A new second-order approximation method for optimum design of structures

IF 1.6 Q3 ENGINEERING, CIVIL Australian Journal of Civil Engineering Pub Date : 2020-08-07 DOI:10.1080/14488353.2020.1798039
H. Ahmadvand, A. Habibi
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引用次数: 2

Abstract

ABSTRACT In this study, a new method called Second-order Consistent Exponential Approximation (SCEA) is developed to generate the high-quality nonlinear approximation of the structural problems. For this purpose, some important parameters are designed by employing design sensitivities to enhance its consistency with various structural optimisation problems. In the optimisation process, the design variables for which sensitivity of the objective function is zero, are eliminated in the corresponding iteration. In addition, in approximating the design constraints, the zero design sensitivities are limited to a small value. In the presented approach, the primary optimisation problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. For reducing computational cost and enhancing the efficiency and capability of the proposed method, a corrective technique is applied for tolerance on the constraint violation, the function value, and the design variables in the SQP algorithm. Several structural examples and highly nonlinear problems were utilised to demonstrate the efficiency of the proposed method. Optimal solutions were compared to the conventional approximation methods and some of the metaheuristic approaches. Results illustrate that the accuracy of the optimum design is improved and the rate of the convergence speeds up.
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结构优化设计的一种新的二阶近似方法
摘要在本研究中,提出了一种新的方法——二阶一致指数逼近(SCEA)来生成结构问题的高质量非线性逼近。为此,通过采用设计灵敏度来设计一些重要参数,以增强其与各种结构优化问题的一致性。在优化过程中,目标函数灵敏度为零的设计变量在相应的迭代中被消除。此外,在近似设计约束时,零设计灵敏度被限制在较小的值。在所提出的方法中,主优化问题被一系列显式子问题取代。使用序列二次规划(SQP)算法有效地解决了每个子问题。为了降低计算成本,提高所提出方法的效率和能力,在SQP算法中对约束违反、函数值和设计变量的容差应用了校正技术。通过几个结构实例和高度非线性的问题来证明所提出方法的有效性。将最优解与传统的近似方法和一些元启发式方法进行了比较。结果表明,优化设计的精度得到了提高,收敛速度加快。
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来源期刊
CiteScore
3.90
自引率
7.70%
发文量
31
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