Results 21 to 30 of about 33,726 (205)
A Customized ADMM Approach for Large-Scale Nonconvex Semidefinite Programming
Mathematics, 2023 We investigate a class of challenging general semidefinite programming problems with extra nonconvex constraints such as matrix rank constraints. This problem has extensive applications, including combinatorial graph problems, such as MAX-CUT and ...
Chuangchuang Sun
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ON OPTIMUM DESIGN OF FRAME STRUCTURES
Acta Polytechnica CTU Proceedings, 2020 Optimization of frame structures is formulated as a non-convex optimization problem, which is currently solved to local optimality. In this contribution, we investigate four optimization approaches: (i) general non-linear optimization, (ii) optimality ...
Marek Tyburec +3 more
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On the Embed and Project Algorithm for the Graph Bandwidth Problem
Mathematics, 2021 The graph bandwidth problem, where one looks for a labeling of graph vertices that gives the minimum difference between the labels over all edges, is a classical NP-hard problem that has drawn a lot of attention in recent decades. In this paper, we focus
Janez Povh
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Proximal-stabilized semidefinite programming [PDF]
Computational Optimization and ApplicationsAbstract A regularized version of the primal-dual Interior Point Method (IPM) for the solution of Semidefinite Programming Problems (SDPs) is presented in this paper. Leveraging on the proximal point method, a novel Proximal Stabilized Interior Point Method for SDP (PS-SDP-IPM) is introduced.
Stefano Cipolla, Jacek Gondzio
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Variational density matrix optimization using semidefinite programming [PDF]
, 2011 We discuss how semidefinite programming can be used to determine the second-order density matrix directly through a variational optimization. We show how the problem of characterizing a physical or N -representable density matrix leads to matrix ...
Boyd +22 more
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Distributionally Robust Joint Chance Constrained Problem under Moment Uncertainty
Journal of Applied Mathematics, 2014 We discuss and develop the convex approximation for robust joint chance constraints under uncertainty of first- and second-order moments. Robust chance constraints are approximated by Worst-Case CVaR constraints which can be reformulated by a ...
Ke-wei Ding
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The algebraic degree of semidefinite programming [PDF]
Mathematical Programming, 2008 Given a generic semidefinite program, specified by matrices with rational entries, each coordinate of its optimal solution is an algebraic number. We study the degree of the minimal polynomials of these algebraic numbers. Geometrically, this degree counts the critical points attained by a linear functional on a fixed rank locus in a linear space of ...
Jiawang Nie +2 more
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A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
Journal of Applied Mathematics, 2013 Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation ...
Xuewen Mu, Yaling Zhang
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Variational Quantum Algorithms for Semidefinite Programming [PDF]
QuantumA semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond.
Dhrumil Patel +2 more
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Semidefinite Programs and Association Schemes [PDF]
Computing, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
GOEMANS, Michel, RENDL, Franz
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