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.
Cite
Text
Akgün et al. "A Framework for Constraint Based Local Search Using Essence." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/173Markdown
[Akgün et al. "A Framework for Constraint Based Local Search Using Essence." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/akgun2018ijcai-framework/) doi:10.24963/IJCAI.2018/173BibTeX
@inproceedings{akgun2018ijcai-framework,
title = {{A Framework for Constraint Based Local Search Using Essence}},
author = {Akgün, Özgür and Attieh, Saad and Gent, Ian P. and Jefferson, Christopher and Miguel, Ian and Nightingale, Peter and Salamon, András Z. and Spracklen, Patrick and Wetter, James},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {1242-1248},
doi = {10.24963/IJCAI.2018/173},
url = {https://mlanthology.org/ijcai/2018/akgun2018ijcai-framework/}
}