Variable neighbourhood search: methods and applications
By Pierre Hansen, Nenad Mladenovic, José Andrés Moreno-Pérez. Annals of Operations Research, 2010
592 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Industrial and Manufacturing Engineering, Organizational Behavior and Human Resource Management
View Paper: https://www.semanticscholar.org/paper/112063e22eea8820ce5cdd2d409aa2f5cd93bee1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- S. Bonhomme
- Patrick Siarry
- Berat Dogan
- Ilhem Boussaïd
- Julien Lepagnot
- Tamer Ölmez
- Elena Manresa
- Seyedali Mirjalili
In Industrial and Manufacturing Engineering
In Organizational Behavior and Human Resource Management
Citations in the corpus
- A new metaheuristic for numerical function optimization: Vortex Search algorithm (2015, background): “Single-solution based metaheuristics are also known as trajectory methods, which are based on a single solution at any time and comprise local search-based metaheuristics such as Simulated Annealing (SA) [30,9], Tabu Search (TS) [18], Iterated Local Search (ILS) [33], Guided Local Search (GLS) [3], ”
- Grouped Patterns of Heterogeneity in Panel Data (2015, methodology): “The Variable Neighborhood Search (VNS) method has been pointed out as the state-of-the-art heuristics to solve the minimum sum-of-squares partitioning problem (Hansen and Mladenović, 2001, Hansen et al., 2010).”
- A survey on optimization metaheuristics (2013, methodology): “Recent surveys of VNS and its extensions are available in [122,123].”
- Variable neighborhood search: basics and variants (2017, unknown): “For other VNS hybridization we refer the reader to [27].”