Multi-performance robust optimum design of steel structures

1. Abstract In engineering problems the randomness and uncertainties are inherent, thus the scatter of structural parameters from their nominal ideal values is unavoidable. Robust Design Optimization (RDO) methods primarily seek to minimize the influence of stochastic variations on the mean design, and traditionally rely on rough approximations of the stochastic response about the mean design. RDO yields a design with a state of robustness, so that its performance is the least sensitive to the variability of uncertain variables. The Monte Carlo Simulation method, that has been employed in the present work, has been proven to be very efficient for studying the stochastic response of large-scale structural systems with a large number of random variables. In this study, the task of robust design optimization of structures is formulated as a multi-criteria optimization problem, in which the design variables of the optimization problem, together with other design parameters, such as the modulus of elasticity and the yield stress, are considered as random variables having mean values equal to their nominal values. In the present study the aim is to minimize both structural weight and the variance of the structural response. The optimization algorithm employed is a two stage multi-membered Evolution Strategies scheme, specially tailored for solving multi-criteria structural optimization problems. 2.