A Quick Performance Assessment for Artificial Electric Field Algorithm
Oluwatayomi Rereloluwa Adegboye, Ezgi Deniz Ülker · 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) · 2022
There are several effective metaheuristic algorithms in this literature for solving complex problems from different fields. In this work, Artificial Electric Field Algorithm (AEFA) is compared with the state-of-art algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Harmony Search (HS) algorithms. The values are studied based on convergence at the global optimum and resilience in tracking shifting optimum value. To accomplish this purpose, a series of benchmark functions with static and dynamic properties are employed. The results show that AEFA performs well in both cases.