Scopus
YÖKSİS DOI Eşleşti
SJR Q1
A Comprehensive Survey of Henry Gas Solubility Optimization Algorithm with its Theory, Variants, and Applications
Archives of Computational Methods in Engineering · Ocak 2026
YÖKSİS Kayıtları
A Comprehensive Survey of Henry Gas Solubility Optimization Algorithm with its Theory, Variants, and Applications
Archives of Computational Methods in Engineering · 2026 SCI-Expanded
Arş. Gör. MUSA DOĞAN →
A Comprehensive Survey of Henry Gas Solubility Optimization Algorithm with its Theory, Variants, and Applications
Archives of Computational Methods in Engineering · 2025 SCI-Expanded
Doç. Dr. MURAT KÖKLÜ →
Makale Bilgileri
ISSN11343060
Yayın TarihiOcak 2026
Cilt / Sayfa33 · 81-138
Scopus ID2-s2.0-105010444640
Özet
Henry Gas Solubility Optimization (HGSO) algorithm is a well-known physics-based nature-inspired optimization algorithm inspired by the behavior of Henry’s law. The HGSO algorithm, developed by Hashim et al. in 2019, has attracted significant interest from scientists and researchers. It has been widely applied to solve various optimization problems in different fields due to its unique structure, simplicity, easiness of implementation, and reasonable execution time. This paper explores and examines over 200 previous existing research on the HGSO algorithm covering its advancements, enhanced variants (multi-objective, hybridized, and modified), and a wide range of real-world applications such as intrusion detection, wireless sensor networks, optimal parameters control, photovoltaic systems, image processing, and feature selection. Additionally, The performance of the HGSO algorithm is assessed using 23 IEEE CEC benchmark functions in comparison with 14 well-regarded optimization meta-heuristics published in the literature. Furthermore, the results of the HGSO algorithm are compared with some of its key variants. The survey also provides a critical evaluation of HGSO’s convergence behavior, highlighting its strengths and limitations. Finally, the paper concludes with some potential directions for future work. The insights gained from this survey offer valuable guidance for researchers aiming to apply or enhance the HGSO algorithm in a wide range of optimization problems.
Yazarlar (9)
1
Amylia Ait Saadi
2
Sylia Mekhmoukh Taleb
3
Selma Yahia
4
Musa Dogan
5
Elham Tahsin Yasin
ORCID: 0000-0003-3246-6000
6
Yassine Meraihi
7
Murat Koklu
ORCID: 0000-0002-2737-2360
8
Seyedali Mirjalili
ORCID: 0000-0003-3246-6000
9
Amar Ramdane-Cherif
Kurumlar
ESME
Paris France
Laboratoire d'Ingénierie des Systèmes de Versailles
Velizy-Villacoublay France
Obuda University
Budapest Hungary
Selçuk Üniversitesi
Selçuklu Turkey
Torrens University Australia
Adelaide Australia
Université de Boumerdes
Boumerdes Algeria
VSB – Technical University of Ostrava
Ostrava Czech Republic
Son Atıflar
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Archives of Computational Methods in Engineering
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· 2025 · DOI
Scimago Dergi (ISSN Eşleşmesi)
Archives of Computational Methods in Engineering
Q1
SJR Skoru2,415
H-Index129
YayıncıSpringer Netherlands
ÜlkeNetherlands
Applied Mathematics (Q1)
Computer Science Applications (Q1)
Metrikler
2
Atıf
9
Yazar