An interior trust region algorithm for solving linearly constrained nonlinear optimization

  • Ou Yigui
  • Hou Dingpi


In this paper, an interior point algorithm based on trust region techniques is proposed for solving nonlinear optimization problems with linear equality constraints and nonnegative variables. Unlike those existing interior-point trust region methods, this proposed method does not require that a general quadratic subproblem with a trust region bound be solved at each iteration. Instead, a system of linear equations is solved to get a search direction, and then a linesearch of Armijo type is performed in this direction to obtain a new iteration point. From a computational point of view, this approach may in general reduce a computational effort, and thus improve the computational efficiency. Under suitable conditions, it is proven that any accumulation of the sequence generated by the algorithm satisfies the first-order optimality condition.

AMS Mathematics Subject Classification

90C30 65K05 49M40 

Key words and phrases

Trust region method interior-point method line-search of Armijo-type KKT-point 


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Copyright information

© Korean Society for Computational & Applied Mathematics and Korean SIGCAM 2006

Authors and Affiliations

  1. 1.Department of Applied MathematicsHainan UniversityHaikou, HainanP. R. China
  2. 2.Department of MathematicsUSTCHefei, AnhuiP.R. China

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