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Article Citation - WoS: 60Citation - Scopus: 64Seeding the Initial Population With Feasible Solutions in Metaheuristic Optimization of Steel Trusses(Taylor & Francis Ltd, 2018) Azad, Saeid KazemzadehIn 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: 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: 23Citation - Scopus: 21Design Optimization of Real-Size Steel Frames Using Monitored Convergence Curve(Springer, 2021) Azad, Saeid Kazemzadeh; Azad, Saeıd Kazemzadeh; Azad, Saeıd Kazemzadeh; Department of Civil Engineering; Department of Civil EngineeringIt is an undeniable fact that there are main challenges in the use of metaheuristics for optimal design of real-size steel frames in practice. In general, steel frame optimization problems usually require an inordinate amount of processing time where the main portion of computational effort is devoted to myriad structural response computations during the optimization iterations. Moreover, the inherent complexity of steel frame optimization problems may result in poor performance of even contemporary or advanced metaheuristics. Beside the challenging nature of such problems, significant difference in geometrical properties of two adjacent steel sections in a list of available profiles can also mislead the optimization algorithm and may result in trapping the algorithm in a poor local optimum. Consequently, akin to other challenging engineering optimization instances, significant fluctuations could be observed in the final results of steel frame optimization problems over multiple runs even using contemporary metaheuristics. Accordingly, the main focus of this study is to improve the solution quality as well as the stability of results in metaheuristic optimization of real-size steel frames using a recently developed framework so-called monitored convergence curve (MCC). Two enhanced variants of the well-known big bang-big crunch algorithm are adopted as typical contemporary metaheuristic algorithms to evaluate the usefulness of the MCC framework in steel frame optimization problems. The numerical experiments using challenging test examples of real-size steel frames confirm the efficiency of the MCC integrated metaheuristics versus their standard counterparts.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.
