Results 31 to 40 of about 1,235 (113)
A comparison of four approaches from stochastic programming for large-scale unit-commitment
EURO Journal on Computational Optimization, 2017 In energy management, the unit-commitment problem deals with computing the most cost-efficient production schedule that meets customer load, while satisfying the operational constraints of the units.
Wim van Ackooij
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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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A parametric linearizing approach for quadratically inequality constrained quadratic programs
Open Mathematics, 2018 In this paper we propose a new parametric linearizing approach for globally solving quadratically inequality constrained quadratic programs. By utilizing this approach, we can derive the parametric linear programs relaxation problem of the investigated ...
Jiao Hongwei, Chen Rongjiang
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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
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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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, 2014 We present a multidimensional optimization problem that is formulated and solved in the tropical mathematics setting. The problem consists of minimizing a nonlinear objective function defined on vectors over an idempotent semifield by means of a ...
A. Tharwat +22 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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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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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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