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[02298] New semidefinite relaxations for a class of complex quadratic programming problems

  • Session Time & Room : 3C (Aug.23, 13:20-15:00) @A201
  • Type : Contributed Talk
  • Abstract : In this talk, we propose some new semide finite relaxations for a class of nonconvex complex quadratic programming problems, widely appear in signal processing and power system. By deriving new valid constraints to the matrix variables in the lifted space, we derive some enhanced semide finite relaxations of complex quadratic programming problems. Then, we compare the proposed semide finite relaxations with existing ones, and show that the newly proposed semide finite relaxations could be strictly tighter than the previous ones. Numerical results indicate that the proposed semidefi nite relaxations not only provide tighter relaxation bounds but also improve some existing approximation algorithms by finding better sub-optimal solutions.
  • Classification : 90C20, 90C22, 90C35
  • Format : Talk at Waseda University
  • Author(s) :
    • Zhibin Deng (University of Chinese Academy of Sciences)
    • Yinzhe Xu (North China Electric Power University)
    • Cheng Lu (North China Electric Power University)
    • Yafeng Liu (Chinese Academy of Sciences)