
The authors study the invertibility of the matrix that determines the solvability of the Newton equations in smoothing-type algorithms used in optimization problems. They begin with an introduction to this problem and the necessary definitions, which is followed by a section presenting the necessary and sufficient conditions for this matrix to be invertible. In the third section these results are interpreted to the to solvability of the original Newton equations which are used to parameterize the optimization problem.
Second-order cone complementarity problem, Applied Mathematics, second-order cone complementarity problem (SOCCP), Solvability of Newton equations, Nonconvex programming, global optimization, smoothing-type algorithm, solvability of Newton equations, Computational Mathematics, Numerical mathematical programming methods, Nonlinear programming, Smoothing-type algorithm, Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming)
Second-order cone complementarity problem, Applied Mathematics, second-order cone complementarity problem (SOCCP), Solvability of Newton equations, Nonconvex programming, global optimization, smoothing-type algorithm, solvability of Newton equations, Computational Mathematics, Numerical mathematical programming methods, Nonlinear programming, Smoothing-type algorithm, Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming)
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