The Rules of Constraint Modelling
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 109-115.
Abstract
Many and diverse combinatorial problems have been solved successfully using finite-domain constraint programming. However, to apply constraint programming to a particular domain, the problem must first be modelled as a constraint satisfaction or optimisation problem. Since constraints provide a rich language, typically many alternative models exist. Formulating a good model therefore requires a great deal of expertise. This paper describes CONJURE, a system that refines a specification of a problem in the abstract constraint specification language ESSENCE into a set of alternative constraint models. Refinement is compositional: alternative constraint models are generated by composing refinements of the components of the specification. Experimental results demonstrate that CONJURE is able to generate a variety of models for practical problems from their ESSENCE specifications.
@inproceedings{ijcai2005p232,
title = {The Rules of Constraint Modelling},
author = {Frisch, Alan M. and Jefferson, Christopher and Hernández, Bernadette Martínez and Miguel, Ian},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {109--115},
year = {2005},
url = {https://ijcai.org/proceedings/2005/232},
}
TY - CPAPER TI - The Rules of Constraint Modelling AU - Frisch, Alan M. AU - Jefferson, Christopher AU - Hernández, Bernadette Martínez AU - Miguel, Ian T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 109 EP - 115 UR - https://ijcai.org/proceedings/2005/232 ER -Copied
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