License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2023.23
URN: urn:nbn:de:0030-drops-190605
URL: https://drops.dagstuhl.de/opus/volltexte/2023/19060/
Go to the corresponding LIPIcs Volume Portal


Kuroiwa, Ryo ; Beck, J. Christopher

Large Neighborhood Beam Search for Domain-Independent Dynamic Programming

pdf-format:
LIPIcs-CP-2023-23.pdf (2 MB)


Abstract

Large neighborhood search (LNS) is an algorithmic framework that removes a part of a solution and performs search in the induced search space to find a better solution. While LNS shows strong performance in constraint programming, little work has combined LNS with state space search. We propose large neighborhood beam search (LNBS), a combination of LNS and state space search. Given a solution path, LNBS removes a partial path between two states and then performs beam search to find a better partial path. We apply LNBS to domain-independent dynamic programming (DIDP), a recently proposed generic framework for combinatorial optimization based on dynamic programming. We empirically show that LNBS finds better quality solutions than a state-of-the-art DIDP solver in five out of nine benchmark problem types with a total of 8570 problem instances. In particular, LNBS shows a significant improvement over the existing state-of-the-art DIDP solver in routing and scheduling problems.

BibTeX - Entry

@InProceedings{kuroiwa_et_al:LIPIcs.CP.2023.23,
  author =	{Kuroiwa, Ryo and Beck, J. Christopher},
  title =	{{Large Neighborhood Beam Search for Domain-Independent Dynamic Programming}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{23:1--23:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/19060},
  URN =		{urn:nbn:de:0030-drops-190605},
  doi =		{10.4230/LIPIcs.CP.2023.23},
  annote =	{Keywords: Large Neighborhood Search, Dynamic Programming, State Space Search, Combinatorial Optimization}
}

Keywords: Large Neighborhood Search, Dynamic Programming, State Space Search, Combinatorial Optimization
Collection: 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)
Issue Date: 2023
Date of publication: 22.09.2023
Supplementary Material: Software (Source Code): https://github.com/domain-independent-dp/didp-rs/releases/tag/lnbs-cp23 archived at: https://archive.softwareheritage.org/swh:1:dir:b531b883c4c9eda4e0452fe801a5b50f6a3970cc


DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI