Aminbakhsh, SamanAzad, Saeid KazemzadehAminbakhsh, SamanAzad, Saeıd KazemzadehCivil EngineeringDepartment of Civil Engineering2024-07-052024-07-05202252352-710210.1016/j.jobe.2021.1037672-s2.0-85121204003https://doi.org/10.1016/j.jobe.2021.103767https://hdl.handle.net/20.500.14411/1846Aminbakhsh, Saman/0000-0002-4389-1910; Kazemzadeh Azad, Saeid/0000-0001-9309-607XThis paper proposes a design-driven structural optimization algorithm named e-constraint guided stochastic search (e-GSS) for multi-objective design optimization of large-scale steel double-layer grids having numerous discrete design variables. Based on the well-known e-constraint method, first, the multi-objective optimization problem is transformed into a set of single-objective optimization problems. Next, each single-objective optimization problem is tackled using an enhanced reformulation of the standard guided stochastic search algorithm proposed based on a stochastic maximum incremental/decremental step size approach. Moreover, a successive seeding strategy is employed in conjunction with the proposed e-GSS algorithm to improve its performance in multi-objective optimization of large-scale steel double-layer grids. The numerical results obtained through multi-objective optimization of three challenging test examples, namely a 1728-member double-layer compound barrel vault, a 2304-member double-layer scallop dome, and a 2400-member double-layer multi-radial dome, demonstrate the usefulness of the proposed e-GSS algorithm in generating Pareto fronts of the foregoing multi-objective structural optimization problems with up to 2400 distinct sizing variables.eninfo:eu-repo/semantics/closedAccessMulti-objective optimizationStructural optimizationSteel double-layer gridse-constraint methodGuided stochastic searchHigh-dimensional optimizationArticleQ146WOS:000776167300003