Improved semidefinite approximation bounds for nonconvex nonhomogeneous quadratic optimization with ellipsoid constraints

  • Yong Hsia
  • , Shu Wang
  • , Zi Xu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We study the problem of approximating nonconvex quadratic optimization with ellipsoid constraints (ECQP) and establish a new semidefinite approximation bound, which greatly improves Tseng's result (Tseng, 2003). As an application, we strictly improve the approximation ratio for the assignment-polytope constrained quadratic program. Finally, based on a randomized algorithm, we obtain a new approximation bound for (ECQP) which is sharp in the order of the number of the ellipsoid constraints.

Original languageEnglish
Pages (from-to)378-383
Number of pages6
JournalOperations Research Letters
Volume43
Issue number4
DOIs
StatePublished - 30 May 2015

Keywords

  • Approximation algorithm
  • Quadratic constrained quadratic programming
  • Semidefinite programming relaxation

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