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
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 aNon - convex Function Subject to General Inequality and LinearEquality
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.
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