Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to emerge from the corresponding valley. In this paper we present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes. In addition, our survey includes parallel implementations and hybrids with other metaheuristics.