A trust region method based on interior point techniques for nonlinear programming

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• 作者：Richard H. Byrd ; Jean Charles Gilbert and Jorge Nocedal
• 关键词：Key words ; constrained optimization – ; interior point method – ; large ; scale optimization – ; nonlinear programming – ; primal method – ; primal ; dual method – ; SQP iteration – ; barrier method – ; trust region method Mathematics Subject Classification (1991) ; 20E28 ; 20G40 ; 20C20
• 刊名：Mathematical Programming
• 出版年：2000
• 出版时间：November 2000
• 年：2000
• 卷：89
• 期：1
• 页码：149-185
• 全文大小：225 KB
• 刊物类别：Mathematics and Statistics
• 刊物主题：Mathematics
  Calculus of Variations and Optimal Control
  Mathematics of Computing
  Numerical Analysis
  Combinatorics
  Mathematical and Computational Physics
  Mathematical Methods in Physics
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1436-4646

文摘

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 primal version of the new algorithm. An analysis of the convergence properties of this method is presented.