The Mathematical Institute, University of Oxford, Eprints Archive

A second derivative SQP method with imposed descent

Gould, Nicholas I. M. and Robinson, Daniel P. (2008) A second derivative SQP method with imposed descent. Technical Report. Unspecified. (Submitted)



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 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.

Item Type:Technical Report (Technical Report)
Subjects:H - N > Numerical analysis
Research Groups:Numerical Analysis Group
ID Code:1071
Deposited By: Lotti Ekert
Deposited On:06 May 2011 07:23
Last Modified:29 May 2015 18:45

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