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Global optimization of a class of nonconvex quadratically constrained quadratic programming problems

  • Yong Xia*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we study a class of nonconvex quadratically constrained quadratic programming problems generalized from relaxations of quadratic assignment problems. We show that each problem is polynomially solved. Strong duality holds if a redundant constraint is introduced. As an application, a new lower bound is proposed for the quadratic assignment problem.

Original languageEnglish
Pages (from-to)1803-1812
Number of pages10
JournalActa Mathematica Sinica, English Series
Volume27
Issue number9
DOIs
StatePublished - Sep 2011

Keywords

  • Nonconvex programming
  • polynomial solvability
  • quadratic assignment problem
  • quadratically constrained quadratic programming
  • strong duality

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