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A second derivative SQP method with imposed descent

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 Sl1QP...

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Publication date:
2008-06-05
URN:
uuid:b56aa11d-21c3-4e5e-90c0-b154cb7a1830
Local pid:
oai:eprints.maths.ox.ac.uk:1071

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