Large Neighborhood Search
By David Pisinger, Stefan Røpke. Handbook of Metaheuristics, 2018
598 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/bc9580c4bf5874b6e14f82b9c8a7ade208d90a49
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Stefan Røpke
- David Sacramento
- David Pisinger
- André Schidler
- Stefan Szeider
- Gilbert Laporte
- Jean-François Cordeau
- Michael Schneider
In Industrial and Manufacturing Engineering
- Stefan Røpke
- David Pisinger
- David Sacramento
- André Schidler
- Stefan Szeider
- Amin Mousavi
- Shi Qiang Liu
- Erhan Kozan
In Management Science and Operations Research
Citations in the corpus
- An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones (2019, methodology): “The ALNS framework has been applied to many other VRP variants in the past and is often easy to adapt to new problems (Pisinger and Ropke, 2010).”
- SAT-based Decision Tree Learning for Large Data Sets (2021, methodology): “SLIM is similar to Large Neighborhood Search (Pisinger and Ropke 2010), where SLIM distinguishes itself by combining a structurally constrained notion of neighbourhood with a complete method (SAT).”
- The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations (2016, unknown): “A general introduction to LNS and its variants and extensions can be found in Pisinger and Ropke (2010).”
- Open-pit block sequencing optimization: A mathematical model and solution technique (2016, background): “According to this mechanism, a part of the solution is destroyed and then a repair technique rebuilds the solution (Pisinger and Ropke 2010).”