Computer ScienceMathematics

P. Hansen, N. Mladenovic, R. Todosijević, S. Hanafi

2017.9.1EURO Journal on Computational Optimization

DOI: 10.1007/s13675-016-0075-x

tlooto Summary

This paper presents some of VNS basic schemes as well as several VNS variants deduced from these basic schemes, and includes parallel implementations and hybrids with other metaheuristics.

Abstract

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.

Citation format

HANSEN, P., et al. Variable neighborhood search: Basics and variants. EURO Journal on Computational Optimization, 2017, 5: 423–454.