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A method for global minimization of nonconvex quadratic functions

  • Adil Bagirov
  • Vivek Laha
  • Juan Enrique Martínez-Legaz
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Abstract

The problem of global minimization of nonconvex quadratic functions subject to box constraints is studied. Applying Gershgorin theorem we reduce the main matrix A to its diagonal form which is used to obtain difference of convex representation of the quadratic function. Then ε-subdifferentials of DC components are studied and used to design a method for minimizing the quadratic function globally.

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Cite

BibTeXRIS
BibTeX
@misc{bagirov2026method,
  title = {{A method for global minimization of nonconvex quadratic functions}},
  author = {Adil Bagirov and Vivek Laha and Juan Enrique Martínez-Legaz},
  howpublished = {arXiv},
  year = {2026},
  month = aug,
  doi = {10.48550/arxiv.2608.30611},
  eprint = {2608.30611},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.30611},
}
RIS
TY  - UNPB
TI  - A method for global minimization of nonconvex quadratic functions
AU  - Adil Bagirov
AU  - Vivek Laha
AU  - Juan Enrique Martínez-Legaz
PY  - 2026
DA  - 2026/08/31
PB  - arXiv
DO  - 10.48550/arxiv.2608.30611
UR  - https://arxiv.org/abs/2608.30611
AB  - The problem of global minimization of nonconvex quadratic functions subject to box constraints is studied. Applying Gershgorin theorem we reduce the main matrix A to its diagonal form which is used to obtain difference of convex representation of the quadratic function. Then ε-subdifferentials of DC components are studied and used to design a method for minimizing the quadratic function globally.
ER  -