Kısıtlı optimizasyon problemlerinin çözümü için atom arama optimizasyon algoritması

Öz

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.  

Anahtar Kelimeler

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

Kaynakça

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