论文信息 - B-453 User's Manual for SparseCoLO: Conversion Methods for SPARSE COnic-form Linear Optimization Problems

B-453 User's Manual for SparseCoLO: Conversion Methods for SPARSE COnic-form Linear Optimization Problems

SparseCoLO is a Matlab package for implementing the four conversion methods, proposed by Kim, Kojima, Mevissen, and Yamashita, via positive semidefinite matrix completion for an optimization problem with matrix inequalities satisfying a sparse chordal graph structure. It is based on a general description of optimization problem including both primal and dual form of linear, semidefinite, and second-order cone programs with equality/inequality constraints. Among the four conversion methods, two methods utilize the domain-space sparsity of a semidefinite matrix variable and the two other methods the range-space sparsity of a linear matrix inequality (LMI) constraint of the given problem. SparseCoLO can be used as a preprocessor to reduce the size of the given problem before applying semidefinite programming solvers. The website for this package is http://www.is.titech.ac.jp/∼kojima/SparseCoLO where the package SparseCoLO and this manual can be downloaded.

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