Sequential equality-constrained optimization for nonlinear programming

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• 作者：E. G. Birgin ; L. F. Bueno ; J. M. Martínez
• 关键词：Nonlinear programming ; Sequential equality ; constrained optimization ; Augmented Lagrangian ; Numerical experiments
• 刊名：Computational Optimization and Applications
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：65
• 期：3
• 页码：699-721
• 全文大小：634 KB
• 刊物类别：Mathematics and Statistics
• 刊物主题：Mathematics
  Optimization
  Operations Research and Mathematical Programming
  Operation Research and Decision Theory
  Statistics
  Convex and Discrete Geometry
  
• 出版者：Springer Netherlands
• ISSN：1573-2894
• 卷排序：65

文摘

A novel idea is proposed for solving optimization problems with equality constraints and bounds on the variables. In the spirit of sequential quadratic programming and sequential linearly-constrained programming, the new proposed approach approximately solves, at each iteration, an equality-constrained optimization problem. The bound constraints are handled in outer iterations by means of an augmented Lagrangian scheme. Global convergence of the method follows from well-established nonlinear programming theories. Numerical experiments are presented.