Harris hawks optimization: a comprehensive review of recent variants and applications

Harris hawks optimizer (HHO) has received widespread attention among researchers in terms of the performance, quality of results, and its acceptable convergence in dealing with different applications in real-world problems. This increased interest led to the emergence of many versions of HHO applied to various optimization problems in different fields. Therefore, this study aims to identify, retrieve, summarize, and analyze the critical studies related to the development of HHO. For this aim, we applied a review methodology. The applied methodology led to identified and selection of 69 related studies from different electronic sources. The review result revealed that although HHO algorithm is still in the infant stage, its superiority over several well-established metaheuristic algorithms in terms of speed and accuracy for addressing various benchmark problems and tackling several real-world optimization problems has been clearly observed. The HHO algorithm was evaluated, and its strengths and weaknesses were discussed. This review not only suggested possible future directions in this domain but also serves as a comprehensive source of information about HHO and HHO variants for future researchers due to the inclusion of charts and tabular comparison across a wide variety of attributes. A public website supports open access to this research and also source codes of the HHO in a different language and its supplementary materials at https://aliasgharheidari.com/HHO.html.

Automated summary

The Harris hawks optimizer (HHO) has shown superior performance compared to other metaheuristic algorithms in terms of speed and accuracy, despite being in its early stages. The review suggests potential future directions for research and serves as a comprehensive source of information on HHO and its variants.