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DOĞRUSAL OLMAYAN OPTİMİZASYON PROBLEMLERİ İÇİN TAŞINIR ALGORİTMİK FONKSİYONLAR YÖNTEMİ

TRANSITIVE ALGORITHMIC FUNCTIONS METHOD FOR NONLINEAR OPTIMIZATION PROBLEMS

Journal Name:

  • Havacılık ve Uzay Teknolojileri Dergisi

Publication Year:

  • 2011

Key Words:

Keywords (Original Language):

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Abstract (2. Language): 
In this work, an equation is proposed to solve the general nonlinear continuous optimization problems. This equation can be used directly for obtaining analytical and numerical solutions. Since it can be transformed to some algorithmic functions through both analytically and numerically, this equation is named as the Transitive Algorithmic Functions (TAF) equation. The TAF equation can be applied to the optimization of general nonlinear continuous engineering problems. This equation presents alternative deterministic techniques and can define simple TAF algorithms which do not require derivative information as stochastic methods. Effectiveness of the equation and the proposed algorithms are demonstrated by their implementations.
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Abstract (Original Language): 
Bu çalışmada, sürekli gerçek sayılı fonksiyonların optimizasyon problemlerinin çözümüne yönelik olarak bir denklem önerilmiştir. Doğrudan analitik ya da sayısal çözümlere dönüşebildiği gibi, analitik veya sayısal yaklaşımla üretilebilecek yeni algoritma fonksiyonlarına da taşınabilen diferansiyel formdaki bu denklem, Taşınır Algoritmik Fonksiyonlar (TAF) Denklemi olarak isimlendirilmiştir. TAF denkleminin doğrusal olmayan sürekli fonksiyonlarla ifade edilen mühendislik problemlerine uygulanabilmesi mümkündür. Belirleyici (deterministik) olarak nitelendirilebilecek teknikler veren bu denklemle, olasılıksal (stochastic) yöntemlerde olduğu gibi istenirse türev bilgisi kullanmayan basit TAF yöntemleri tanımlanabilmektedir. Denklemin ve önerilen tekniklerin etkinliği uygulamalarla gösterilmiştir.
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REFERENCES

References: 

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Çizelge 4. Tersten kanat profili tasarımı için 1500
fonksiyon hesabı ile elde edilen en iyi fonksiyon
değerleri (x10−6 ).
GA TGA TAF1-
2m TAF1-2m0 TAF2-
2m
TAF1-1m
TAF2-1m
9.52 10.2 5.58 32.2 4.01 5.65
13.6 7.77 2.54 14.6 2.0 3.85
15.3 3.5 6.53 19.9 2.06 3.03
4.52 2.56 9.28 13.4 2.47 4.79
5.7 1.58 7.91 25.9 6.66 8.74
Doğrusal Olmayan Optimizasyon Problemleri İçin Taşınır Algoritmik Fonksiyonlar Yöntemi
HACIOĞLU
9
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