An Analysis of Arithmetic Constraints on Integer Intervals

Arithmetic constraints on integer intervals are supported in many constraint programming systems. We study here a number of approaches to implement constraint propagation for these constraints. To describe them we introduce integer interval arithmetic. Each approach is explained using appropriate proof rules that reduce the variable domains. We compare these approaches using a set of benchmarks. For the most promising approach we provide results that characterize the effect of constraint propagation. This is a full version of our earlier paper, cs.PL/0403016.Comment: 44 pages, to appear in 'Constraints' journa

Improving Linear Constraint Propagation By Changing Constraint Representation

Propagation based nite domain solvers provide a general mechanism for solving combinatorial problems. Dierent propagation methods can be used in conjunction by communicating through the domains of shared variables. The exibility that this entails has been an important factor in the success of propagation based solving for solving hard combinatorial problems. In this paper we investigate how linear integer constraints should be represented in order that propagation can determine strong domain information. We identify two kinds of substitution which can improve propagation solvers, and can never weaken the domain information. This leads us to an alternate approach to propagation based solving where the form of constraints is modi ed by substitution as computation progresses. We compare and contrast a solver using substitution against an indexical based solver, the current method of choice for implementing propagation based constraint solvers, identifying the relative advantages and disadvantages of the two approaches. In doing so we investigate a number of choices in propagation solvers and their eects on a suite of benchmarks