By the same authors

A framework for constraint based local search using ESSENCE

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Author(s)

  • Ozgur Akgun
  • Saad Wasim A Attieh
  • Ian Philip Gent
  • Christopher Anthony Jefferson
  • Ian James Miguel
  • Peter William Nightingale
  • András Z. Salamon
  • Patrick Spracklen
  • James Patrick Wetter

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Publication details

Title of host publicationProceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
DateAccepted/In press - 16 Apr 2018
DatePublished (current) - 13 Jul 2018
Pages1242-1248
Number of pages7
PublisherInternational Joint Conferences on Artificial Intelligence
EditorsJérôme Lang
Original languageEnglish
ISBN (Electronic)9780999241127

Abstract

Structured Neighbourhood Search (SNS) is a framework for constraint-based local search for problems expressed in the Essence abstract constraint specification language. The local search explores a structured neighbourhood, where each state in the neighbourhood preserves a high level structural feature of the problem. SNS derives highly structured problem-specific neighbourhoods automatically and directly from the features of the ESSENCE specification of the problem. Hence, neighbourhoods can represent important structural features of the problem, such as partitions of sets, even if that structure is obscured in the low-level input format required by a constraint solver. SNS expresses each neighbourhood as a constrained optimisation problem, which is solved with a constraint solver. We have implemented SNS, together with automatic generation of neighbourhoods for high level structures, and report high quality results for several optimisation problems.

Bibliographical note

Funding: UK Engineering & Physical Sciences Research Council (EPSRC) grants EP/P015638/1 and EP/P026842/1.

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