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  • 标题:A Superlinearly feasible SQP algorithm for Constrained Optimization
  • 本地全文:下载
  • 作者:Zhijun Luo
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2013
  • 卷号:10
  • 期号:2
  • 出版社:IJCSI Press
  • 摘要:This paper is concerned with a Superlinearly feasible SQP algorithm algorithm for general constrained optimization. As compared with the existing SQP methods, it is necessary to solve equality constrained quadratic programming sub-problems at each iteration, which shows that the computational effort of the proposed algorithm is reduced further. Furthermore, under some mild assumptions, the algorithm is globally convergent and its rate of convergence is one-step superlinearly.
  • 关键词:Constrained Optimization; SQP Algorithm; Global convergence; Superlinear convergence rate.
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