Optimization of uncertain structures based on possibilistic reliability model

The paper deals with the problem of optimization of uncertain structures. Reliability-based optimization of uncertain structures is usually solved using stochastic model, which needs a wealth of data on stochastic parameters and is often a time consuming task. A different strategy which makes use of possibilistic reliability theory we proposed in a previous paper is used here. A new procedure of reliability-based optimization for uncertain structural design is presented, which is parallel to the traditional stochastic-reliability-based optimization procedure. In the context, possibility theory is used to model uncertainties. Structural optimization is described as minimizing the failure possibility of structures for a given weight or cost, or minimizing the weight or cost for a specified allowable failure possibility. Because possibilistic reliability procedure does not require large amount of data and is easy to compute, the present procedure can make use of limited available information and reduce the computational cost. A numerical example shows that the present procedure is effective and feasible for optimization of uncertain structures.