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Full Record Details
DOI
10.5286/raltr.2009001
Persistent URL
http://purl.org/net/epubs/work/53045
Record Status
Checked
Record Id
53045
Title
A second derivative SQP method: global convergence
Contributors
NIM Gould (STFC Rutherford Appleton Lab.)
,
DP Robinson
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
Keywords
Funding Information
Related Research Object(s):
49215823
Licence Information:
Language
English (EN)
Type
Details
URI(s)
Local file(s)
Year
Report
RAL Technical Reports
RAL-TR-2009-001. STFC, 2009.
grRAL2009001.pdf
2009
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