Abstract
In this study, safety margin explicit equation has been established using random variables (i.e., the engineering conditions, structure parameters, structural strength, and external load), and the genetic algorithm (GA)–based structural reliability optimization design has been addressed subsequently. Though the conventional adaptive GA can change automatically with fitness, it is still not unsatisfactory in sufficiently improving the algorithm convergence speed, especially for complex structures. This article presents an improved adaptive technology termed as the distant relative genetic algorithm (DRGA), in which the distant relative pointer and immunity operators can effectively improve the search performance of the GA. In early evolution, by means of cross controlling and avoiding pairing between individuals with the same genes, the methodology prevents the isogenic individuals expanding locally. Besides, the revised algorithm is able to jump out of the local optimal solution, thus ensuring the realization of a fast global convergence. An example based on wing box structure optimization has been demonstrated using the improved method, and the calculation results show that this strategy makes the GA more effective in dealing with the constraint optimization issues.
Highlights
With the rapid development of large and complex structures, more and more attention has been paid to the structural safety, such as the structural control and health monitoring [1, 2], the long-term performance deterioration [3, 4], and the structural optimization [5, 6], where the reliability-based structural optimization (RBSO) with multiple stochastic variables is always a difficult problem [7]
In the past few decades, much attention has been paid to the standard genetic algorithm (SGA) [8, 9]
A wing box structure is taken as the example to verify the proposed method
Summary
With the rapid development of large and complex structures, more and more attention has been paid to the structural safety, such as the structural control and health monitoring [1, 2], the long-term performance deterioration [3, 4], and the structural optimization [5, 6], where the reliability-based structural optimization (RBSO) with multiple stochastic variables is always a difficult problem [7]. The element safety margin function and system failure analysis are introduced, focusing on the optimization problem of an ideal elastic–plastic beam–slab structure system. The AGA alone cannot accommodate this phenomenon that once an overwhelming individual exists in the population, increasing pc cannot generate new models nor make the calculation jump out of the local optimal solution. After deducing the safety margin explicit equation, the branchand-bound method is adopted to search the main failure modes, and the probabilistic network evaluation technique (PNET) is adopted to calculate the system reliability index. The reliability-based structural optimization is calculated using the improved strategy as follows. The optimization results of the wing box structure are summarized in Tables 1, 2, including the cross-sectional areas of beams and the thicknesses of slabs. It is obvious that the average fitness is attained earlier based on the DRGA, which means a higher convergence efficiency
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