Considering Soil-Structure Interaction Effects On Performance-Based Design Optimization Of Moment-Resisting Steel Frames By An Engineered Cluster-Based Genetic Algorithm

An engineered cluster-based genetic algorithm (ECGA) has been used for performance-based design optimization of two dimensional moment-resisting steel frames (MRSF) considering effects of the soil-structure interaction (SSI). Based on the engineering judgments and via using simple specified filters on defined constrained of the problem, an engineered population is generated. To impose this concept for increasing efficiency of the genetic algorithm (GA), first, engineered populations are generated, and then linear analysis of the structure is performed to check some of the constraints, finally in the case of satisfying the first stage constraints, nonlinear static analysis is carried out. The nonlinear spring model has been used to model SSI of the frames in OpenSees software. The constructed model in the OpenSees has been coupled with the GA optimization technique in MATLAB software to minimize weight of the structural elements. Efficiency and accuracy of the proposed method are demonstrated.