A Framework for Constraint Based Local Search using Essence

Author:

Akgün Özgür1,Attieh Saad1,Gent Ian P.1,Jefferson Christopher1,Miguel Ian1,Nightingale Peter1,Salamon András Z.1,Spracklen Patrick1,Wetter James1

Affiliation:

1. School of Computer Science, University of St Andrews, UK

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.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research Report on Automatic Synthesis of Local Search Neighborhood Operators;Electronic Proceedings in Theoretical Computer Science;2019-09-19

2. Generating Local Search Neighborhood with Synthesized Logic Programs;Electronic Proceedings in Theoretical Computer Science;2019-09-19

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