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Journals / Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2026 / Cilt: 25 Sayı: 2

Comparison of Flower Pollination Algorithm and Particle Swarm Optimization for Structural Weight Minimization of RC Beams with Carbon Fiber Reinforced Polymer (CFRP)

Karbon Fiber Polimer Takviyeli Betonarme Kirişlerin Yapısal Ağırlık Minimizasyonu İçin Popülasyon Tabanlı Metasezgisel Algoritmaların Karşılaştırılması

Melda Yücel(İSTANBUL AYDIN ÜNİVERSİTESİ)0000-0002-2583-8630
Pages
381–387
Publication Date
2025-04-11
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to results, it can be said that FPA is the most powerful algorithm for determining the best parameters of structural models with the aim of providing minimum weight by considering the error metrics of objective function, and the lowness of weight values.

📌 3 Key Takeaways

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Objective & Hypothesis:In order to generate the best namely most appropriate design, different methodologies can be preferred.
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Key Findings & Data:For this reason, in the current study, to design the most appropriate structural model intended for reinforced concrete (RC) beam structures supported with carbon fiber reinforced polymer (CFRP), two different population-based metaheuristic methodologies as flower pollination algorithm (FPA), and a classical one as particle swarm optimization (PSO) were operated.
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Conclusion & Impact:According to results, it can be said that FPA is the most powerful algorithm for determining the best parameters of structural models with the aim of providing minimum weight by considering the error metrics of objective function, and the lowness of weight values.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Optimizasyon · Metasezgisel algoritmalar · Yapı mühendisliği

Abstract

In order to generate the best namely most appropriate design, different methodologies can be preferred. In nowadays, especially, metaheuristic algorithms, which have been proposed by inspiring various metaphors such as genetic, abilities of animals or natural behaviors of plants etc., can be useful, suitable and effective to provide the target results for any optimization problem. For this reason, in the current study, to design the most appropriate structural model intended for reinforced concrete (RC) beam structures supported with carbon fiber reinforced polymer (CFRP), two different population-based metaheuristic methodologies as flower pollination algorithm (FPA), and a classical one as particle swarm optimization (PSO) were operated. By this respect, several independent optimization cases were applied to compare the success and efficiency of algorithms in terms of minimization of total weight besides optimization of design parameters as number and width of CFRP plates. According to results, it can be said that FPA is the most powerful algorithm for determining the best parameters of structural models with the aim of providing minimum weight by considering the error metrics of objective function, and the lowness of weight values.

Özet

En iyi diğer bir deyişle en uygun tasarımı oluşturmak için farklı metodolojiler tercih edilebilmektedir. Günümüzde ise özellikle genetik, canlıların yetenekleri veya bitkilerin doğal yaşamdaki davranışları gibi çeşitli metaforlardan ilham alınarak geliştirilmiş olan metasezgisel algoritmalar herhangi bir optimizasyon problemi için hedef sonuçları sağlamak açısından kullanışlı, uygun ve etkili olabilmektedir. Bu nedenle mevcut çalışmada karbon fiber polimer takviye ile desteklenen betonarme kiriş yapıları için en uygun yapısal modelin tasarlanmasında çiçek tozlaşma algoritması ve klasik bir metod olan parçacık sürüsü optimizasyonu olarak iki farklı popülasyon tabanlı metasezgisel algoritma kullanılmıştır. Bu bağlamda CFRP plakaların genişliği ve sayısı olarak tanımlanan tasarım parametrelerinin optimizsyonunun yanısıra algoritmaların başarısı ve etkinliğini toplam ağırlığın minimize edilmesi açısından kıyaslamak için çeşitli bağımsız optimizasyon senaryoları uygulanmıştır. Sonuçlara göre ağırlık değerlerinin düşüklüğü ve amaç fonksiyonu için hata metrikleri dikkate alınarak minimum ağırlığın sağlanması doğrultusunda yapısal modellerin en iyi parametrelerini belirlemek için FPA’ nın en güçlü algoritma olduğu söylenebilir

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Cite This Article

Yücel, M. (2025). Comparison of Flower Pollination Algorithm and Particle Swarm Optimization for Structural Weight Minimization of RC Beams with Carbon Fiber Reinforced Polymer (CFRP). Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 25 Sayı: 2, 381–387. https://doi.org/10.35414/akufemubid.1507994

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