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Relaxation approach to topology optimization of frame structure under frequency constraint

机译:频率约束下框架结构拓扑优化的松弛方法

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This paper deals with the frame topology optimization under the frequency constraint and proposes an algorithm that solves a sequence of relaxation problems to obtain a local optimal solution with high quality. It is known that an optimal solution of this problem often has multiple eigenvalues and the feasible set is disconnected. Due to these two difficulties, conventional nonlinear programming approaches often converge to a local optimal solution that is unacceptable from a practical point of view. In this paper, we formulate the frequency constraint as a positive semidefinite constraint of a certain symmetric matrix, and then relax this constraint to make the feasible set connected. The proposed algorithm solves a sequence of the relaxation problems with gradually decreasing the relaxation parameter. The positive semidefinite constraint is treated with the logarithmic barrier function and, hence, the algorithm finds no difficulty in multiple eigenvalues of a solution. Numerical experiments show that global optimal solutions, or at least local optimal solutions with high qualities, can be obtained with the proposed algorithm.
机译:本文针对频率约束条件下的帧拓扑优化问题,提出了一种解决一系列松弛问题的算法,以获得高质量的局部最优解。众所周知,此问题的最佳解决方案通常具有多个特征值,并且可行集被断开。由于这两个困难,常规的非线性编程方法通常会收敛到局部最优解,这从实践的角度来看是无法接受的。在本文中,我们将频率约束公式化为某个对称矩阵的正半定约束,然后放宽此约束以使可行集连通。提出的算法通过逐渐减小松弛参数来解决一系列松弛问题。正对半定约束用对数屏障函数处理,因此,该算法在求解的多个特征值中不存在困难。数值实验表明,该算法可以得到全局最优解,或至少具有高质量的局部最优解。

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