Henry Gas Solubility Optimization Algorithm: A Systematic Review of Its Variants and Applications

Henry Gas Solubility Optimizer (HGSO) is a new metaheuristic algorithm which has attracted many researchers due to its supremacy, outstanding results, and its best convergence when applied to several real-world optimization applications. Thanks to much interest from researchers, several variants of HGSO have been proposed and applied in tackling numerous optimization areas in diverse domains. Consequently, this work intends to provide a comprehensive review and analysis of various studies reported in literature concerning HGSO variants. Different applications of HGSO variants are also reviewed. Our methodology is based on identifying and selecting 118 HGSO-related papers from various recognized journals. The HGSO algorithm was examined, and its merits and drawbacks were analyzed. In this study, the performance of the HGSO and its variants has been tested on the benchmark test functions regards to various assessment criteria including convergence behavior, Friedman test, mean absolute error (MAE) test, overall effectiveness test, performance index (PI) analysis and execution time analysis. According to the results, the HHO-HGSO exhibits better convergence behaviors in most of the cases for the dimensions 10, 30, 50 and 100. The Friedman test results show that the HHO-HGSO records the first rank in 30, 50 and 100 dimensions, whilst the MVQIHGSO gets the first rank in 10 dimension. Likewise, the HHO-HGSO attains better MAE test results in 30, 50 and 100 dimensions, whereas the MVQIHGSO surpasses its counterparts in 10 dimension for MAE test results. The comparison demonstrate that the HHO-HGSO accomplishes an overall effectiveness of 71.552% which is the best amidst the HGSO variants. The HHO-HGSO also achieves better PI values in most of the cases. Besides, the simulation results reveals that based on the computational time, the QHGSO is the most rapid algorithm in terms of tackling all the benchmark test functions. Lastly, some future works for the HGSO variants are recommended.