Improved approximation results on standard quartic polynomial optimization

Chen Ling, Hongjin He, Liqun Qi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


In this paper, we consider the problem of approximately solving standard quartic polynomial optimization (SQPO). Using its reformulation as a copositive tensor programming, we show how to approximate the optimal solution of SQPO by using a series of polyhedral cones to approximate the cone of copositive tensors. The established quality of approximation is sharper than the ones studied in the literature. As an interesting extension, we also propose some approximation bounds on multi-homogenous polynomial optimization problems.
Original languageEnglish
Pages (from-to)1767-1782
Number of pages16
JournalOptimization Letters
Issue number8
Publication statusPublished - 1 Dec 2017


  • Copositive tensor
  • Multi-homogenous polynomial optimization
  • PTAS
  • Quality of approximation
  • Standard quartic polynomial optimization

ASJC Scopus subject areas

  • Control and Optimization


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