Uygunluk-Mesafe Dengesi Tabanlı Dev Armadillo Optimizasyon Algoritması

Abstract

Bu çalışmada, algoritmalardaki keşif ve sömürü arasındaki dengesizliği ortadan kaldırmak adına etkili bir yöntem olan Uygunluk-Mesafe Dengesi (FDB) yöntemi ile Dev Armadillo Optimizasyon (GAO) algoritması geliştirilmesi sağlanmıştır. Önerilen Uygunluk-Mesafe Dengesi tabanlı Dev Armadillo Optimizasyon (FDBGAO) algoritması ile temel GAO algoritmasına kıyasla keşif ve sömürü arasında daha etkili bir denge sağlanması amaçlanmıştır. Benzetim çalışmasında, temel GAO ve FDBGAO algoritmalarının etkinliğini incelemek amacıyla 23 standart kıyaslama fonksiyonu için analizler gerçekleştirilmiş ve elde edilen sonuçlar ortalama ve standart sapma değerleri açısından karşılaştırılmıştır. Elde edilen sonuçlar, FDBGAO algoritmasının tek-modlu, çok-modlu ve çok-modlu düşük boyutlu kıyaslama fonksiyonlarının çözümünde temel GAO algoritmasına kıyasla daha etkili ve başarılı sonuçlar verdiğini göstermektedir.

Keywords

• Uygunluk-Mesafe Dengesi
• Dev Armadillo Optimizasyon Algoritması
• Meta-sezgisel Algoritmalar

Fintess-Distance Balance based Giant Armadillo Optimization Algorithm

Abstract

In this study, the Giant Armadillo Optimization (GAO) algorithm has been developed using the Fitness-Distance Balance (FDB) method, which is an effective method to eliminate the imbalance between exploration and exploitation in the algorithms. The proposed Fitness-Distance Balance based Giant Armadillo Optimization (FDBGAO) algorithm aims to provide a more effective balance between exploration and exploitation compared to the main GAO algorithm. In the simulation study, in order to examine the effectiveness of the main GAO and FDBGAO algorithms, analyzes were performed for 23 standard benchmark functions and the obtained results were compared in terms of mean and standard deviation values. The obtained results show that the FDBGAO algorithm provides more effective and successful results compared to the basic GAO algorithm in solving single-mode, multi-mode and multi-mode low-dimensional benchmark functions.

Keywords

• Fitness-Distance Balance
• Giant Armadillo Optimization Algorithm
• Meta-heuristic Algorithms

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