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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.Article Citation - WoS: 45Citation - Scopus: 51Computationally Efficient Discrete Sizing of Steel Frames Via Guided Stochastic Search Heuristic(Pergamon-elsevier Science Ltd, 2015) Azad, S. Kazemzadeh; Hasancebi, O.; Kazemzadeh Azad, S.Recently a design-driven heuristic approach named guided stochastic search (GSS) technique has been developed by the authors as a computationally efficient method for discrete sizing optimization of steel trusses. In this study, an extension and reformulation of the GSS technique are proposed for its application to problems from discrete sizing optimization of steel frames. In the GSS, the well-known principle of virtual work as well as the information attained in the structural analysis and design stages are used together to guide the optimization process. A design wise strategy is employed in the technique where resizing of members is performed with respect to their role in satisfying strength and displacement constraints. The performance of the GSS is investigated through optimum design of four steel frame structures according to AISC-LRFD specifications. The numerical results obtained demonstrate that the GSS can be employed as a computationally efficient design optimization tool for practical sizing optimization of steel frames. (C) 2015 Elsevier Ltd. All rights reserved.
