Combined bound-grid-factor constraints for enhancing RLT relaxations for polynomial programs

DOI10.1007/s10898-010-9639-0zbMath1229.90145OpenAlexW2034063035MaRDI QIDQ652688

Evrim Dalkiran, Hanif D. Sherali

Publication date: 15 December 2011

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-010-9639-0

zbMATH Keywords

global optimizationfactorable programscutting planesvalid inequalitiesreformulation-linearization technique (RLT)BARONpolynomial programsgrid-factor constraints

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items

RLT-POS: reformulation-linearization technique-based optimization software for solving polynomial programming problems, Theoretical filtering of RLT bound-factor constraints for solving polynomial programming problems to global optimality, Reduced RLT representations for nonconvex polynomial programming problems, Global optimization of general nonconvex problems with intermediate polynomial substructures

Uses Software

• BARON
• SNOPT

Cites Work

• Enhancing RLT-based relaxations for polynomial programming problems via a new class of \(v\)-semidefinite cuts
• Investigation of selection strategies in branch and bound algorithm with simplicial partitions and combination of Lipschitz bounds
• Dual quadratic estimates in polynomial and Boolean programming
• A global optimization algorithm for polynomial programming problems using a reformulation-linearization technique
• Comparison of two reformulation-linearization technique based linear programming relaxations for polynomial programming problems
• New reformulation linearization/convexification relaxations for univariate and multivariate polynomial programming problems
• A polyhedral branch-and-cut approach to global optimization
• Global optimization of mixed-integer nonlinear programs: a theoretical and computational study
• Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems
• SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
• Global optimization of nonconvex factorable programming problems