Handbook of semidefinite programming : theory, algorithms, and applications
By Henry Wolkowicz, Romesh Saigal, Lieven Vandenberghe. 2000
772 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/88a6f0e69ba4de67b21b288ec12fc43108905097
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Citations in the corpus
- A Sufficient Condition for Global Optimality of Solutions to the Optimal Power Flow Problem (2014, background): “Using and from (5), the first KKT condition of complementarity is (6) The second regards feasibility of the and matrices.”
- Non-Iterative Enhanced SDP Relaxations for Optimal Scheduling of Distributed Energy Storage in Distribution Systems (2017, methodology): “Linear equalities (10b)–(10d) have been used to tighten the SDP relaxation for small-scale general QCQP problems which contain linear equality constraints [28].”
- Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence (2014, unknown): “, [70], [71], [72], [63], [64], [73], [74], [62].”
- Geometric representations of graphs (2014, background): “For more comprehensive studies of issues concerning semidefinite optimization, see [191, 126].”
- Convex relaxation of optimal power flow: A tutorial (2013, unknown): “, [32], [33], [34], [35], [36], [37], [38], [39].”
- A numerical algorithm for block-diagonal decomposition of matrix *-algebras with general irreducible components (2010, background): “[7] introduced a class of group symmetric SDPs, which arise from topology optimization problems of trusses, and derived symmetry of central paths which play a fundamental role in the primal-dual interior-point method [16] for solving them.”
- Application of the Moment-SOS Approach to Global Optimization of the OPF Problem (2013, background): “SDP is a subfield of convex conic optimization [35].”
- Sums of squares of polynomials with rational coefficients (2012, unknown): “The background for the question comes from semidefinite programming (see e.g. [22], [7], [15], [1]) and more specifically, from polynomial optimization.”