Results 21 to 30 of about 1,126 (142)
Global solution of non-convex quadratically constrained quadratic programs [PDF]
The class of mixed-integer quadratically constrained quadratic programs (QCQP) consists of minimizing a quadratic function under quadratic constraints where the variables could be integer or continuous. On a previous paper we introduced a method called MIQCR for solving QCQPs with the following restriction: all quadratic sub-functions of purely ...
Elloumi, Sourour, Lambert, Amélie
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A Convex Approximation for Optimal DER Scheduling on Unbal-anced Power Distribution Networks
The increase of solar photovoltaic penetration poses several challenges for distribution network operation, mainly because such high penetration might cause reliability problems like protection malfunctioning, accelerated decay of voltage regulators and ...
Iván David Serna-Suárez
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Semidefinite Programming for Approximate Maximum Likelihood Sinusoidal Parameter Estimation
We study the convex optimization approach for parameter estimation of several sinusoidal models, namely, single complex/real tone, multiple complex sinusoids, and single two-dimensional complex tone, in the presence of additive Gaussian noise.
Kenneth W. K. Lui, H. C. So
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Ellipsoid Bounds for Convex Quadratic Integer Programming
Summary: Solving convex quadratic integer minimization problems by a branch-and-bound algorithm requires tight lower bounds on the optimal objective value. To obtain such dual bounds, we follow the approach of \textit{C. Buchheim} et al. [Math. Program. 135, No.
Christoph Buchheim +2 more
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An infeasible interior point methods for convex quadratic problems
In this paper, we deal with the study and implementation of an infeasible interior point method for convex quadratic problems (CQP). The algorithm uses a Newton step and suitable proximity measure for approximately tracing the central path and ...
Hayet Roumili, Nawel Boudjellal
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Convex quadratic and semidefinite programming relaxations in scheduling [PDF]
We consider the problem of scheduling unrelated parallel machines subject to release dates so as to minimize the total weighted completion time of jobs. The main contribution of this paper is a provably good convex quadratic programming relaxation of strongly polynomial size for this problem. The best previously known approximation algorithms are based
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Parallel Constraint Distribution in Convex Quadratic Programming [PDF]
We consider convex quadratic programs with large numbers of constraints. We distribute these constraints among several parallel processors and modify the objective function for each of these subproblems with Lagrange multiplier information from the other processors.
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An algorithm for indefinite quadratic programming with convex constraints [PDF]
The authors present a new branch-and-bound method for solving the following problem: \[ \min(f(x,y)=p^ T x+x^ T My+q^ T y: (x,y)\in S), \] where \(S\subset R^ n\times R^ m\) is a closed convex non-empty set, \(p\in R^ n\) and \(q\in R^ m\) are given vectors and \(M\) is a given \(n\times m\) matrix.
Muu, Lê D., Oettli, Werner
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Designing Camera Networks by Convex Quadratic Programming [PDF]
AbstractIn this paper, we study the problem of automatic camera placement for computer graphics and computer vision applications. We extend the problem formulations of previous work by proposing a novel way to incorporate visibility constraints and camera‐to‐camera relationships.
Bernard Ghanem, Yuanhao Cao, Peter Wonka
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Process industries increasingly face large-scale nonlinear programs with high dimensionality and tight constraints. This study reports on the design and implementation of a reduced-space sequential quadratic programming (RSQP) solver for such settings ...
Chuanlei Zhao +5 more
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