چكيده به لاتين
Over the past three decades, due to improvements in computational methods, the availability of high-speed processors, and the need for cost-effective designs, optimization of structures has become an attractive research field for researchers. Optimization on items and deterministic variables is called deterministic optimization. However, in real conditions, uncertainties due to modeling and simulation errors, or operational conditions such as loading changes, are always present and will affect the uncertainty of the responses of the structures. Given the uncertainties mentioned at each step in engineering design and operation; there is a need to introduce safety factors in the final optimization calculations. While the design of these types of structures will lead to overly conservative structures that will not be effective or may lead to an unsafe design under conditions. In order to resolve these problems, another design method called reliability-based design optimization has recently been of great interest to researchers. This method seeks to find the best balance between cost savings and satisfactory safety levels. A process that can not be achieved with deterministic optimization. In this approach, design safety based on the probability of failure is evaluated, as well as the above uncertainties are modeled with the probability distribution of random variables. This method is used for various structures. Different methods have been proposed to solve the RBDO problems to date, but due to the complexity and timeliness of solving these issues, what matters in reviewing and comparing these methods, their efficiency level means the level of accuracy of the final result and despite the low computational cost, the range of application methods is different for examples. In this work, after introducing the most recent and most effective methods for solving optimization problems based on reliability, weighted simulation method is selected due to low computational cost with high precision for simulation and firefly algorithm for optimization. After describing the details of this method at the end of the paper, we will address the mathematical examples that are selected from engineering issues, and examine its results with other relevant reliability methods, including the well-known methods of Monte Carlo Simulation and FORM and SORM, we evaluate the reliability and capability of the proposed method. The results of numerical examples compared with other methods of research indicate that the proposed method is accurate and feasible to address the reliability issues examined, especially those in which the dimensions of the variables are not high.
