Abstract
In the field of deterministic structural optimization, the designer reduces the structural cost without taking into account uncertainties concerning materials, geometry and loading. This way the resulting optimal design may represent a lower level of reliability and thus a higher risk of failure. The integration of reliability analysis into the design optimization problem represents the Reliability-Based Design Optimization (RBDO) model. The objective of this model is to design structures which should be both economic and reliable. The traditional RBDO solution is achieved by alternating between reliability and optimization iterations, and leads to very high computational cost and weak convergence stability. Fortunately, a hybrid method based on simultaneous solution of the reliability and the optimization problem, has successfully reduced the computational time problem [7]. However, both classical and hybrid RBDO may provide local optima. Here, the designer can do several trials to select the best solution. Therefore, in the present paper a new methodology based on the optimality conditions is proposed to provide the designer with global optimum.
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Kharmanda, G., Elhami, A., Olhoff, N. (2004). Global Reliability-Based Design Optimization. In: Floudas, C.A., Pardalos, P. (eds) Frontiers in Global Optimization. Nonconvex Optimization and Its Applications, vol 74. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0251-3_14
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DOI: https://doi.org/10.1007/978-1-4613-0251-3_14
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