Results 11 to 20 of about 1,126 (142)
IEEE Access, 2021 There are the transmission loss of the electric power network, the delay and loss of the heating network, the insufficient utilization of flexible resources such as energy storage in the integrated electric-heat system, which may lead to the imbalance of
Xinrui Liu +3 more
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IEEE Open Journal of the Communications Society, 2021 Full-duplex amplify-and-forward multiple-input multiple-output relaying has been the focus of several recent studies, due to the potential for achieving a higher spectral efficiency and lower latency, together with inherent processing simplicity. However,
Omid Taghizadeh +3 more
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EURO Journal on Computational Optimization, 2021 Adjustable robust optimization allows for some variables to depend upon the uncertain data after its realization. However, the uncertainty is often not revealed exactly.
V. Jeyakumar, G. Li, D. Woolnough
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Lifted Convex Quadratic Programming
CoRR, 2016 Symmetry is the essential element of lifted inference that has recently demon- strated the possibility to perform very efficient inference in highly-connected, but symmetric probabilistic models models. This raises the question, whether this holds for optimisation problems in general.
Martin Mladenov +2 more
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On convex relaxations for quadratically constrained quadratic programming [PDF]
Mathematical Programming, 2012 A quadratically constrained (possibly non-convex) quadratic programming problem is considered. The efficiency, for this problem, of several known convex underestimating methods is analyzed. The underestimates, obtained by means of the considered methods, are ranked according to their tightness.
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The Scientific World Journal, 2013 Recently, the existed proximal gradient algorithms had been used to solve non-smooth convex optimization problems. As a special nonsmooth convex problem, the singly linearly constrained quadratic programs with box constraints appear in a wide range of ...
Congying Han +3 more
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On the minimum-norm solution of convex quadratic programming [PDF]
RAIRO - Operations Research, 2021 We discuss some basic concepts and present a numerical procedure for finding the minimum-norm solution of convex quadratic programs (QPs) subject to linear equality and inequality constraints. Our approach is based on a theorem of alternatives and on a convenient characterization of the solution set of convex QPs.
Saeed Ketabchi +2 more
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An efficient beamforming design for multipair full-duplex relaying systems
ICT Express, 2017 We consider a decode-and-forward full-duplex relaying system for multiple pairs of users. Our objective is to maximize the minimum achievable rate for all user pairs under the transmit power constraints.
Hyeon Min Kim +2 more
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Journal of the Mechanical Behavior of Materials, 2015 This paper introduces constructing convex-relaxed programs for nonconvex optimization problems. Branch-and-bound algorithms are convex-relaxation-based techniques.
Keller André A.
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Expanding the reach of quantum optimization with fermionic embeddings [PDF]
QuantumQuadratic programming over orthogonal matrices encompasses a broad class of hard optimization problems that do not have an efficient quantum representation.
Andrew Zhao, Nicholas C. Rubin
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