Dual modelling of permutation and injection problems

  • Authors:

  • Brahim Hnich;Barbara M. Smith;Toby Walsh

  • Affiliations:

  • Cork Constraint Computation Center, University College Cork, Cork, Ireland;Cork Constraint Computation Center, University College Cork, Cork, Ireland;Cork Constraint Computation Center, University College Cork, Cork, Ireland

  • Venue:
  • Journal of Artificial Intelligence Research
  • Year:
  • 2004

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Abstract

When writing a constraint program, we have to choose which variables should be the decision variables, and how to represent the constraints on these variables. In many cases, there is considerable choice for the decision variables. Consider, for example, permutation problems in which we have as many values as variables, and each variable takes an unique value. In such problems, we can choose between a primal and a dual viewpoint. In the dual viewpoint, each dual variable represents one of the primal values, whilst each dual value represemts one of the primal variables. Alternatively, by means of channelling constraints to link the primal and dual variables, we can have a combines model with both sets of variables. In this paper, we perform an extensive theoretical and empirical study of such primal, dual and combines models for two classes of problems: permutation problems and injection problems. Our results show that if often be advantageous to use multiple viewpoints, and to have constraints which channel between them to maintain consistency. They also illustrate a general methodology for comparing different constraint models.