An intelligent extension of Variable Neighbourhood Search for labelling
  graph problems
  In this paper we describe an extension of the Variable Neighbourhood Search
(VNS) which integrates the basic VNS with other complementary approaches from
machine learning, statistics and experimental algorithmic, in order to produce
high-quality performance and to completely automate the resulting optimization
strategy. The resulting intelligent VNS has been successfully applied to a
couple of optimization problems where the solution space consists of the
subsets of a finite reference set. These problems are the labelled spanning
tree and forest problems that are formulated on an undirected labelled graph; a
graph where each edge has a label in a finite set of labels L. The problems
consist on selecting the subset of labels such that the subgraph generated by
these labels has an optimal spanning tree or forest, respectively. These
problems have several applications in the real-world, where one aims to ensure
connectivity by means of homogeneous connections.
