| Deterministic and probabilistic (reliability-based) structural optimizations are topics of a great deal of research. This thesis examines the differences in the theory, application and practice of deterministic and probabilistic structural optimization. The theories of probability and optimization are presented by introducing reliability analysis and optimization algorithms. Three structural optimization examples, formulated for both deterministic and probabilistic design, are used to describe the application of deterministic and probabilistic structural optimization. Optimization problem features (modelling, data selection, formulation, solution and interpretation) are examined in order to determine the similarities, differences and peculiarities of deterministic and probabilistic optimization application. A database of optimization examples is examined and a review of optimization algorithm comparisons is presented in order to assess the state-of-the-practice of structural optimization. The novelty, features and methods of optimization practice are discussed to determine the information a non-expert can draw from current structural optimization literature. It is concluded that for optimization to be employed as a design tool, many designer oriented examples are required. Further research and development of probabilistic analysis theory and techniques are necessary before probabilistic optimization can be broadly applied. |
