Performance Comparison of Biology based Metaheuristics Optimization Algorithms using Unimodal and Multimodal Benchmark Functions

Harun Bingöl

Makale detayları

Performance Comparison of Biology based Metaheuristics Optimization Algorithms using Unimodal and Multimodal Benchmark Functions

Yazarlar:

Harun Bingöl

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering

Dergi:

Turkish Journal of Science and Technology Vol.18 Issue 1, pp.157-167

Belge Tipi:

Makale

Yayın Tarihi:

3/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001285848

pISSN:

1308-9080

Anahtar kelimeler:

Özet:

 Optimization is used in almost every aspect of our lives today and makes our lives easier. Optimization is generally studied as classical and heuristic optimization techniques. Classical optimization methods are not effective in real-world engineering problems. These methods, by their nature, require a mathematical model. Metaheuristic optimization methods have started to be used frequently today in the solution of these problems when a mathematical model cannot be created or a solution cannot be produced in an effective time even if it is created. These methods, by their nature, cannot produce effective results in all engineering problems. Therefore, new metaheuristic optimization methods are constantly being researched. In this study, quality test functions have been used to compare the performances of five algorithms that have been developed in recent years and produce effective results. The results obtained from these functions are shared in this study. It has been observed that the Artificial Hummingbird Optimization Algorithm AHA gives better results than other metaheuristic algorithms.

 Optimization is used in almost every aspect of our lives today and makes our lives easier. Optimization is generally studied as classical and heuristic optimization techniques. Classical optimization methods are not effective in real-world engineering problems. These methods, by their nature, require a mathematical model. Metaheuristic optimization methods have started to be used frequently today in the solution of these problems when a mathematical model cannot be created or a solution cannot be produced in an effective time even if it is created. These methods, by their nature, cannot produce effective results in all engineering problems. Therefore, new metaheuristic optimization methods are constantly being researched. In this study, quality test functions have been used to compare the performances of five algorithms that have been developed in recent years and produce effective results. The results obtained from these functions are shared in this study. It has been observed that the Artificial Hummingbird Optimization Algorithm AHA gives better results than other metaheuristic algorithms.

 Optimization is used in almost every aspect of our lives today and makes our lives easier. Optimization is generally studied as classical and heuristic optimization techniques. Classical optimization methods are not effective in real-world engineering problems. These methods, by their nature, require a mathematical model. Metaheuristic optimization methods have started to be used frequently today in the solution of these problems when a mathematical model cannot be created or a solution cannot be produced in an effective time even if it is created. These methods, by their nature, cannot produce effective results in all engineering problems. Therefore, new metaheuristic optimization methods are constantly being researched. In this study, quality test functions have been used to compare the performances of five algorithms that have been developed in recent years and produce effective results. The results obtained from these functions are shared in this study. It has been observed that the Artificial Hummingbird Optimization Algorithm AHA gives better results than other metaheuristic algorithms.

 Optimizasyon günümüzde hayatımızın hemen her alanında kullanılmakta ve hayatımızı kolaylaştırmaktadır. Optimizasyon genellikle klasik ve sezgisel optimizasyon teknikleri olarak incelenmektedir. Klasik optimizasyon yöntemleri gerçek dünya mühendislik problemlerinde etkili değildir. Bu yöntemler doğaları gereği matematiksel bir modele ihtiyaç duyarlar. Matematiksel modelin oluşturulamadığı yada oluşturulsa bile etkili bir zamanda çözüm üretilemeyeceği anlarda bu problemlerin çözümünde metasezgisel optimizasyon yöntemleri günümüzde sıklıkla kullanılmaya başlamıştır. Bu yöntemler tüm mühendislik problemlerinde etkili sonuçları doğaları gereği üretemezler. Bundan dolayı sürekli olarak yeni metasezgisel optimizasyon yöntemleri araştırılmaktadır. Bu çalışmada da son yıllarda geliştirilen ve etkili sonuçlar üreten beş adet algoritmanın başarımlarını karşılaştırmak amacıyla kalite test fonksiyonları kullanılmıştır. Bu fonksiyonlardan elde edilen sonuçlar bu çalışmada paylaşılmıştır. Yapay Sinek Kuşu Optimizasyon Algoritmasının YSA diğer metasezgisel algoritmalardan daha iyi sonuçlar verdiği gözlemlenmiştir.

Makale detayları

Performance Comparison of Biology based Metaheuristics Optimization Algorithms using Unimodal and Multimodal Benchmark Functions

Yazarlar:

Harun Bingöl

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering

Dergi:

Turkish Journal of Science and Technology Vol.18 Issue 1, pp.157-167

Belge Tipi:

Makale

Yayın Tarihi:

3/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001285848

pISSN:

1308-9080

AHA

optimization

artificial intelligence

metaheuristic optimization

AHA

optimization

artificial intelligence

metaheuristic optimization

Sayı

Makale detayları

Yazarlar: Harun Bingöl

Yayıncı: Fırat University

Ana Başlıklar: Engineering

Dergi: Turkish Journal of Science and Technology Vol.18 Issue 1, pp.157-167

Belge Tipi: Makale

Yayın Tarihi: 3/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001285848

pISSN: 1308-9080

Sayı

Yazarlar:

Harun Bingöl

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering

Dergi:

Turkish Journal of Science and Technology Vol.18 Issue 1, pp.157-167

Belge Tipi:

Makale

Yayın Tarihi:

3/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001285848

pISSN:

1308-9080