Abstract
An efficient multi-objective reliability-based design optimization (MO-RBDO) method is proposed based on the probability and interval hybrid model. With probability variables coexist with interval variables in MO-RBDO problem, the original MO-RBDO problem could be considered as a three-layer nested multi-objective optimization problem. To reduce computing costs, firstly, an efficient decoupling strategy is developed to transform original three-layer MO-RBDO problem to single-layer optimization problem based on Karush–Kuhn–Tucker (KKT) necessary condition and the second-order fourth moment method. Secondly, a MO-RBDO method based on the adaptive approximation model is proposed for further improve computational efficiency. Then, the multi-objective genetic algorithm is employed to solve the MO-RBDO problem. Finally, the effectiveness and practicability of the proposed method are demonstrated by three numerical examples. • An efficient multi-objective reliability-based design optimization (RBDO) method is proposed. • A single-layer optimization problem is obtained based on decoupling strategy. • A multi-objective RBDO method based on the adaptive approximation model is proposed. • The multi-objective genetic algorithm is employed to solve the multi-objective RBDO problem. • The fine optimization results exhibit the effectiveness and practicability of the present method.
Published Version
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