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- Publisher Website: 10.1007/s10589-006-6442-4
- Scopus: eid_2-s2.0-33748319447
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Article: A Logarithmic-Quadratic proximal prediction-correction method for structured monotone variational inequalities
Title | A Logarithmic-Quadratic proximal prediction-correction method for structured monotone variational inequalities |
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Authors | |
Keywords | Variational inequality Prediction-correction Logarithmic-Quadratic Proximal method |
Issue Date | 2006 |
Citation | Computational Optimization and Applications, 2006, v. 35, n. 1, p. 19-46 How to Cite? |
Abstract | Inspired by the Logarithmic-Quadratic Proximal (LQP) method for variational inequalities, we present a prediction-correction method for structured monotone variational inequalities. Each iteration of the new method consists of a prediction and a correction. Both the predictor and the corrector are obtained easily with tiny computational load. In particular, the LQP system that appears in the prediction is approximately solved under significantly relaxed inexactness restriction. Global convergence of the new method is proved under mild assumptions. In addition, we present a self-adaptive version of the new method that leads to easier implementations. Preliminary numerical experiments for traffic equilibrium problems indicate that the new method is effectively applicable in practice. © 2006 Springer Science + Business Media, LLC. |
Persistent Identifier | http://hdl.handle.net/10722/250913 |
ISSN | 2023 Impact Factor: 1.6 2023 SCImago Journal Rankings: 1.322 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | He, Bing Sheng | - |
dc.contributor.author | Xu, Ya | - |
dc.contributor.author | Yuan, Xiao Ming | - |
dc.date.accessioned | 2018-02-01T01:54:04Z | - |
dc.date.available | 2018-02-01T01:54:04Z | - |
dc.date.issued | 2006 | - |
dc.identifier.citation | Computational Optimization and Applications, 2006, v. 35, n. 1, p. 19-46 | - |
dc.identifier.issn | 0926-6003 | - |
dc.identifier.uri | http://hdl.handle.net/10722/250913 | - |
dc.description.abstract | Inspired by the Logarithmic-Quadratic Proximal (LQP) method for variational inequalities, we present a prediction-correction method for structured monotone variational inequalities. Each iteration of the new method consists of a prediction and a correction. Both the predictor and the corrector are obtained easily with tiny computational load. In particular, the LQP system that appears in the prediction is approximately solved under significantly relaxed inexactness restriction. Global convergence of the new method is proved under mild assumptions. In addition, we present a self-adaptive version of the new method that leads to easier implementations. Preliminary numerical experiments for traffic equilibrium problems indicate that the new method is effectively applicable in practice. © 2006 Springer Science + Business Media, LLC. | - |
dc.language | eng | - |
dc.relation.ispartof | Computational Optimization and Applications | - |
dc.subject | Variational inequality | - |
dc.subject | Prediction-correction | - |
dc.subject | Logarithmic-Quadratic Proximal method | - |
dc.title | A Logarithmic-Quadratic proximal prediction-correction method for structured monotone variational inequalities | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s10589-006-6442-4 | - |
dc.identifier.scopus | eid_2-s2.0-33748319447 | - |
dc.identifier.volume | 35 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 19 | - |
dc.identifier.epage | 46 | - |
dc.identifier.eissn | 1573-2894 | - |
dc.identifier.isi | WOS:000240256500002 | - |
dc.identifier.issnl | 0926-6003 | - |