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Persistent URL http://purl.org/net/epubs/work/53045
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Record Id 53045
Title A second derivative SQP method: global convergence
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 method based on quadratic subproblems that are either convex, and thus may be solved efficiently, or need not be solved globally. Additionally, an explicit descent-constraint is imposed on certain QP subproblems, which “guides” the iterates through areas in which nonconvexity is a concern. Global convergence of the resulting algorithm is established.
Organisation CSE , STFC
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Language English (EN)
Type Details URI(s) Local file(s) Year
Journal Article SIAM J Optimiz 20, no. 4 (2010): 2023-2048. doi:10.1137/080744542 2010
Report RAL Technical Reports RAL-TR-2009-001. 2009. grRAL2009001.pdf 2009