Akademik Veri Yönetim Sistemi
3rd International Congress of Electrical and Computer Engineering, ICECENG 2024, Bandirma, Türkiye, 27 - 30 Kasım 2024, ss.429-444, (Tam Metin Bildiri)
Optimization has become a critical term in many fields today. This direction has made considerable progress due to the rise of metaheuristic optimization algorithms meant primarily toward solving many intractable issues. The sources of inspiration for these algorithms are quite diverse, with ones based on mathematical, physical, biological, and chemical laws, the behavior of animals, the growth of plants, the movement of water, and even people being developed. However, not all algorithms are optimal for every problem. The task’s complexity and essence determine this variability in performance. Therefore, there is a constant proposal of new algorithms and comparison of their performance. Contextual studies have examined recently introduced algorithms such as the hippopotamus optimization algorithm, the Newton–Raphson-based optimizer, and the golf optimization algorithm, among others, within 33 sets of quality control tests. These tests provide a strong diet of the necessary data for a better definition of the efficiency and performance one expects from the algorithms. Nonparametric Friedman and Wilcoxon tests were applied to compare the results more accurately. The results indicate that the hippopotamus optimization algorithm strategy performed better than the remaining strategies in all three challenges.