---
title: "The Rules of Constraint Modelling"
authors:
  - "Alan M. Frisch"
  - "Christopher Jefferson"
  - "Bernadette Martínez Hernández"
  - "Ian Miguel"
doi: ""
url: "https://ijcai.org/proceedings/2005/232"
pdf: "https://ijcai.org/proceedings/2005/0232.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "109-115"
track: ""
keywords:
---

# The Rules of Constraint Modelling

Alan M. Frisch, Christopher Jefferson, Bernadette Martínez Hernández, Ian Miguel

*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.