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Dependency-Curated Large Neighbourhood Search

Authors Frej Knutar Lewander , Pierre Flener , Justin Pearson

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Subject Classification

ACM Subject Classification
  • Computing methodologies → Heuristic function construction
Keywords
  • Combinatorial Optimisation
  • Large Neighbourhood Search (LNS)
  • Constraint-Based Local Search (CBLS)

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Abstract

In large neighbourhood search (LNS), an incumbent initial solution is incrementally improved by selecting a subset of the variables, called the freeze set, and fixing them to their values in the incumbent solution, while a value for each remaining variable is found and assigned via solving (such as constraint programming-style propagation and search). Much research has been performed on finding generic and problem-specific LNS selection heuristics that select freeze sets that lead to high-quality solutions. In constraint-based local search (CBLS), the relations between the variables via the constraints are fundamental and well-studied, as they capture dependencies of the variables. In this paper, we apply these ideas from CBLS to the LNS context, presenting the novel dependency curation scheme, which exploits them to find a low-cardinality set of variables that the freeze set of any selection heuristic should be a subset of. The scheme often improves the overall performance of generic selection heuristics. Even when the scheme is used with a naïve generic selection heuristic that selects random freeze sets, the performance is competitive with more elaborate generic selection heuristics.

Cite As Get BibTex

Frej Knutar Lewander, Pierre Flener, and Justin Pearson. Dependency-Curated Large Neighbourhood Search. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 20:1-20:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.CP.2025.20

Author Details

Frej Knutar Lewander
  • Department of Information Technology, Uppsala University, Sweden
Pierre Flener
  • Department of Information Technology, Uppsala University, Sweden
Justin Pearson
  • Department of Information Technology, Uppsala University, Sweden

Funding

Supported by grant 2018-04813 of the Swedish Research Council (VR).

Acknowledgements

We thank Mikael Zayenz Lagerkvist and Dexter Leander for their help with the Gecode implementation.

Supplementary Materials

References

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