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Article Citation - WoS: 2Citation - Scopus: 2Structural Design Optimization of Multi-Layer Spherical Pressure Vessels: a Metaheuristic Approach(Springer, 2019) Akis, Tolga; Azad, Saeid KazemzadehThis study addresses the optimum design problem of multi-layer spherical pressure vessels based on von Mises yield criterion. In order to compute the structural responses under internal pressure, analytical solutions for one-, two-, and three-layer spherical pressure vessels are provided. A population-based metaheuristic algorithm is reformulated for optimum material selection as well as thickness optimization of multi-layer spherical pressure vessels. Furthermore, in order to enhance the computational efficiency of the optimization algorithm, upper bound strategy is also integrated with the algorithm for reducing the total number of structural response evaluations during the optimization iterations. The performance of the algorithm is investigated through weight and cost minimization of one-, two- and three-layer spherical pressure vessels and the results are presented in detail. The obtained numerical results, based on different internal pressures as well as vessel sizes, indicate the usefulness and efficiency of the employed methodology in optimum design of multi-layer spherical pressure vessels.Article Citation - Scopus: 4Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm(Turkish Chamber of Civil Engineers, 2020) Kazemzadeh Azad,S.; Akiş,E.Mechanically stabilized earth walls are among the most commonly used soil-retaining structural systems in the construction industry. This study addresses the optimum design problem of mechanically stabilized earth walls using a recently developed metaheuristic optimization algorithm, namely adaptive dimensional search. For a cost efficient design, different types of steel reinforcement as well as reinforced backfill soil are treated as discrete design variables. The performance of the adaptive dimensional search algorithm is investigated through cost optimization instances of mechanically stabilized earth walls under realistic design criteria specified by standard design codes. The numerical results demonstrate the efficiency and robustness of the adaptive dimensional search algorithm in minimum cost design of mechanically stabilized earth walls and further highlight the usefulness of design optimization in engineering practice. © 2020 Turkish Chamber of Civil Engineers. All rights reserved.Master Thesis Genel Öncüllük İlişkili Kesikli Zaman-maliyet-kalite Ödünleşim Problemi için Bir Meta-sezgisel Yöntem(2021) Abdulsattar, Abdulrahman M.; Amınbakhsh, Samanİnşaat projeleri kesinlikle bir ülkenin ekonomik büyümesine büyük katkı sağlayan en önemli unsurlardan biri olarak kabul edilebilir. Uygun çalışma alanları ve kaynakların mobilizasyonu için araçlar (örneğin ofis binaları, hastaneler, okullar, otoyollar) sağlayarak diğer endüstrilerdeki gelişmeleri de kolaylaştırırlar. Eşsiz kamu veya özel teklifler yoluyla, hükümetler ve paydaşlar, bu tür projeler için mümkün olan en kısa sürede ve en iyi kalitede makul fiyatlara ulaşmayı amaçlar. Açıkçası, mevcut teklifleri tartmak ve en uygun kararı bulmak karar vericiler için zorluklar doğurabilir. Bu bağlamda, karar vericilerin çatışan proje hedefleri (yani zaman, maliyet ve kalite) arasında uygun bir denge kurmalarına yardımcı olacak bir aracın oluşturulması zorunludur. Bu amaçla, bu çalışma, proje faaliyetlerinin her biri için mevcut seçenekler arasından en iyi uzlaşma seçeneklerinin seçilmesine yardımcı olan bir yöntem önermektedir. Önerilen yöntem, zaman ve maliyetin yanı sıra kalite boyutunu da denkleme dahil etmek için tasarlanmıştır. Kaliteyi ölçmek için, her bir faaliyetin ağırlıklı önemine ve performansına atıfta bulunan bir değer kullanılır. Önerilen yöntem, potansiyel adaylardan en iyi çözümlerin seçilmesi için hakimiyet kavramını içeren biraz değiştirilmiş bir Genetik Algoritmaya (GA) dayanmaktadır. GA tabanlı yöntem, her bir aktivite için sınırsız sayıda öncelik ilişkisini yönetebilir ve hepsinden önemlisi, her türlü mantıksal ilişkiyi yakalayabilir ve çözebilir. Bu özellik, faaliyetlerin paralelleştirilmesi gerçek yaşam projelerinde yaygın bir uygulama olduğundan, bu araştırmanın pratik alaka düzeyini önemli ölçüde artırır. Planlayıcılar, çeşitli ilişki türlerinden (yani, Başlangıç-Başlangıç, Başlangıç-Bitiş, Bitiş-Başlangıç ve Bitiş-Bitiş) ve gecikme süresi kavramından yararlanarak ağa sıklıkla paralelleştirme getirir. Örtüşen faaliyetler, istenmeyen boşta kalma sürelerini azaltmaya ve projeyi önemli ölçüde hızlandırmaya yardımcı olur. Uygulamayı göstermek ve önerilen modelin etkinliğini değerlendirmek için, ikisi bu tez kapsamında oluşturulan üç farklı Zaman-Maliyet-Kalite (TCQ) değiş tokuş probleminin çözümü için kullanılmıştır. Uygulanan örnekler, sırasıyla mevcut 29-ve 63-etkinlik zaman-maliyet takas problemlerine dayalı olarak burada üretilen daha karmaşık 29-ve 63-aktivite TCQ problemlerine ek olarak literatürden alınan 18 aktivite ile küçük bir kıyaslama TCQ problemini içerir. Elde edilen sonuçlar, hem önerilen modelin etkinliğini hem de planlamacılar tarafından zorlu kararlar alırken kullanılabilme olasılığını ortaya koymaktadır.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, TolgaDecision 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: 1Citation - Scopus: 1Metaheuristic Optimization of Rotating Multilayer Composite Tubes Under Internal Heating and Pressure(Springer, 2022) Azad, Saeid Kazemzadeh; Akis, TolgaAlthough analysis/design of multilayer assemblies has been always an active field of research, works on the optimal design of rotating multilayer composite tubes are very limited. This paper addresses the design optimization of rotating multilayer composite tubes under internal heating and pressure. For determining the structural responses, analytical solutions are provided based on different boundary conditions. The automated selection of optimal material as well as thickness optimization of pressurized multilayer assemblies is carried out under different angular speed and internal heating conditions using a metaheuristic algorithm. The corresponding optimum design for each angular speed as well as internal heating condition is sought, and the numerical results are discussed. The study provides general guidelines for conceptual design of rotating multilayer composite tubes subjected to internal heating and pressure.Article Citation - WoS: 4Citation - Scopus: 6A Study of Shrink-Fitting for Optimal Design of Multi-Layer Composite Tubes Subjected To Internal and External Pressure(Springer, 2019) Azad, Saeid Kazemzadeh; Akis, TolgaThis 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.Conference Object Citation - WoS: 2Citation - Scopus: 3Autonomous Tuning for Constraint Programming Via Artificial Bee Colony Optimization(Springer-verlag Berlin, 2015) Soto, Ricardo; Crawford, Broderick; Mella, Felipe; Flores, Javier; Galleguillos, Cristian; Misra, Sanjay; Paredes, FernandoConstraint Programming allows the resolution of complex problems, mainly combinatorial ones. These problems are defined by a set of variables that are subject to a domain of possible values and a set of constraints. The resolution of these problems is carried out by a constraint satisfaction solver which explores a search tree of potential solutions. This exploration is controlled by the enumeration strategy, which is responsible for choosing the order in which variables and values are selected to generate the potential solution. Autonomous Search provides the ability to the solver to self-tune its enumeration strategy in order to select the most appropriate one for each part of the search tree. This self-tuning process is commonly supported by an optimizer which attempts to maximize the quality of the search process, that is, to accelerate the resolution. In this work, we present a new optimizer for self-tuning in constraint programming based on artificial bee colonies. We report encouraging results where our autonomous tuning approach clearly improves the performance of the resolution process.
