AbstractThis paper presents for the first time a robust exact line-search method based on a full pseud'/> Optimization via Chebyshev polynomials
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Optimization via Chebyshev polynomials

机译:通过Chebyshev多项式优化

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AbstractThis paper presents for the first time a robust exact line-search method based on a full pseudospectral (PS) numerical scheme employing orthogonal polynomials. The proposed method takes on an adaptive search procedure and combines the superior accuracy of Chebyshev PS approximations with the high-order approximations obtained through Chebyshev PS differentiation matrices. In addition, the method exhibits quadratic convergence rate by enforcing an adaptive Newton search iterative scheme. A rigorous error analysis of the proposed method is presented along with a detailed set of pseudocodes for the established computational algorithms. Several numerical experiments are conducted on one- and multi-dimensional optimization test problems to illustrate the advantages of the proposed strategy.]]>
机译:Abstract本文首次提出了一种基于全伪谱(PS)的鲁棒精确线搜索方法采用正交多项式的数值格式。该方法采用自适应搜索过程,将切比雪夫PS逼近的优越精度与通过切比雪夫PS微分矩阵获得的高阶逼近相结合。此外,通过采用自适应牛顿搜索迭代格式,该方法具有二次收敛速度。文中对所提出的方法进行了严格的误差分析,并为已建立的计算算法提供了一组详细的伪码。在一维和多维优化测试问题上进行了若干数值实验,以说明该策略的优点]>

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