Spectral Outer-Approximation Algorithms for Binary Semidefinite Problems

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: de Roux, Daniel, Peng, Zedong, Neira, David E. Bernal
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866918067942981632
author de Roux, Daniel
Peng, Zedong
Neira, David E. Bernal
author_facet de Roux, Daniel
Peng, Zedong
Neira, David E. Bernal
contents Integer semidefinite programming (ISDP) has recently gained attention due to its connection to binary quadratically constrained quadratic programs (BQCQPs), which can be exactly reformulated as binary semidefinite programs (BSDPs). However, it remains unclear whether this reformulation effectively uses existing ISDP solvers to address BQCQPs. To the best of our knowledge, no specialized ISDP algorithms exploit the unique structure of BSDPs derived from BQCQPs. This paper proposes a novel spectral outer approximation algorithm tailored for BSDPs derived from BQCQP reformulations. Our approach is inspired by polyhedral and second-order representable regions that outer approximate the feasible set of a semidefinite program relying on a spectral decomposition of a matrix that simultaneously diagonalizes the objective matrix and an aggregation of the constraint matrices. Computational experiments show that our algorithm is competitive with, and in some cases outperforms, state-of-the-art ISDP solvers such as SCIP-SDP and PAJARITO, highlighting ISDP's potential for solving BQCQPs.
format Preprint
id arxiv_https___arxiv_org_abs_2506_18265
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Spectral Outer-Approximation Algorithms for Binary Semidefinite Problems
de Roux, Daniel
Peng, Zedong
Neira, David E. Bernal
Optimization and Control
90-08, 90C11, 90C22
Integer semidefinite programming (ISDP) has recently gained attention due to its connection to binary quadratically constrained quadratic programs (BQCQPs), which can be exactly reformulated as binary semidefinite programs (BSDPs). However, it remains unclear whether this reformulation effectively uses existing ISDP solvers to address BQCQPs. To the best of our knowledge, no specialized ISDP algorithms exploit the unique structure of BSDPs derived from BQCQPs. This paper proposes a novel spectral outer approximation algorithm tailored for BSDPs derived from BQCQP reformulations. Our approach is inspired by polyhedral and second-order representable regions that outer approximate the feasible set of a semidefinite program relying on a spectral decomposition of a matrix that simultaneously diagonalizes the objective matrix and an aggregation of the constraint matrices. Computational experiments show that our algorithm is competitive with, and in some cases outperforms, state-of-the-art ISDP solvers such as SCIP-SDP and PAJARITO, highlighting ISDP's potential for solving BQCQPs.
title Spectral Outer-Approximation Algorithms for Binary Semidefinite Problems
topic Optimization and Control
90-08, 90C11, 90C22
url https://arxiv.org/abs/2506.18265