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检索条件"主题词=Convex quadratic programming"
134 条 记 录,以下是1-10 订阅
排序:
Bi-affine scaling iterative method for convex quadratic programming with bound constraints
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MATHEMATICS AND COMPUTERS IN SIMULATION 2024年 226卷 373-382页
作者: Yue, Hongwei Shen, Peiping North China Univ Water Resources & Elect Power Sch Math & Stat Zhengzhou Peoples R China
To solve general convex quadratic programming problems with bound constraints, this paper proposes a new interior point iterative method that is easy to be implemented. The method exhibits a simple and sufficiently sm... 详细信息
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A new full-Newton step feasible interior point method for convex quadratic programming
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OPTIMIZATION 2024年 第5期73卷 1571-1588页
作者: Boudjellal, Nawel Benterki, Djamel Univ Ferhat Abbas Setif 1 Fac Sci Dept Math Lab Fundamental & Numer Math Setif Algeria Univ Akli Mohand Oulhadj Bouira Bouira Algeria
In this paper, we propose and analyse a new full-Newton step feasible interior point method for convex quadratic programming. The basic idea of this method is to replace a complementarity condition by a non-negative v... 详细信息
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IPRQP: a primal-dual interior-point relaxation algorithm for convex quadratic programming
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JOURNAL OF GLOBAL OPTIMIZATION 2023年 第2-4期87卷 1027-1053页
作者: Zhang, Rui-Jin Liu, Xin-Wei Dai, Yu-Hong Chinese Acad Sci Acad Math & Syst Sci Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China Hebei Univ Technol Inst Math Tianjin Peoples R China
We propose IPRQP, an enhanced primal-dual interior-point relaxation method (IPRM), for solving convex quadratic programming. This method is based on a smoothing barrier augmented Lagrangian function for convex quadrat... 详细信息
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QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional convex quadratic programming Problems
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ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE 2022年 第3期48卷 1-27页
作者: Liang, Ling Li, Xudong Sun, Defeng Toh, Kim-Chuan Natl Univ Singapore Dept Math 10 Lower Kent Ridge Rd Singapore 119076 Singapore Fudan Univ Sch Data Sci Shanghai Peoples R China Hong Kong Polytech Univ Dept Appl Math Hung Hom Hong Kong Peoples R China Natl Univ Singapore Inst Operat Res & Analyt 10 Lower Kent Ridge Rd Singapore 119076 Singapore
In this article, we aim to solve high-dimensional convex quadratic programming (QP) problems with a large number of quadratic terms, linear equality, and inequality constraints. To solve the targeted QP problem to a d... 详细信息
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An efficient arc-search interior-point algorithm for convex quadratic programming with box constraints
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NUMERICAL ALGORITHMS 2022年 第2期91卷 711-748页
作者: Yang, Yaguang US NRC Off Res 11555 Rockville Pike Rockville MD 20852 USA
This paper proposes an arc-search interior-point algorithm for convex quadratic programming with box constraints. The problem has many applications, such as optimal control with actuator saturation. It is shown that a... 详细信息
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An interior point-proximal method of multipliers for convex quadratic programming
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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2021年 第2期78卷 307-351页
作者: Pougkakiotis, Spyridon Gondzio, Jacek Univ Edinburgh Edinburgh Midlothian Scotland
In this paper we combine an infeasible Interior Point Method (IPM) with the Proximal Method of Multipliers (PMM). The resulting algorithm (IP-PMM) is interpreted as a primal-dual regularized IPM, suitable for solving ... 详细信息
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A primal-dual interior point algorithm for convex quadratic programming based on a new parametric kernel function
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OPTIMIZATION 2021年 第8期70卷 1703-1724页
作者: Boudjellal, N. Roumili, H. Benterki, D. J. Univ Ferhat Abbas Setif 1 Fac Sci Lab Fundamental & Numer Math Dept Math Setif Algeria
In this paper, we deal with a polynomial primal-dual interior-point algorithm for solving convex quadratic programming based on a new parametric kernel function with an exponential barrier term. The proposed kernel fu... 详细信息
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Towards an efficient augmented Lagrangian method for convex quadratic programming
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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2020年 第3期76卷 767-800页
作者: Bueno, Luis Felipe Haeser, Gabriel Santos, Luiz-Rafael Univ Fed Sao Paulo Inst Sci & Technol Sao Jose Dos Campos SP Brazil Univ Sao Paulo Dept Appl Math Sao Paulo SP Brazil Univ Fed Santa Catarina Dept Math Blumenau SC Brazil
Interior point methods have attracted most of the attention in the recent decades for solving large scale convex quadratic programming problems. In this paper we take a different route as we present an augmented Lagra... 详细信息
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Extension of Eaves Theorem for Determining the Boundedness of convex quadratic programming Problems
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TAIWANESE JOURNAL OF MATHEMATICS 2020年 第6期24卷 1551-1563页
作者: Huu-Quang Nguyen Van-Bong Nguyen Ruey-Lin Sheu Vinh Univ Sch Nat Sci Educ Dept Math Vinh Nghe An Vietnam Natl Cheng Kung Univ Dept Math Tainan Taiwan Tay Nguyen Univ Dept Math Istanbul Vietnam
It is known that the boundedness of a convex quadratic function over a convex quadratic constraint (c-QP) can be determined by algorithms. In 1985, Terlaky transformed the said boundedness problem into an l(p) program... 详细信息
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A constraint-reduced MPC algorithm for convex quadratic programming, with a modified active set identification scheme
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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2019年 第3期72卷 727-768页
作者: Laiu, M. Paul Tits, Andre L. Oak Ridge Natl Lab Comp Sci & Math Div Computat & Appl Math Grp Oak Ridge TN 37831 USA Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA Univ Maryland Syst Res Inst College Pk MD 20742 USA
A constraint-reduced Mehrotra-predictor-corrector algorithm for convex quadratic programming is proposed. (At each iteration, such algorithms use only a subset of the inequality constraints in constructing the search ... 详细信息
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