A globally and superlinearly convergent feasible QP-free method for nonlinear programming
作者: Zhibin Zhu
作者单位: 1Department of Computational Science and Mathematics, Guilin Institute of Electronic Technology, Guilin 541004, PR China
刊名: Applied Mathematics and Computation, 2005, Vol.168 (1), pp.519-539
来源数据库: Elsevier Journal
DOI: 10.1016/j.amc.2004.09.034
关键词: Constrained optimizationQP-free algorithmSQP algorithmSystem of linear equationsGlobal convergenceSuperlinear convergence
原始语种摘要: Abstract(#br)In this paper, we propose a QP-free type algorithm which solves the problem of minimizing a smooth function subject to smooth inequality constraints. In contrast with the SQP methods, each iteration this algorithm only needs to solve systems of linear equations which are derived from the equality part in the KKT first order optimality conditions. It is observed that, if the quasi-Newton direction is zero, we can obtain a direction of descent by dropping a constraint from the active set at the current iterate. A high order modified direction is introduced in order to prevent Maratos effect. Global and superlinear convergence are proven under some suitable conditions.
全文获取路径: Elsevier  (合作)
影响因子:1.349 (2012)

  • convergence 汇合
  • convergent 收敛的
  • programming 程序设计
  • optimization 最佳化
  • nonlinear 非线性的
  • SQP 逐次二次规划
  • algorithm 算法
  • feasible 可实行的
  • globally 世界上
  • method 方法