Güncel metasezgisel optimizasyon algoritmalarının CEC2020 test fonksiyonları ile karşılaştırılması

Yıl 2021, Cilt: 12 Sayı: 5, 729 - 741, 31.12.2021

Elif Varol Altay Osman Altay

https://doi.org/10.24012/dumf.1051338

Cited By: 4

Öz

Son yıllarda karmaşık, çok modlu, yüksek boyutlu ve doğrusal olmayan arama ve optimizasyon problemleri için birçok metasezgisel optimizasyon algoritması önerilmiştir. Doğada yer alan canlıların sürü davranışları, bitkilerin davranış biçimleri, insanların sosyal davranışları, matematiksel, fiziksel, kimyasal, biyolojik yasalar ve kurallardan ilham alan çok sayıda metasezgisel optimizasyon algoritması bulunmaktadır. Bu algoritmalar bazı problemlerde başarı ile sonuç üretirken bazı problemlerde yeterince başarılı sonuç üretememektedir. Önerilen bu algoritmaların performansları problemin yapısına göre değişiklik göstermektedir. Araştırmacılar da bundan dolayı her geçen gün yeni yöntemler önermektedir. Bu çalışmada son zamanlarda ortaya çıkan Cıvık Mantar Optimizasyon Algoritması, Balina Optimizasyon Algoritması, Gri Kurt Optimizasyonu, Harris Şahin Optimizasyonu ve Arşimet Optimizasyon Algoritması tanıtılmış ve bu yöntemlerin performansları 10 adet unimodal, multimodal, hibrit ve composition fonksiyonlarını içeren CEC2020 test fonksiyonlarında karşılaştırılmıştır.

Anahtar Kelimeler

Metasezgisel yöntemler, kalite test fonksiyonları, global optimizasyon

Kaynakça

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