Journal of Bionic Engineering ›› 2024, Vol. 21 ›› Issue (1): 374-408.doi: 10.1007/s42235-023-00437-8
Geyser Inspired Algorithm: A New Geological‑inspired Meta‑heuristic for Real‑parameter and Constrained Engineering Optimization
Mojtaba Ghasemi1； Mohsen Zare2； Amir Zahedi3； Mohammad‑Amin Akbari4； Seyedali Mirjalili5,6 Laith Abualigah7,8,9,10
- 1 Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran 2 Department of Electrical Engineering, Faculty of Engineering, Jahrom University, Jahrom, Fras, Iran 3 Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran 4 Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus 5 Centre for Artifcial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, QLD 4006, Australia 6 University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary 7 Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon 8 Hourani Center for Applied Scientifc Research, Al-Ahliyya Amman University, Amman 19328, Jordan 9 MEU Research Unit, Middle East University, Amman 11831, Jordan 10 Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan
Geyser Inspired Algorithm: A New Geological‑inspired Meta‑heuristic for Real‑parameter and Constrained Engineering Optimization
Mojtaba Ghasemi1； Mohsen Zare2； Amir Zahedi3； Mohammad‑Amin Akbari4； Seyedali Mirjalili5,6 Laith Abualigah7,8,9,10
- 1 Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran 2 Department of Electrical Engineering, Faculty of Engineering, Jahrom University, Jahrom, Fras, Iran 3 Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran 4 Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus 5 Centre for Artifcial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, QLD 4006, Australia 6 University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary 7 Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon 8 Hourani Center for Applied Scientifc Research, Al-Ahliyya Amman University, Amman 19328, Jordan 9 MEU Research Unit, Middle East University, Amman 11831, Jordan 10 Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan
摘要： Over the past years, many eforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a new optimization method based on an unusual geological phenomenon in nature, named Geyser inspired Algorithm (GEA). The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process. The efciency and accuracy of GEA are verifed using statistical examination and convergence rate comparison on numerous CEC 2005, CEC 2014, CEC 2017, and real-parameter benchmark functions. Moreover, GEA has been applied to several real-parameter engineering optimization problems to evaluate its efectiveness. In addition, to demonstrate the applicability and robustness of GEA, a comprehensive investigation is performed for a fair comparison with other standard optimization methods. The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known natureinspired algorithms, including ABC, BBO, PSO, and RCGA. Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.