Reliability-Based Optimal Design of Space Structures Using Genetic Algorithm

Optimization by explicit and deterministic variables is called deterministic optimization. It is known that there are wide varieties of uncertainties which are originated from the errors in modeling and simulation and condition of services such as changes in loading. Moreover, we must consider these uncertainties in different stages of design process of structures. Some of the most important factors which should be consider in structural designing are variation of material properties, geometrical dimensions of the structures, and the loading patterns. On the other hand, deterministic optimization on structures uses the strong safety factors instead of uncertainties. Thus, the resultant designed-structures are leading to the excessive conservative structures that would not be economical and optimal. According to, existing some uncertainties in each level of engineering design process; it is required to consider safety factors in computation of the deterministic optimization. In order to resolve this problem, an efficient approach is recently developed which is called reliability based optimal design. In this method the safety of structures are evaluated based on the failure probability and the aforementioned uncertainties are modeled by the probability distribution of random variables. Finally, the investigated components embedded in the assessed acceptable ranges of safety which is introduces with the failure definition. This practical method can be applied to different structures.