Current optimization approaches to nondeterministic structural systems subject to random loads almost invariably treat the serviceability and ultimate limit states separately. A major drawback to these approaches is that design decisions at one limit state must be made in the absence of explicit information as to their consequences at other limit states of concern. This leads either to a considerable waste of money because of overdesign or to a low reliability of structural systems. The essential objective of this project is to develop an efficient and effective method for the multi-objective reliability-based optimization of structural systems subject to performance constraints imposed simultaneously at both serviceability and ultimate limit states. Almost no basic studies in structural optimization have been performed to develop such a method. A survey of recent research will be made for identifying probabilistic behavior models for nondeterministic structural members under service and ultimate random loads. These individual models will be incorporated into a general system model which will be used for developing a multi-objective reliability-based optimization method whereby performance constraints will be satisfied simultaneously at both service end ultimate limit states. This method will be extended to accommodate generel response sensitivities of the optimum solution to changes in the random parameters that define the loading and the member resistances. It is anticipated that the results will be of considerable value for the efficient design of structural systems under multiple reliability-based performance constraints.
