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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 : International Journal of Electrical and Computer Engineering

 1 
Best-worst northern goshawk optimizer: a new stochastic optimization method Kusuma, Purba Daru; Hasibuan, Faisal Candrasyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp7016-7026

Abstract

This study introduces a new metaheuristic method: the best-worst northern goshawk optimizer (BW-NGO). This algorithm is an enhanced version of the northern goshawk optimizer (NGO). Every BW-NGO iteration consists of four phases. First, each agent advances toward the best agent and away from the worst agent. Second, each agent moves relatively to the agent selected at random. Third, each agent conducts a local search. Fourth, each agent traces the space at random. The first three phases are mandatory, while the fourth phase is optional. Simulation is performed to assess the performance of BW-NGO. In this simulation, BW-NGO is confronted with four algorithms: particle swarm optimization (PSO), pelican optimization algorithm (POA), golden search optimizer (GSO), and northern goshawk optimizer (NGO). The result exhibits that BW-NGO discovers an acceptable solution for the 23 benchmark functions. BW-NGO is better than PSO, POA, GSO, and NGO in consecutively optimizing 22, 20, 15, and 11 functions. BW-NGO can discover the global optimal solution for three functions.
Half mirror algorithm: a metaheuristic that hybridizes swarm intelligence and evolution-based system Kusuma, Purba Daru; Hasibuan, Faisal Candrasyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3320-3331

Abstract

This paper promotes a new metaheuristic called the half mirror algorithm (HMA). As its name suggests, HMA offers a new kind of mirroring search. HMA is developed by hybridizing swarm intelligence and the evolution system. Swarm intelligence is adopted by constructing several autonomous agents called swarms. On the other hand, the evolution system is adopted using arithmetic crossover based on a particular reference called a mirror. Four mirrors are used in HMA: the best swarm member, a randomly selected swarm member, the central point of the space, and the corresponding swarm member. During the confrontative assessment, HMA is confronted with average and subtraction-based optimization (ASBO), total interaction algorithm (TIA), walrus optimization algorithm (WaOA), coati optimization algorithm (COA), and clouded leopard optimization (CLO). The result shows that HMA is superior to ASBO, TIA, WaOA, COA, and CLO in 20, 19, 19, 20, and 20 out of 23 functions, respectively. Moreover, HMA has found the global optimal of eight functions. It means the superiority of HMA occurs in almost entire functions. In the future, the mirroring search can be combined with the guided and neighborhood search to construct a more powerful metaheuristic.
Swarm flip-crossover algorithm: a new swarm-based metaheuristic enriched with a crossover strategy Kusuma, Purba Daru; Hasibuan, Faisal Candrasyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp2145-2155

Abstract

A new swarm-based metaheuristic that is also enriched with the crossover technique called swarm flip-crossover algorithm (SFCA) is introduced in this work. SFCA uses swarm intelligence as its primary technique and the crossover as its secondary one. It consists of three searches in every iteration. The swarm member walks toward the best member as the first search. The central point of the swarm becomes the target in the second search. There are two walks in the second search. The first walk is getting closer to the target, while the second is avoiding the target. The better result between these two walks becomes the candidate for the replacement. In the third search, the swarm member performs balance arithmetic crossover with the central point of the space or jumps to the opposite location within the area (flipping). The assessment is taken by confronting SFCA with five new metaheuristics: slime mold algorithm (SMA), golden search optimization (GSO), osprey optimization algorithm (OOA), coati optimization algorithm (COA), and walrus optimization algorithm (WaOA) in handling the set of 23 functions. The result shows that SFCA performs consecutively better than SMA, GSO, OOA, COA, and WaOA in 20, 23, 17, 17, and 17 functions.
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