The Boolean quadric polytope: some characteristics, facets and relatives
Mathematical Programming: Series A and B
The cut polytope and the Boolean quadric polytope
Discrete Mathematics
Unconstrained 0–1 optimization and Lagrangian relaxation
Selected papers on First international colloquium on pseudo-boolean optimization and related topics
A linearization procedure for quadratic and cubic mixed-integer problems
Operations Research - Supplement
Persistency in quadratic 0–1 optimization
Mathematical Programming: Series A and B
A lift-and-project cutting plane algorithm for mixed 0-1 programs
Mathematical Programming: Series A and B
Cut-polytopes, Boolean quadratic polytopes and nonnegative quadratic pseudo-Boolean functions
Mathematics of Operations Research
A decomposition method for quadratic zero-one programming
Management Science
Adaptive Memory Tabu Search for Binary Quadratic Programs
Management Science
Solving quadratic (0,1)-problems by semidefinite programs and cutting planes
Mathematical Programming: Series A and B
Evolution and state-of-the-art in integer programming
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Greedy and Local Search Heuristics for Unconstrained Binary Quadratic Programming
Journal of Heuristics
Discrete Applied Mathematics
Cutting planes in integer and mixed integer programming
Discrete Applied Mathematics
Particle Algorithms for Optimization on Binary Spaces
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special Issue on Monte Carlo Methods in Statistics
Approximation algorithms for load-balanced virtual backbone construction in wireless sensor networks
Theoretical Computer Science
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In this paper, we are interested in linearization techniques for the exact solution of the Unconstrained Quadratic (0-1) Problem. Our purpose is to propose ''economical'' linear formulations. We first extend current techniques in a general linearization framework containing many other schemes and propose a new linear formulation. Numerical results comparing classical, Glover's and the new linearization are reported.