Fast algorithm for singly linearly constrained quadratic programs with box-like constraints.
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| Title: | Fast algorithm for singly linearly constrained quadratic programs with box-like constraints. |
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| Authors: | Liu, Meijiao1 liulmj@gmail.com, Liu, Yong-Jin1 yjliu@sau.edu.cn |
| Source: | Computational Optimization & Applications. Mar2017, Vol. 66 Issue 2, p309-326. 18p. |
| Subjects: | Quadratic programming, Secant function, Algorithms, Mathematical variables, Linear equations |
| Abstract: | This paper focuses on a singly linearly constrained class of convex quadratic programs with box-like constraints. We propose a new fast algorithm based on parametric approach and secant approximation method to solve this class of quadratic problems. We design efficient implementations for our proposed algorithm and compare its performance with two state-of-the-art standard solvers called Gurobi and Mosek. Numerical results on a variety of test problems demonstrate that our algorithm is able to efficiently solve the large-scale problems with the dimension up to fifty million and it substantially outperforms Gurobi and Mosek in terms of the running time. [ABSTRACT FROM AUTHOR] |
| Copyright of Computational Optimization & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 121042103 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Fast algorithm for singly linearly constrained quadratic programs with box-like constraints. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Meijiao%22">Liu, Meijiao</searchLink><relatesTo>1</relatesTo><i> liulmj@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yong-Jin%22">Liu, Yong-Jin</searchLink><relatesTo>1</relatesTo><i> yjliu@sau.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computational+Optimization+%26+Applications%22">Computational Optimization & Applications</searchLink>. Mar2017, Vol. 66 Issue 2, p309-326. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Quadratic+programming%22">Quadratic programming</searchLink><br /><searchLink fieldCode="DE" term="%22Secant+function%22">Secant function</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+variables%22">Mathematical variables</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+equations%22">Linear equations</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper focuses on a singly linearly constrained class of convex quadratic programs with box-like constraints. We propose a new fast algorithm based on parametric approach and secant approximation method to solve this class of quadratic problems. We design efficient implementations for our proposed algorithm and compare its performance with two state-of-the-art standard solvers called Gurobi and Mosek. Numerical results on a variety of test problems demonstrate that our algorithm is able to efficiently solve the large-scale problems with the dimension up to fifty million and it substantially outperforms Gurobi and Mosek in terms of the running time. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computational Optimization & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=121042103 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10589-016-9863-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 309 Subjects: – SubjectFull: Quadratic programming Type: general – SubjectFull: Secant function Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Mathematical variables Type: general – SubjectFull: Linear equations Type: general Titles: – TitleFull: Fast algorithm for singly linearly constrained quadratic programs with box-like constraints. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Meijiao – PersonEntity: Name: NameFull: Liu, Yong-Jin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 09266003 Numbering: – Type: volume Value: 66 – Type: issue Value: 2 Titles: – TitleFull: Computational Optimization & Applications Type: main |
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