Skip to main navigation Skip to search Skip to main content

A polynomial optimization framework for polynomial quasi-variational inequalities with Moment-SOS relaxations

Xindong Tang, Min Zhang, Wenzhi Zhong

Research output: Contribution to journalArticlepeer-review

Abstract

We consider quasi-variational inequality problems (QVI) given by polynomial functions. By applying Lagrange multiplier expressions, we formulate polynomial optimization problems whose minimizers are KKT points for the QVI. Then, feasible extensions are exploited to preclude KKT points that are not solutions. Moment-SOS relaxations are incorporated to solve the polynomial optimization problems in our methods. Under certain conditions, our approach guarantees to find a solution to the QVI or detect the nonexistence of solutions.

Original languageEnglish
Pages (from-to)61-83
Number of pages23
JournalNumerical Algebra, Control and Optimization
Volume16
Early online date9 Dec 2024
DOIs
Publication statusPublished - 31 Mar 2026

Funding

Xindong Tang is supported by the NSFC Young Scientists Fund, grant number [12301407]. Min Zhang is supported by the National Natural Science Foundation of China Youth Fund Project, grant number [12101598].

Keywords

  • Lagrange multiplier expression
  • Moment-SOS hierarchy
  • polynomial optimization
  • Quasi-variational inequality

ASJC Scopus subject areas

  • Algebra and Number Theory
  • Control and Optimization
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'A polynomial optimization framework for polynomial quasi-variational inequalities with Moment-SOS relaxations'. Together they form a unique fingerprint.

Cite this