Results 11 to 20 of about 6,923,335 (304)
HPIPM: a high-performance quadratic programming framework for model predictive control [PDF]
IFAC-PapersOnLine, 2020 This paper introduces HPIPM, a high-performance framework for quadratic programming (QP), designed to provide building blocks to efficiently and reliably solve model predictive control problems.
G. Frison, M. Diehl
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Preprocessing for quadratic programming [PDF]
Mathematical Programming, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nick I. M. Gould, Philippe L. Toint
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GPU acceleration of ADMM for large-scale quadratic programming [PDF]
J. Parallel Distributed Comput., 2019 The alternating direction method of multipliers (ADMM) is a powerful operator splitting technique for solving structured convex optimization problems.
M. Schubiger, G. Banjac, J. Lygeros
semanticscholar +1 more source
On Linear and Quadratic Two-Stage Transportation Problem
Кібернетика та комп'ютерні технології, 2020 Introduction. When formulating the classical two-stage transportation problem, it is assumed that the product is transported from suppliers to consumers through intermediate points.
Petro Stetsyuk +2 more
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Least Squares Method for Solving Fuzzy LR Interval Algebraic Linear Systems
Fuzzy Information and Engineering, 2022 We first investigate the solvability conditions of fuzzy LR interval algebraic linear systems with fuzzy LR interval coefficient matrix and fuzzy LR interval hand-right vector.
Mehrnoosh Salari +2 more
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Quadratic Convex Reformulations for Semicontinuous Quadratic Programming [PDF]
SIAM Journal on Optimization, 2017 Summary: We consider in this paper a class of semicontinuous quadratic programming problems, which arises in many real-world applications such as production planning, portfolio selection, and subset selection in regression. We build upon the idea of the quadratic convex reformulation approach, i.e., adding to the original objective function an ...
Baiyi Wu +3 more
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Approximating sparse quadratic programs
Theoretical Computer Science, 2022 Given a matrix $A \in \mathbb{R}^{n\times n}$, we consider the problem of maximizing $x^TAx$ subject to the constraint $x \in \{-1,1\}^n$. This problem, called MaxQP by Charikar and Wirth [FOCS'04], generalizes MaxCut and has natural applications in data clustering and in the study of disordered magnetic phases of matter. Charikar and Wirth showed that
Danny Hermelin +3 more
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An SQP Algorithm for Structural Topology Optimization Based on Majorization–Minimization Method
Applied Sciences, 2022 When applying the sequential quadratic programming (SQP) algorithm to topology optimization, using the quasi-Newton methods or calculating the Hessian matrix directly will result in a considerable amount of calculation, making it computationally ...
Weilong Liao, Qiliang Zhang, Huanli Meng
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Representing quadratically constrained quadratic programs as generalized copositive programs [PDF]
Operations Research Letters, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Samuel Burer, Hongbo Dong 0001
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On Solutions of Possibilistic Multi- objective Quadratic Programming Problems [PDF]
International Journal of Supply and Operations Management, 2017 In this paper, a multi- objective quadratic programming (Poss- MOQP) problem with possibilistic variables coefficients matrix in the objective functions is studied.
Hamiden Khalifa
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