Results 31 to 40 of about 174 (149)
Unsupervised and supervised data classification via nonsmooth and global optimization
, 2003 Clustering, classification, cluster function, nonsmooth optimization, global optimization, 65K05, 90C26, 90C30, 90C90,
A. Bagirov +7 more
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Using truncated conjugate gradient method in trust-region method with two subproblems and backtracking line search [PDF]
, 2010 A trust-region method with two subproblems and backtracking line search for solving unconstrained optimization is proposed. At every iteration, we use the truncated conjugate gradient method or its variation to solve one of the two subproblems ...
Mingyun Tang +3 more
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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
doaj +1 more source
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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On generalized semi-infinite programming
, 2006 Generalized semi-infinite programming, extended Mangasarian-Fromovitz, Kuhn-Tucker and Abadie constraint qualification, Fritz-John condition, first and second order optimality conditions, optimal value function, directional differentiability, second ...
Alfredo Gomez, J +3 more
core +1 more source
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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Demonstratio MathematicaIn this paper, a modified Rivaie-Mohd-Ismail-Leong (RMIL) conjugate gradient-based projection algorithm for constrained nonlinear equations is proposed, which integrates projection techniques and line search approaches to enhance solution accuracy and ...
Wang Kai, Li Dandan, Wang Songhua
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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
doaj +1 more source