SparsePOP : a Sparse Semidefinite Programming Relaxation of Polynomial Optimization Problems

  • Sunyoung Kim
  • Masakazu Kojima
  • Masakazu Muramatsu
  • Hayato Waki
    • Categories Global Optimization, Optimization Software and Modeling Systems, Semi-definite Programming Tags , , , , , Short URL: https://optimization-online.org/?p=9718

    SparesPOP is a MATLAB implementation of a sparse semidefinite programming (SDP) relaxation method proposed for polynomial optimization problems (POPs) in the recent paper by Waki et al. The sparse SDP relaxation is based on a hierarchy of LMI relaxations of increasing dimensions by Lasserre, and exploits a sparsity structure of polynomials in POPs. The efficiency of SparsePOP to compute bounds for optimal values of POPs is increased and larger scale POPs can be handled. The software package SparesPOP and this manual with some numerical examples are available at http://www.is.titech.ac.jp/~kojima/SparsePOP

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    Research Report B-414, Dept. of Mathematical and Computing Sciences, Tokyo Institute of Tehnology, Oh-Okayama, Meguro 152-8552, Tokyo, Japan

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