A Primal - Dual Trust - Region Algorithm for Minimizing aNon - convex Function Subject to General Inequality and LinearEquality
نویسندگان
چکیده
A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Preliminary numerical results are presented.
منابع مشابه
A Primal-dual Trust-region Algorithm for Minimizing a Non-convex Function Subject to General Inequality and Linear Equality Constraints a Primal-dual Trust-region Algorithm for Non-convex Constrained Minimization
A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Preliminary numerical results are presented.
متن کاملA primal-dual trust-region algorithm for non-convex nonlinear programming
A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Numerical results are presented for general quadratic pr...
متن کاملA trust region method based on interior point techniques for nonlinear programming
An algorithm for minimizing a nonlinear function subject to nonlinear inequality constraints is described It applies sequential quadratic programming techniques to a sequence of barrier problems and uses trust regions to ensure the robustness of the iteration and to allow the direct use of second order derivatives This framework permits primal and primal dual steps but the paper focuses on the ...
متن کاملAn Affine Scaling Trust Region Algorithm for Nonlinear Programming
A monotonic decrease minimization algorithm can be desirable for nonconvex minimization since there may be more than one local minimizers. A typical interior point algorithm for a convex programming problem does not yield monotonic improvement of the objective function value. In this paper, a monotonic affine scaling trust region algorithm is proposed for nonconvex programming. The proposed aff...
متن کاملAn Interior Point Algorithm for Solving Convex Quadratic Semidefinite Optimization Problems Using a New Kernel Function
In this paper, we consider convex quadratic semidefinite optimization problems and provide a primal-dual Interior Point Method (IPM) based on a new kernel function with a trigonometric barrier term. Iteration complexity of the algorithm is analyzed using some easy to check and mild conditions. Although our proposed kernel function is neither a Self-Regular (SR) fun...
متن کامل