Nonmonotone curvilinear line search methods for unconstrained optimization |
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Authors: | M C Ferris S Lucid M Roma |
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Institution: | (1) Computer Sciences Department, University of Wisconsin, 53706 Madison, Wisconsin, USA;(2) Dipartimento di Informatica e Sistemistica, Università di Roma La Sapienza, Roma, Italy |
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Abstract: | We present a new algorithmic framework for solving unconstrained minimization problems that incorporates a curvilinear linesearch. The search direction used in our framework is a combination of an approximate Newton direction and a direction of negative curvature. Global convergence to a stationary point where the Hessian matrix is positive semidefinite is exhibited for this class of algorithms by means of a nonmonotone stabilization strategy. An implementation using the Bunch-Parlett decomposition is shown to outperform several other techniques on a large class of test problems.The work of this author was based on research supported by the National Science Foundation Grant CCR-9157632, the Air Force Office of Scientific Research Grant F49620-94-1-0036 and the Department of Energy Grant DE-FG03-94ER61915.These authors were partially supported by Agenzia Spaziale Italiana, Roma, Italy. |
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