Bounds of the Solution Set to the Polynomial Complementarity Problem

IF 1.6 3区 数学 Q2 MATHEMATICS, APPLIED
Yang Xu, Guyan Ni, Mengshi Zhang
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引用次数: 0

Abstract

In this paper, we investigate bounds of solution set of the polynomial complementarity problem. When a polynomial complementarity problem has a solution, we propose a lower bound of solution norm by entries of coefficient tensors of the polynomial. We prove that the proposing lower bound is larger than some existing lower bounds appeared in tensor complementarity problems and polynomial complementarity problems. When the solution set of a polynomial complementarity problem is nonempty, and the coefficient tensor of the leading term of the polynomial is an \(R_0\)-tensor, we propose a new upper bound of solution norm of the polynomial complementarity problem by a quantity defining by an optimization problem. Furthermore, we prove that when coefficient tensors of the polynomial are partially symmetric, the proposing lower bound formula with respect to tensor tuples reaches the maximum value, and the proposing upper bound formula with respect to tensor tuples reaches the minimum value. Finally, by using such partial symmetry, we obtain bounds of solution norm by coefficients of the polynomial.

多项式互补问题解集的边界
本文研究多项式互补问题解集的边界。当多项式互补问题有解时,我们提出了多项式系数张量项的解规范下界。我们证明,提出的下界大于张量互补问题和多项式互补问题中出现的一些现有下界。当多项式互补问题的解集是非空的,并且多项式前项的系数张量是\(R_0\)-张量时,我们提出了一个新的多项式互补问题解规范的上界,这个上界是由一个优化问题定义的量来表示的。此外,我们还证明了当多项式的系数张量部分对称时,针对张量元组提出的下界公式会达到最大值,而针对张量元组提出的上界公式会达到最小值。最后,利用这种部分对称性,我们可以得到多项式系数的解规范约束。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
149
审稿时长
9.9 months
期刊介绍: The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.
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