Gould, Nicholas I. M. and Robinson, Daniel P. (2008) A second derivative SQP method: theoretical issues. Technical Report. SIAM Journal on Optimization. (Submitted)

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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 exactHessian 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 secondderivative 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 descentconstraint 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:  O  Z > Operations research, mathematical programming A  C > Calculus of variations and optimal control H  N > Numerical analysis 
Research Groups:  Numerical Analysis Group 
ID Code:  873 
Deposited By:  Lotti Ekert 
Deposited On:  17 Dec 2009 08:04 
Last Modified:  29 May 2015 18:33 
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