Separable QCQPs and Their Exact SDP Relaxations

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Kojima, Masakazu, Kim, Sunyoung, Arima, Naohiko
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911564896927744
author Kojima, Masakazu
Kim, Sunyoung
Arima, Naohiko
author_facet Kojima, Masakazu
Kim, Sunyoung
Arima, Naohiko
contents This paper studies exact semidefinite programming relaxations (SDPRs) for separable quadratically constrained quadratic programs (QCQPs). We consider the construction of a larger separable QCQP from multiple QCQPs with exact SDPRs. We show that exactness is preserved when such QCQPs are combined through a separable horizontal connection, where the coupling is induced through the right-hand-side parameters of the constraints. The proposed framework provides a simple sufficient condition for exactness of the resulting SDPR. We then identify notable classes of QCQPs for which this condition holds, including convex QCQPs, QCQPs defined by sign-pattern and graph-structural conditions, and separable homogeneous QCQPs with a limited number of constraints. Two examples illustrate the constructive nature of the proposed framework, showing how heterogeneous QCQPs can be combined to yield new instances with exact SDP relaxations.
format Preprint
id arxiv_https___arxiv_org_abs_2604_02968
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Separable QCQPs and Their Exact SDP Relaxations
Kojima, Masakazu
Kim, Sunyoung
Arima, Naohiko
Optimization and Control
90C20, 90C22, 90C25, 90C26
This paper studies exact semidefinite programming relaxations (SDPRs) for separable quadratically constrained quadratic programs (QCQPs). We consider the construction of a larger separable QCQP from multiple QCQPs with exact SDPRs. We show that exactness is preserved when such QCQPs are combined through a separable horizontal connection, where the coupling is induced through the right-hand-side parameters of the constraints. The proposed framework provides a simple sufficient condition for exactness of the resulting SDPR. We then identify notable classes of QCQPs for which this condition holds, including convex QCQPs, QCQPs defined by sign-pattern and graph-structural conditions, and separable homogeneous QCQPs with a limited number of constraints. Two examples illustrate the constructive nature of the proposed framework, showing how heterogeneous QCQPs can be combined to yield new instances with exact SDP relaxations.
title Separable QCQPs and Their Exact SDP Relaxations
topic Optimization and Control
90C20, 90C22, 90C25, 90C26
url https://arxiv.org/abs/2604.02968