Global optimization algorithms for linearly constrained indefinite quadratic problems

AbstractIn this paper we consider the problem of finding the constrained global optimum of an indefinite quadratic function. Since such a function may have many local optima, finding the global optimum is a computationally difficult problem. We give an overview of the most important methods used, which include Benders decomposition, concave programming approaches, enumerative techniques, and bilinear programming