Results 31 to 40 of about 1,196 (89)
Open Mathematics, 2018 In this paper, we present an effective algorithm for globally solving quadratic programs with quadratic constraints, which has wide application in engineering design, engineering optimization, route optimization, etc.
Tang Shuai, Chen Yuzhen, Guo Yunrui
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, 2017 Multipoint secant and interpolation methods are effective tools for solving systems of nonlinear equations. They use quasi-Newton updates for approximating the Jacobian matrix.
Burdakov, Oleg, Kamandi, Ahmad
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Improving the linear relaxation of maximum k-cut with semidefinite-based constraints
EURO Journal on Computational Optimization, 2019 We consider the maximum k-cut problem that involves partitioning the vertex set of a graph into k subsets such that the sum of the weights of the edges joining vertices in different subsets is maximized.
VilmarJefté Rodrigues de Sousa +2 more
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On the construction of quadratic models for derivative-free trust-region algorithms
EURO Journal on Computational Optimization, 2017 We consider derivative-free trust-region algorithms based on sampling approaches for convex constrained problems and discuss two conditions on the quadratic models for ensuring their global convergence.
Adriano Verdério +3 more
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Demonstratio MathematicaIt is of strong theoretical significance and application prospects to explore three-block nonconvex optimization with nonseparable structure, which are often modeled for many problems in machine learning, statistics, and image and signal processing.
Zhao Ying, Lan Heng-you, Xu Hai-yang
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EURO Journal on Computational Optimization, 2015 We present O(n2)an integer linear formulation that uses the so-called “distance variables” to solve the quadratic assignment problem (QAP). The formulation performs particularly well for problems with Manhattan distance matrices.
Serigne Gueye, Philippe Michelon
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Interiors of completely positive cones [PDF]
, 2014 A symmetric matrix $A$ is completely positive (CP) if there exists an entrywise nonnegative matrix $B$ such that $A = BB^T$. We characterize the interior of the CP cone.
Fan, Jinyan, Zhou, Anwa
core
Uncontrolled inexact information within bundle methods
EURO Journal on Computational Optimization, 2017 We consider convex non-smooth optimization problems where additional information with uncontrolled accuracy is readily available. It is often the case when the objective function is itself the output of an optimization solver, as for large-scale energy ...
Jérôme Malick +2 more
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A Note on the Convergence of ADMM for Linearly Constrained Convex Optimization Problems
, 2016 This note serves two purposes. Firstly, we construct a counterexample to show that the statement on the convergence of the alternating direction method of multipliers (ADMM) for solving linearly constrained convex optimization problems in a highly ...
Chen, Liang, Sun, Defeng, Toh, Kim-Chuan
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Generalized semi-infinite programming: Numerical aspects [PDF]
, 1998 Generalized semi-infinite optimization problems (GSIP) are considered. It is investigated how the numerical methods for standard semi-infinite programming (SIP) can be extended to GSIP. Newton methods can be extended immediately.
Still, G.J.
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