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Article Citation - WoS: 17Citation - Scopus: 16Discrete 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: 3Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm(Turkish Chamber Civil Engineers, 2020) Azad, Saeid Kazemzadeh; Akış, EbruMechanically 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.
