Neigborhood Selection in Variable Neighborhood Search
  Variable neighborhood search (VNS) is a metaheuristic for solving
optimization problems based on a simple principle: systematic changes of
neighborhoods within the search, both in the descent to local minima and in the
escape from the valleys which contain them. Designing these neighborhoods and
applying them in a meaningful fashion is not an easy task. Moreover, an
appropriate order in which they are applied must be determined. In this paper
we attempt to investigate this issue. Assume that we are given an optimization
problem that is intended to be solved by applying the VNS scheme, how many and
which types of neighborhoods should be investigated and what could be
appropriate selection criteria to apply these neighborhoods. More specifically,
does it pay to "look ahead" (see, e.g., in the context of VNS and GRASP) when
attempting to switch from one neighborhood to another?
