A framework for constraint based local search using ESSENCE
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.
Citation
Akgun , O , Attieh , S W A , Gent , I P , Jefferson , C A , Miguel , I J , Nightingale , P W , Salamon , A Z , Spracklen , P & Wetter , J P 2018 , A framework for constraint based local search using ESSENCE . in J Lang (ed.) , Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence . International Joint Conferences on Artificial Intelligence , pp. 1242-1248 , 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence , Stockholm , Sweden , 13/07/18 . https://doi.org/10.24963/ijcai.2018/173 conference
Publication
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Type
Conference item
Rights
Copyright © 2018, IJCAI. This work has been made available online in accordance with the publisher’s policies. This is the final published version of the work, which was originally published at https://doi.org/10.24963/ijcai.2018/173
Description
Funding: UK Engineering & Physical Sciences Research Council (EPSRC) grants EP/P015638/1and EP/P026842/1.Collections
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
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