ANALYTICAL AND EXPERIMENTAL COMPARISON OF PROBABILISTIC AND DETERMINISTIC OPTIMIZATION

The objective of this paper Is to evaluate experimentally the gain in reliability that can be achieved in the design of a system by using pr obabilistic optimization instead of deterministic optimization, The de sign of a truss structure, equipped with tuned dampers and subject to constraints on the dynamic response amplitudes, is used for the invest igation. The locations of the dampers and of tuning masses added to th e truss are used as design variables. The properties of the dampers ar e the main sources of uncertainties. The deterministic and probabilist ic optimizations are performed with genetic algorithms, Probabilities of failure are measured in the laboratory by testing multiple realizat ions of deterministic and probabilistic optimum designs. Predicted and measured values of the reliabilities of the. concurrent designs are c ompared. For a design problem selected to maximize the contrast in rel iability between the two optimum designs, the probabilistic optimizati on provided a large improvement in reliability compared with the deter ministic optimum design. This improvement was confirmed by experiments .