Journal of Global Optimization

, Volume 41, Issue 2, pp 203–217

A globally and superlinearly convergent modified SQP-filter method


DOI: 10.1007/s10898-007-9219-0

Cite this article as:
Su, K. J Glob Optim (2008) 41: 203. doi:10.1007/s10898-007-9219-0


In this paper, we presented a modified SQP-filter method based on the modified quadratic subproblem proposed by Zhou (J. Global Optim. 11, 193–2005, 1997). In contrast with the SQP methods, each iteration this algorithm only needs to solve one quadratic programming subproblems and it is always feasible. Moreover, it has no demand on the initial point. With the filter technique, the algorithm shows good numerical results. Under some conditions, the globally and superlinearly convergent properties are given.


Constrained optimizationKKT pointSequential quadratic programmingGlobal convergenceSuperlinear convergence

Copyright information

© Springer Science+Business Media LLC 2007

Authors and Affiliations

  1. 1.Department of MathematicsTongji UniversityShangHaiP.R.China
  2. 2.College of Mathematics and ComputerHebei UniversityBaodingP.R.China