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A second derivative SQP method: theoretical issues

Abstract:

Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second derivative information may often be calculated, there is little practical theory that justifies exact-Hessian SQP methods. In particular, the resulting quadratic programming (QP) subproblems are often nonconvex, and thus finding their global solutions may be computationally nonviable. This paper presents a second-derivative SQP m...

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Nicholas I. M. Gould More by this author
Daniel P. Robinson More by this author
Publication date:
2008-11-05
URN:
uuid:0a226abc-bf9a-47ea-8f7c-1eefc7ea8ca1
Local pid:
oai:eprints.maths.ox.ac.uk:873

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