Variable Neighbourhood Search

By Pierre Hansen, Nenad Mladenovic. 2003

438 citations recorded by the source corpus.

The Variable Neighbourhood Search (VNS) is a recent metaheuristic for solving optimization problems whose basic idea is systematic change of neighborhood within a local search. In this paper we present basic rules of the VNS and its extensions. We briefly summarize the most relevant applications in Artificial Intelligence. These applications comprise classic tasks, like constraints satisfaction, planning or learning, in addition to computer-assisted discovery and heuristic solution of a variety of optimization problems. Finally we include some reflections on the essential aspects of the metaheuristics and the analysis of the heuristic solution procedures, and the contribution of the works with VNS for these questions.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/bc621f300c3fa27a7bf0c900597a9eadd2198f6b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Maurício Resende
2. Renato F. Werneck

In Computer Vision and Pattern Recognition

1. Maurício Resende
2. Renato F. Werneck

In Signal Processing

1. Maurício Resende
2. Renato F. Werneck

Citations in the corpus

• A Hybrid Heuristic for the p-Median Problem (2004, result): “These strategies, combined with multi-generation path-relinking, can be easily incorporated into traditional metaheuristics with wide application, such as GRASP, tabu search, and VNS.”