Variable neighborhood search: basics and variants

By Pierre Hansen, Nenad Mladenovic, R. Todosijević, S. Hanafi. EURO Journal on Computational Optimization, 2017

350 citations recorded by the source corpus.

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 escape 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, the paper includes parallel implementations and hybrids with other metaheuristics.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/77c4fab5a1f2f1ba571cf51fd8ab1bbc33747fc9