THE PERFORMANCE COMPARISON OF THREE METAHEURISTIC ALGORITHMS ON THE SIZE, LAYOUT AND TOPOLOGY OPTIMIZATION OF TRUSS STRUCTURES

Abstract

The structural optimization problem mostly deals with the weight minimization of the structural system. This issue can be assessed from the size, layout and topology aspects. No matter which of these aspects are targeted, to solve them an optimization technique is required. In the last decades the metaheuristic techniques, as the non-gradient optimization algorithms, are widely applied on solving these classes of problems. In the structural optimization, the most time consuming part of the process is the objective function evaluation. Based on this fact, in the current work, these techniques are divided into three main groups as single phase, double phase and multi-phase algorithms. Then based on the author knowledge, three representative methods are picked for each group and their search performance comparatively inspected on solving size, shape and topology optimization of truss structures. To meet this aim, Integrated Particle Swarm Optimization (iPSO), Teaching and Learning Based Optimization (TLBO) and Drosophila Food-Search Optimization (DSO) algorithms are selected, respectively. Different properties like accuracy, convergence rate and complexity of the algorithms are investigated. The outcomes are provided via illustrative diagrams and tables. Based on the achieved results, DSO shows the most complexity level among the other algorithm while the iPSO and TLBO can outperform it on both accuracy and convergence rate. Consequently, iPSO presents a higher accuracy level on finding optimal solutions and TLBO with the lowest standard deviation value through the process shows the highest level of stability on finding optimal solutions.

Keywords

• Structural Optimization,Metaheuristic Algorithms,Constrained Optimization,Performance Comparison

ÜÇ SEZGİSEL YÖNTEMİN KAFES SİSTEMLERİN TOPOLOJİ, GEOMETRİ VE BOYUT OPTİMİZASYONU ÜZERİNDE PERFORMANS KARŞILAŞTIRMASI

Abstract

Bir yapısal optimizasyonda elemanların topolojisi, geometrisi veya kesitlerin boyutları dikkate alınarak sistemin ağırlığının minimize edilmesi amaçlanmaktadır. Çözüm tekniği olarak bu alanda son yıllarda üzerinde oldukça sık çalışılan sezgisel (metaheuristic) yöntemler geliştirilmiş ve kullanılmıştır. Yapısal optimizasyonda, amaç fonksiyonunun değerlendirmesi her iterasiyonda bir (ya da birden fazla)  yapısal analiz gerektirmektedir ve dolaysıyla çözüm sürecinin en çok zaman alan kısmını oluşturmaktadır. Bu gerçeği dikkate alarak, mevcut çalışmada bu yöntemler, tek fazlı, çift fazlı ve çok fazlı algoritmalar olarak üç ana gruba ayrılmış ve her gruptan bir yöntem seçilmiştir. Daha sonra bu yöntemlerin arama performansları kafes yapıların boyut, geometri ve topoloji optimizasyonu üzerinde karşılaştırılmıştır. Entegre edilmiş Partikül Sürüsü Optimizasyon (EPSO), Öğretme ve Öğrenme esaslı Optimizasyon (ÖÖO) ve Derosofila Yiyecek arama Optimizasyon (DYO) sırasıyla seçilen algoritmalardır. Algoritmaların, yakınsama hızı, dikkati ve karmaşıklığı gibi farklı özellikleri değerlendirilmiştir. Elde edilen sonuçlara göre, DYO diğer algoritmalara kıyasen en yüksek karmaşıklık indeksine sahiptir, ayrıca EPSO ve ÖÖO dikkat ve yakınsama hızı açısından daha iyi performans göstermektedirler. Üstelik, EPSO, optimum çözümler bulma konusunda daha yüksek bir dikkat seviyesine sahiptir. Optimizasyon sürecinde ÖÖO en düşük standart sapma değerine sahiptir ve dolaysıyla optimum çözümler bulma konusunda en yüksek kararlılık seviyesini göstermektedir.

Keywords

• Yapısal Optimizasyon,Sezgisel Algoritmalar,Kısıtlı Optimizasyon,Performans Karşılaştırması

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