solving 12, 20, 12, and 1 function consecutively. In the future, improvement can be made by transforming RGO into solid multiple-phase strategy without losing its identity as a metaheuristic with multiple strategy in every iteration.
Co-Authors Alfarrelwijaya, Dheandra Alfian, Devid Andreson, Enrico Andri Ulus Rahayu ANGGUNMEKA LUHUR PRASASTI Athallah, Raken Putra Bhaskara, Komang Jaya Bobby, Syahdika Budhi Irawan Daffa Ahmadhan Khusumah David, Axel Dhesvira Nurseha Putri Doan Perdana Fajri, Farhan Ulil Fakhrezi, Alfian Fathoni Waseso Jati Fathoni waseso jati Gantoro, Rasyid Abdi Hady , Muhammad Jibran Hariwidjaja, Valrama Wardhana Hartono, Aditya Firmansyah Herlambang, Yohanes Yogas Ivan Rinaldhy Saputra jati, Fathoni waseso Khusumah, Daffa Ahmadhan Komang Jaya Bhaskara Komang Jaya Bhaskara Mahatya Kusumo, Atallah Satrio L., Kemas Muslim Luthfi, Zaidan Mahaasin, Habib Irfan Mahatya, Komang Jaya Bhaskara Mahendra, Dimas Putra Mertu, Aidi Meta Kallista Muhammad Rafindha Aslam Novianty, Astri Nugroho, Aditya Bakti Nur, Alan Rezky Dwiputra Nur’ilham, Muhammad Fauzan Pamungkas, Fajar Triaji Prasetyo, Aldy Putra Purba Daru Kusuma Rahadyan , Rizkita Ilham Rahman, Muhammad Syaiful Randy Erfa Saputra Rifqi Muhammad Fikri Ruslan, Ramah Rinaldi Sakri, Annisa Aprilia Putri Setiady, R Rogers Dwiputra Shiddieqy, Hasbi Ash Silalahi, Panji Christoper Sulaeman, Ikhsar Taufiq, Hans Harison Titipan, Muhammad Raga Widodo, Muhammad Faiz Anindyo