Kısıtlı optimizasyon problemlerinin çözümü için atom arama optimizasyon algoritması

Year 2019, , 841 - 851, 29.09.2019

Erdal Eker , Murat Kayri , Serdar Ekinci

https://doi.org/10.24012/dumf.540402

Cited By: 1

Abstract

Son
yıllarda evrim, fizik, matematik ve sürü ilhamlı çok sayıdaki sezgisel-üstü
optimizasyon teknikleri, bilim ve mühendislik alanlarına önerildi. Atom arama
optimizasyonu (ASO), temel moleküler dinamiklerden esinlenen popülasyon tabanlı
yeni bir optimizasyon algoritmasıdır. ASO, basitliği ve az sayıda kontrol
parametresi sayesinde optimizasyon problemlerine kolaylıkla uygulanabilir. ASO,
en çok bilinen sekiz test fonksiyonuna (Sphere, Rosenbrock, Step, Schwefel,
Rastrigin, Ackley, Griewank ve Egg Crate) uygulandı. Ayrıca, her test
fonksiyonu için ASO ile elde edilen istatistiksel sonuçlar (ortalama, standart
sapma ve en iyi değer) literatürdeki diğer algoritmalarla elde edilen
sonuçlarla karşılaştırıldı. Parçacık sürüsü optimizasyonu (PSO), yapay arı
kolonisi (ABC) ve sinüs kosinüs algoritması (SCA) karşılaştırma için seçilen diğer
metotlardır. Tüm test fonksiyonları için elde edilen istatistiksel sonuçlar ve
yakınsama hızlarına bakıldığında, ASO algoritmasının kısıtlı optimizasyon
problemlerini çözmedeki üstün performansı göze çarpmaktadır.  

Keywords

Atom arama optimizasyonu, sezgisel-üstü, optimizasyon, test fonksiyonları

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