Multiobjective reliability-based design optimization of stochastic structural systems using a compromise programming strategy

Abstract

This work addresses the multiobjective reliability-based design optimization (MRBDO) problem involving structural dynamical systems under stochastic excitation. Instead of trying to determine the entire Pareto front, the goal is exploring specific tradeoffs between objectives. To this end, a compromise programming strategy based on aspiration levels is adopted to formulate an auxiliary single-objective optimization problem, which is then solved using a two-phase stochastic search technique. The approach ultimately yields a set of nearly equivalent compromise designs and valuable sensitivity information. For improved numerical efficiency, an adaptive surrogate model is implemented. An application example involving a three-dimensional building model equipped with nonlinear devices under stochastic ground excitation is studied.