Quadratic 0 – 1 optimization using separable underestimators

  title={Quadratic 0 – 1 optimization using separable underestimators},
  author={Christoph Buchheim and Emiliano Traversi},
Binary programs with a quadratic objective function are NP-hard in general, even if the linear optimization problem over the same feasible set is tractable. In this paper, we address such problems by computing quadratic global underestimators of the objective function that are separable but not necessarily convex. Exploiting the binarity constraint on the variables, a minimizer of the separable underestimator over the feasible set can be computed by solving an appropriate linear minimization… CONTINUE READING