A derivative-free filter method for solving nonlinear complementarity problems

In this work, nonlinear complementarity problems (NCPs) are considered. Some NCPs, which come from practice, have no derivatives or it is very difficult to obtain their derivatives. Derivative-free methods are hence considered. Generalized pattern search (GPS) method, as a kind of derivative-free me...

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Vydáno v:Applied mathematics and computation Ročník 161; číslo 3; s. 787 - 797
Hlavní autoři: Nie, Pu-yan, Fan, Jin-yan
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY Elsevier Inc 2005
Elsevier
Témata:
Applied sciences
Artificial intelligence
Calculus of variations and optimal control
Computer science; control theory; systems
Exact sciences and technology
Filter methods
Generalized pattern search methods
Global convergence
Mathematical analysis
Mathematical programming
Mathematics
Nonlinear complementarity problem
Nonlinear programming
Operational research and scientific management
Operational research. Management science
Pattern recognition. Digital image processing. Computational geometry
Sciences and techniques of general use
Filter methods
Global convergence
Nonlinear complementarity problem
Nonlinear programming
Generalized pattern search methods
Reduction method
Sufficient condition
Applied mathematics
Complementarity problem
Nonlinear problems
Non linear programming
Pattern recognition
Convergence
Filter method
ISSN:0096-3003, 1873-5649
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Popis
Shrnutí:In this work, nonlinear complementarity problems (NCPs) are considered. Some NCPs, which come from practice, have no derivatives or it is very difficult to obtain their derivatives. Derivative-free methods are hence considered. Generalized pattern search (GPS) method, as a kind of derivative-free method, plays a very significant role. We combine generalized pattern search method with filter method to attack NCPs because one can analyze the theory of generalized pattern search filter method without sufficient reduction conditions and avoid using of derivatives. Some interesting results are obtained in this work without sufficient reduction conditions. Furthermore, generalized pattern search filter method is efficient to some special problems.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2003.12.038