A Comprehensive Survey Inspired by Elephant Optimization Algorithms: Comprehensive Analysis, Scrutinizing Analysis, and Future Research Directions

ABSTRACT

Complex optimization problems require advanced approaches such as metaheuristic algorithms due to features such as an ample search space, unevenness of the objective function, nonlinear dependence, uncertainty, and multi-objectives. Inspired by nature or social processes, these algorithms effectively solve NP-hard problems and heavy computations. Due to their flexibility and adaptability to various conditions, these algorithms are powerful tools for addressing modern optimization challenges. This paper comprehensively reviews the Elephant Herding Optimization (EHO) and Elephant Clan Optimization (ECO) algorithms from 2021 to 2025. The ECO is one of the newest metaheuristic algorithms invented in 2021, inspired by the life of elephants, to solve optimization problems. Of course, the basic version of this algorithm was invented in 2015 under the name EHO. Therefore, this analysis is based on a comprehensive classification into four categories (hybridization, modified, variants, and applications), including an assessment of the strengths, limitations, and applications of the EHO in various scientific and engineering fields. The references for this article are from 10 international and reference publishers. The most frequently reviewed references belong to Springer (29%), Elsevier (27%), and Wiley (12%). The results of this study show that the EHO algorithm has been most widely applied in the fields of engineering, computer science, and industry.