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Pattern Search Methods for Linearly Constrained MinimizationWe extend pattern search methods to linearly constrained minimization. We develop a general class of feasible point pattern search algorithms and prove global convergence to a Karush-Kuhn-Tucker point. As in the case of unconstrained minimization, pattern search methods for linearly constrained problems accomplish this without explicit recourse to the gradient or the directional derivative. Key to the analysis of the algorithms is the way in which the local search patterns conform to the geometry of the boundary of the feasible region.
Document ID
19980017267
Acquisition Source
Langley Research Center
Document Type
Preprint (Draft being sent to journal)
Authors
Lewis, Robert Michael
(Institute for Computer Applications in Science and Engineering Hampton, VA United States)
Torczon, Virginia
(College of William and Mary Williamsburg, VA United States)
Date Acquired
September 6, 2013
Publication Date
January 1, 1998
Subject Category
Numerical Analysis
Report/Patent Number
ICASE-98-3
NAS 1.26:206904
NASA/CR-1998-206904
Funding Number(s)
CONTRACT_GRANT: F49620-95-1-0210
CONTRACT_GRANT: NAS1-19480
PROJECT: RTOP 505-90-52-01
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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