Kısıtlı Optimizasyon Problemleri için Fil Sürüsü Optimizasyonu Tabanlı Yeni Bir Yaklaşım

Birçok gerçek dünya problemi bir optimizasyon problemi olarak formüle edilebilir ve genel olarak bazı kısıtlamalara sahiptirler. Bu kısıtlamaların üstesinden gelmek için, kısıtlama yöntemleri ve bazı modifikasyonlar kullanarak doğa esinli algoritmalar kısıtlı optimizasyona uyarlanmıştır. Bu çalışmada, yeni ortaya çıkan bir optimizasyon tekniği olan fil sürü optimizasyonu algoritması ile kısıtlı optimizasyon problemlerini çözmek için yeni bir yaklaşım geliştirilmiştir. Temel EHO'nun yanı sıra, iki EHO varyantı (EHO-NoB ve GL-EHO) bu yaklaşımla kısıtlı optimizasyona uyarlanmıştır. İyi bilinen on üç kısıtlı test fonksiyonu, algoritmaların performanslarını analiz etmek için kullanılmıştır. Deneysel sonuçlar, GL-EHO'nun temel EHO ve diğer algoritmalardan daha iyi bir performansa sahip olduğunu göstermektedir. Ayrıca, GL-EHO sonuçları literatürdeki başka bir EHO varyantının sonucuyla karşılaştırılabilir düzeydedir.

A NOVEL APPROACH BASED ON ELEPHANT HERDING OPTIMIZATION FOR CONSTRAINED OPTIMIZATION PROBLEMS

Many real-world problems can be formulated as an optimization problem and they havesome constraints generally. To overcome these constraints, bio-inspired algorithms are adapted toconstrained optimization using constraint handling methods and some modifications. In this study, anew approach is developed to solve constrained optimization problems with elephant herdingoptimization algorithm which is a newly-emerging optimization technique. Besides the basic EHO, twoEHO variants (EHO-NoB and GL-EHO) are adapted to constrained optimization with this approach. Thewell-known thirteen constrained benchmark functions are used to analysis the performances ofalgorithms. Experimental results show that the GL-EHO has a better performance than the basic EHOand other algorithms. In addition, the results of GL-EHO are comparable level with the result of anotherEHO variant in the literature.

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