二次规划中SDP精确性的不变量

Pub Date : 2023-08-22 DOI:10.1016/j.jsc.2023.102258
Julia Lindberg , Jose Israel Rodriguez
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引用次数: 1

摘要

本文通过确定可行集并考虑目标函数的精确松弛空间,研究了二次规划的Shor松弛问题。首先给出了在可行集的生成元选择条件下该区域不变的条件。然后我们描述了在一般线性群的子群作用下可行集不变的区域。最后,我们将这些结果应用于二次二进制程序。我们给出了目标函数的显式描述,其中Shor松弛是精确的,并利用这些知识设计了一种算法,该算法产生二元二次规划的候选解。
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Invariants of SDP exactness in quadratic programming

In this paper we study the Shor relaxation of quadratic programs by fixing a feasible set and considering the space of objective functions for which the Shor relaxation is exact. We first give conditions under which this region is invariant under the choice of generators defining the feasible set. We then describe this region when the feasible set is invariant under the action of a subgroup of the general linear group. We conclude by applying these results to quadratic binary programs. We give an explicit description of objective functions where the Shor relaxation is exact and use this knowledge to design an algorithm that produces candidate solutions for binary quadratic programs.

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