Abstract
The paper deals with the optimization of structural systems involving discrete and continuous sizing type of design variables. In particular, the reliability-based optimization of non-linear systems subject to stochastic excitation where some or all of the design variables are discrete is considered. The reliability-based optimization problem is formulated as the minimization of an objective function subject to multiple reliability constraints. The probability that design conditions are satisfied within a given time interval is used as measure of system reliability. The basic mathematical programming statement of the structural optimization problem is converted into a sequence of explicit approximate primal problems of separable form. The explicit approximate primal problems are solved by constructing continuous explicit dual functions, which are maximized subject to simple non-negativity constraints on the dual variables. A gradient projection type of algorithm is used to find the solution of each dual problem. The effectiveness of the method is demonstrated by presenting a numerical example of a non-linear system subject to stochastic ground acceleration.
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