Enhancing RLT-based relaxations for polynomial programming problems via a new class of \(v\)-semidefinite cuts

DOI10.1007/s10589-011-9425-zzbMath1250.90092OpenAlexW2027109023MaRDI QIDQ453612

Jitamitra Desai, Evrim Dalkiran, Hanif D. Sherali

Publication date: 27 September 2012

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-011-9425-z

zbMATH Keywords

global optimizationsemidefinite programmingreformulation-linearization techniqueBARONpolynomial programssemidefinite cutsGloptiPoly

Mathematics Subject Classification ID

Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Nonlinear programming (90C30)

Related Items

RLT-POS: reformulation-linearization technique-based optimization software for solving polynomial programming problems, A global optimization framework for distributed antenna location in CDMA cellular networks, Theoretical filtering of RLT bound-factor constraints for solving polynomial programming problems to global optimality, Partial Lasserre relaxation for sparse Max-Cut, Branch and cut algorithms for detecting critical nodes in undirected graphs, Computational advances in polynomial optimization: RAPOSa, a freely available global solver, Reduced RLT representations for nonconvex polynomial programming problems, Combined bound-grid-factor constraints for enhancing RLT relaxations for polynomial programs, Extended formulations for convex envelopes

Uses Software

• BARON
• SNOPT
• SeDuMi
• GloptiPoly

Cites Work

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