Aminbakhsh, SamanAzad, Saeid KazemzadehAminbakhsh, SamanAzad, Saeıd KazemzadehCivil EngineeringDepartment of Civil Engineering2024-07-052024-07-052021182352-012410.1016/j.istruc.2021.05.0352-s2.0-85107859081https://doi.org/10.1016/j.istruc.2021.05.035https://hdl.handle.net/20.500.14411/2092Aminbakhsh, Saman/0000-0002-4389-1910; Kazemzadeh Azad, Saeid/0000-0001-9309-607XDespite 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.eninfo:eu-repo/semantics/closedAccessStructural optimizationLarge-scale steel trussesPrinciple of virtual workGuided stochastic searchHigh-dimensional optimizationIntegrated force methodArticleQ23314391456WOS:000702824700004