Azad, Saeıd Kazemzadeh
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Azad, S. Kazemzadeh
Saeid Kazemzadeh, Azad
S.K.Azad
Azad, Saeid Kazemzadeh
S., Azad
Azad, Saeıd Kazemzadeh
A., Saeid Kazemzadeh
S.,Azad
Azad,S.K.
A.,Saeid Kazemzadeh
Saeıd Kazemzadeh, Azad
A.,Saeıd Kazemzadeh
Saeid Kazemzadeh, Azad
S.K.Azad
Azad, Saeid Kazemzadeh
S., Azad
Azad, Saeıd Kazemzadeh
A., Saeid Kazemzadeh
S.,Azad
Azad,S.K.
A.,Saeid Kazemzadeh
Saeıd Kazemzadeh, Azad
A.,Saeıd Kazemzadeh
Job Title
Doçent Doktor
Email Address
saeid.azad@atilim.edu.tr
Main Affiliation
Department of Civil Engineering
Status
Former Staff
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SDG data is not available
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Scholarly Output
23
Articles
21
Views / Downloads
95/1130
Supervised MSc Theses
2
Supervised PhD Theses
0
WoS Citation Count
467
Scopus Citation Count
519
Patents
0
Projects
0
WoS Citations per Publication
20.30
Scopus Citations per Publication
22.57
Open Access Source
3
Supervised Theses
2
| Journal | Count |
|---|---|
| Structural and Multidisciplinary Optimization | 6 |
| Structures | 4 |
| Iranian Journal of Science and Technology, Transactions of Mechanical Engineering | 3 |
| Computers & Structures | 2 |
| Periodica Polytechnica Civil Engineering | 1 |
Current Page: 1 / 2
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23 results
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Now showing 1 - 10 of 23
Article Citation - WoS: 1Citation - Scopus: 1MO-ISCSO: A Challenging Benchmark Test Suite for Large-Scale Multi-Objective Structural Optimization(Elsevier Science inc, 2025) Azad, Saeid Kazemzadeh; Azad, Sina Kazemzadeh; Kazemzadeh Azad, SaeidCurrent studies on the development of multi-objective algorithms for optimization of truss structures mainly depend on small-scale classic benchmark instances. This paper highlights the importance of establishing standard large-scale multi-objective structural optimization benchmarking suites for accurate validation of the proposed algorithms. A new benchmark test suite, called MO-ISCSO, is proposed for large-scale multi-objective structural optimization, based on the most recent optimization problems of the international student competition in structural optimization (ISCSO). Owing to the very small feasibility ratios of the MO-ISCSO instances, the effect of presence of feasible designs in the initial population of NSGA-II, GDE3, and AR-MOEA multi-objective optimization algorithms is investigated using the proposed test suite. The obtained numerical results indicate that seeding the initial population with feasible solutions helps the foregoing algorithms maintain a better balance between convergence and diversity. The statistical results form a baseline for future studies on developing efficient multi-objective structural optimization techniques.Master Thesis Serbest Biçimli Çelık Çift Katmanlı Uzay Kafeslerin Optimizasyonu ve Standardizasyonu(2021) Shaban, Samer S S; Azad, Saeıd KazemzadehSon yıllarda düzensiz eğrili ancak estetik açıdan hoş görünen konfigürasyonlara sahip serbest biçimli yapıların kullanımına artan bir ilgi olmuştur. Normal çelik uzay kafeslerin tasarım optimizasyonu, yapısal optimizasyon literatüründe detaylı bir şekilde ele alınsa da, gerçek boyutlu serbest biçimli uzay kafes yapıların optimum tasarımında yapılan çalışmalar hala sınırlı düzeyde kalmıştır. Bir yandan, gerçek boyutlu serbest biçimli çelik kafeslerin optimizasyonunun önündeki ana engel, güncel evrimsel optimizasyon algoritmalarıyla ortaya çıkan aşırı hesaplama yüküdür. Öte yandan, algoritma tarafından nihai tasarımda farklı çelik kesit boyutlarının sayıca fazlalığını önlemek için gerekli kısıtlamalar uygulanmamışsa, geleneksel optimizasyon algoritmaları kullanılarak elde edilen nihai tasarımların uygulamada tercih edilmemesi muhtemeldir. Bu nedenle, tek bir optimum veya optimuma yakın tasarım sunmak yerine, tasarımcıya veya karar vericiye, hem minimum ağırlığı hem de mevcut ürün çeşitliliğini hesaba katan ve etkin tasarım alternatifleri setinden oluşan bir Pareto eğrisi sunmak daha arzu edilir olacaktır. Buna göre, bu çalışmada, gerçek boyutlu serbest biçimli çelik çift katmanlı uzay kafeslerin optimizasyonu ve standardizasyonu için hesaplama açısından verimli çok aşamalı rehberli stokastik arama algoritması önerilmiştir. İlk optimizasyon aşamasında, algoritmaya ticari olarak mevcut çelik profillerin eksiksiz bir setinin sunulduğu ve sonraki aşamalarda, kullanılmayan veya daha az kullanılan kesitleri eleyerek kesit listesinin kademeli olarak küçültüldüğü, bir tasarım odaklı kesit eleme yaklaşımı izlenmiştir. Serbest biçimli çelik çift katmanlı uzay kafeslerin sıra dışı kolay olmayan test örnekleri üzerinde önerilen tekniğin kullanışlılığını göstermek için algoritmanın iki farklı versiyonu kullanılmış ve elde edilen Pareto eğrisi, minimum ağırlık ve çelik kesit çeşitleri arasındaki dengeyi göstermek için çizilmiştir.Article Citation - WoS: 47Citation - Scopus: 45Enhanced Hybrid Metaheuristic Algorithms for Optimal Sizing of Steel Truss Structures With Numerous Discrete Variables(Springer, 2017) Azad, Saeid Kazemzadeh; Kazemzadeh Azad, SaeidThe advent of modern computing technologies paved the way for development of numerous efficient structural design optimization tools in the recent decades. In the present study sizing optimization problem of steel truss structures having numerous discrete variables is tackled using combined forms of recently proposed metaheuristic techniques. Three guided, and three guided hybrid metaheuristic algorithms are developed by integrating a design oriented strategy to the stochastic search properties of three recently proposed metaheuristic optimization techniques, namely adaptive dimensional search, modified big bang-big crunch, and exponential big bang-big crunch algorithms. The performances of the proposed guided, and guided hybrid metaheuristic algorithms are compared to those of standard variants through optimum design of real-size steel truss structures with up to 728 design variables according to AISC-LRFD specification. The numerical results reveal that the hybrid form of adaptive dimensional search and exponential big bang-big crunch algorithm is the most promising algorithm amongst the other investigated techniques.Article Citation - WoS: 17Citation - Scopus: 17Discrete Sizing of Steel Frames Using Adaptive Dimensional Search Algorithm(Budapest Univ Technology Economics, 2019) Hasancebi, Oguzhan; Azad, Saeid KazemzadehAdaptive dimensional search (ADS) algorithm is a recently proposed metaheuristic optimization technique for discrete structural optimization problems. In this study, discrete sizing optimization problem of steel frames is tackled using the ADS algorithm. An important feature of the algorithm is that it does not use any metaphor as an underlying principle for its implementation. Instead, the algorithm employs an efficient performance-oriented methodology at each iteration for convergence to the optimum or a near optimum solution. The performance of the ADS is investigated through optimum design of five real-size steel frame structures and the results are compared versus several contemporary metaheuristic techniques. The comparison of the obtained numerical results with those of available designs in the literature reveals the reliability and efficiency of the ADS in optimum design of steel frames.Article Citation - Scopus: 1An Enhanced Guided Stochastic Search With Repair Deceleration Mechanism for Very High-Dimensional Optimization Problems of Steel Double-Layer Grids(Springer, 2024) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Gandomi, Amir H.Finding reasonably good solutions using a fewer number of objective function evaluations has long been recognized as a good attribute of an optimization algorithm. This becomes more important, especially when dealing with very high-dimensional optimization problems, since contemporary algorithms often need a high number of iterations to converge. Furthermore, the excessive computational effort required to handle the large number of design variables involved in the optimization of large-scale steel double-layer grids with complex configurations is perceived as the main challenge for contemporary structural optimization techniques. This paper aims to enhance the convergence properties of the standard guided stochastic search (GSS) algorithm to handle computationally expensive and very high-dimensional optimization problems of steel double-layer grids. To this end, a repair deceleration mechanism (RDM) is proposed, and its efficiency is evaluated through challenging test examples of steel double-layer grids. First, parameter tuning based on rigorous analyses of two preliminary test instances is performed. Next, the usefulness of the proposed RDM is further investigated through two very high-dimensional instances of steel double-layer grids, namely a 21,212-member free-form double-layer grid, and a 25,514-member double-layer multi-dome, with 21,212 and 25,514 design variables, respectively. The obtained numerical results indicate that the proposed RDM can significantly enhance the convergence rate of the GSS algorithm, rendering it an efficient tool to handle very high-dimensional sizing optimization problems.Article Citation - WoS: 25Citation - Scopus: 32High-Dimensional Optimization of Large-Scale Steel Truss Structures Using Guided Stochastic Search(Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Kazemzadeh Azad, SaeidDespite a plethora of truss optimization algorithms devised in the recent literature of structural optimization, still high-dimensional large-scale truss optimization problems have not been properly tackled basically due to the excessive computational effort required to handle the foregoing instances. In this study, application of a recently developed design-driven heuristic, namely guided stochastic search (GSS), is extended to a more challenging class of truss optimization problems having thousands of design variables. Two variants of the algorithm, namely GSSA and GSSB, have been employed for sizing optimization of four high-dimensional examples of steel trusses, i.e., a 2075-member single-layer onion dome, a 2688-member double-layer open dome, a 6000-member doublelayer scallop dome, and a 15048-member double-layer grid as per AISC-LRFD specification. The numerical results obtained indicate the efficiency of GSSA and GSSB in handling high-dimensional instances of large-scale steel trusses with up to 15048 discrete design variables.Master Thesis Çelik Kafeslerin Dinamik Uyarımlar Altında Şekil ve Boyut Optimizasyonu(2018) Jawad, Farqad Kamıl Jawad; Azad, Saeıd KazemzadehGeçmiş yıllarda, çelik kafes optimizasyonu konusundaki araştırmaların ana odağı, statik yükleme koşulları altında optimum tasarımı elde etmeye yönelik olup, dinamik uyarımlar altında yapılan optimum yapısal tasarım araştırılmaları sınırlı sayıdadır. Bu tez, dinamik uyarımlara maruz kalan çelik kafes yapıların eş zamanlı şekil ve boyutlandırma optimizasyon problemini ele almaktadır. Modern bir evrimsel algoritma kullanarak, çelik kafeslerin minimum ağırlık tasarımı, hem periyodik hem de periyodik olmayan uyarımlar altında gerçekleştirilmiştir. Periyodik uyarımlarda, dinamik yükün uyarım periyodunun sonuçlar üzerindeki etkisini incelemek için tasarım örnekleri farklı uyarım periyotları altında optimize edilmiş ve elde edilen sonuçlar karşılaştırılmıştır. Kullanılan sinüzoidal yüklemenin periyodunun ve periyodik olmayan adım kuvvetinin yükselme süresinin arttırılmasıyla, optimizasyon sonuçlarının statik yükleme altında elde edilen sonuçlara yaklaştığı gözlenmiştir. Ancak, incelenen dikdörtgen periyodik uyarım durumunda elde edilen sonuçlar, uyarım periyodunun yüksek değerleri için bile statik yükleme altında elde edilen optimum tasarım ağırlıklarına yaklaşamamıştır.Article Citation - WoS: 11Citation - Scopus: 13Automated Selection of Optimal Material for Pressurized Multi-Layer Composite Tubes Based on an Evolutionary Approach(Springer London Ltd, 2018) Azad, Saeid Kazemzadeh; Akis, Tolga; Kazemzadeh Azad, SaeidDecision making on the configuration of material layers as well as thickness of each layer in composite assemblies has long been recognized as an optimization problem. Today, on the one hand, abundance of industrial alloys with different material properties and costs facilitates fabrication of more economical or light weight assemblies. On the other hand, in the design stage, availability of different alternative materials apparently increases the complexity of the design optimization problem and arises the need for efficient optimization techniques. In the present study, the well-known big bang-big crunch optimization algorithm is reformulated for optimum design of internally pressurized tightly fitted multi-layer composite tubes with axially constrained ends. An automated material selection and thickness optimization approach is employed for both weight and cost minimization of one-, two-, and three-layer tubes, and the obtained results are compared. The numerical results indicate the efficiency of the proposed approach in practical optimum design of multi-layer composite tubes under internal pressure and quantify the optimality of different composite assemblies compared to one-layer tubes.Article Citation - WoS: 60Citation - Scopus: 64Seeding the Initial Population With Feasible Solutions in Metaheuristic Optimization of Steel Trusses(Taylor & Francis Ltd, 2018) Azad, Saeid Kazemzadeh; Kazemzadeh Azad, SaeidIn spite of considerable research work on the development of efficient algorithms for discrete sizing optimization of steel truss structures, only a few studies have addressed non-algorithmic issues affecting the general performance of algorithms. For instance, an important question is whether starting the design optimization from a feasible solution is fruitful or not. This study is an attempt to investigate the effect of seeding the initial population with feasible solutions on the general performance of metaheuristic techniques. To this end, the sensitivity of recently proposed metaheuristic algorithms to the feasibility of initial candidate designs is evaluated through practical discrete sizing of real-size steel truss structures. The numerical experiments indicate that seeding the initial population with feasible solutions can improve the computational efficiency of metaheuristic structural optimization algorithms, especially in the early stages of the optimization. This paves the way for efficient metaheuristic optimization of large-scale structural systems.Article Citation - WoS: 5Citation - Scopus: 7A Study of Shrink-Fitting for Optimal Design of Multi-Layer Composite Tubes Subjected To Internal and External Pressure(Springer, 2019) Azad, Saeid Kazemzadeh; Akis, Tolga; Kazemzadeh Azad, SaeidThis paper addresses the effect of shrink-fitting on the optimal design of pressurized multi-layer composite tubes. Analytical solutions for structural response calculations are provided for axially constrained two- and three-layer shrink-fitted tubes under both internal and external pressure. A recently developed numerical evolutionary optimization algorithm is employed for weight and cost minimization of these assemblies. In order to investigate the effect of shrink-fitting, first, optimal material selection and thickness optimization of tightly fitted tubes, under either internal or both internal and external pressure, are accomplished without shrink-fitting. Next, under the same loading and boundary conditions the assemblies are optimized where shrink-fitting parameters are taken into account for weight and cost minimization. The numerical results obtained for multi-layer composite tubes with and without shrink-fitting indicate that more economical or lightweight assemblies can be obtained if shrink-fitting parameters are treated as additional design variables of the optimization problem. Furthermore, it is observed that considering the shrink-fitting parameters for optimal design becomes more advantageous in the test cases with a higher ratio of internal pressure to external pressure.
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