数学季刊 ›› 2009, Vol. 24 ›› Issue (3): 469-474.

• • 上一篇    

不等式约束最优化问题的可行SQP下降算法及其收敛性

  

  1. 1. Department of Mathematics, Luohe Vocational Technology College2. Department of Mathematics, Jiaozuo Teachers College

  • 收稿日期:2009-03-10 出版日期:2009-09-30 发布日期:2023-07-03
  • 作者简介:ZHANG He-ping(1965- ), male, native of Hebi, Henan, an associate professor of Luohe Vocational Technology College, M.S.D., engages in nonlinear programming; YE Liu-qing(1965- ), male, native of Runan, Henan, a professor of Jiaozuo Teachers College, M.S.D., engages in nonlinear programming.
  • 基金资助:
     Supported by the NNSF of China(10231060); Supported by the Soft Science Foundation of Henan Province(082400430820);

Feasible SQP Descent Method for Inequality Constrained Optimization Problems and Its Convergence 

  1. 1. Department of Mathematics, Luohe Vocational Technology College2. Department of Mathematics, Jiaozuo Teachers College
  • Received:2009-03-10 Online:2009-09-30 Published:2023-07-03
  • About author:ZHANG He-ping(1965- ), male, native of Hebi, Henan, an associate professor of Luohe Vocational Technology College, M.S.D., engages in nonlinear programming; YE Liu-qing(1965- ), male, native of Runan, Henan, a professor of Jiaozuo Teachers College, M.S.D., engages in nonlinear programming.
  • Supported by:
     Supported by the NNSF of China(10231060); Supported by the Soft Science Foundation of Henan Province(082400430820);

摘要: In this paper, the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented, and under weaker conditions of relative, we proofed the new method still possesses global convergence and its strong convergence. The 

关键词: nonlinearly constrained optimization, SQP, the generalized projection, line
search,
global convergence, strong convergence.

Abstract: In this paper, the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented, and under weaker conditions of relative, we proofed the new method still possesses global convergence and its strong convergence. The 

Key words: nonlinearly constrained optimization, SQP, the generalized projection, line
search,
global convergence, strong convergence.

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