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Branch-and-Reduction Algorithm for Indefinite Quadratic Programming Problem

机译:无限二次编程问题的分支减少算法

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This paper presents a rectangular branch-and-reduction algorithm for globally solving indefinite quadratic programming problem (IQPP), which has a wide application in engineering design and optimization. In this algorithm, first of all, we convert the IQPP into an equivalent bilinear optimization problem (EBOP). Next, a novel linearizing technique is presented for deriving the linear relaxation programs problem (LRPP) of the EBOP, which can be used to obtain the lower bound of the global optimal value to the EBOP. To obtain a global optimal solution of the EBOP, the main computational task of the proposed algorithm involves the solutions of a sequence of LRPP. Moreover, the global convergent property of the algorithm is proved, and numerical experiments demonstrate the higher computational performance of the algorithm.
机译:本文介绍了一个矩形分支和减少算法,用于全球解决无限二次编程问题(IQPP),其在工程设计和优化方面具有广泛的应用。 在此算法中,首先,我们将IQPP转换为等效的双线性优化问题(EBOP)。 接下来,提出了一种用于导出EBOP的线性松弛程序问题(LRPP)的新型线性化技术,其可用于获得全局最佳值的下限。 为了获得EBOP的全局最佳解决方案,所提出的算法的主要计算任务涉及LRPP序列的解。 此外,证明了算法的全局会聚特性,数值实验证明了算法的较高计算性能。

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