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Additional info for [Journal] Surveys in Operations Research and Management Science. Vol. 17. No 2
101] present a bounding procedure, called the roof dual, which replaces each quadratic function with a tight linear under-estimator. Extensions of this are surveyed in Boros and Hammer . 102 S. N. Letchford / Surveys in Operations Research and Management Science 17 (2012) 97–106 • Pardalos and Rodgers  solve unconstrained 0–1 QPs within a branch-and-bound algorithm involving careful preprocessing and computational efficiencies. • Poljak and Wolkowicz  examine several bounding techniques for unconstrained 0–1 QPs, and show that they all give the same bounds.
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Hansen, B. Simeone, Roof duality, complementation and persistency in quadratic 0–1 optimization, Math. Program. 28 (1984) 121–155.  E. L. Hammer, Pseudo-Boolean optimization, Discrete Appl. Math. 123 (2002) 155–225. M. P. Rodgers, Computational aspects of a branch and bound algorithm for quadratic zero–one programming, Computing 45 (2) (1990) 131–144.  S. Poljak, H. Wolkowicz, Convex relaxations of (0, 1)-quadratic programming, Math. Oper. Res. 20 (1995) 550–561.  A.