Abstracting numeric constraints with Boolean functions

Abstracting numeric constraints with Boolean functions

Representing Boolean Functions as Linear Pseudo-Boolean Constraints

A linear pseudo-Boolean constraint (LPB) is an expression of the form a1 · l1 + . . .+am · lm ≥ d, where each li is a literal (it assumes the value 1 or 0 depending on whether a propositional variable xi is true or false) and the a1, . . . , am, d are natural numbers. The formalism can be viewed as a generalisation of a propositional clause. It has been said that LPBs can be used to represent B...

Abstracting Soft Constraints

ing Soft Constraint S. Bistarelli1, P. Codognet2, Y. Georget3, F. Rossi4 1: Universit a di Pisa, Dipartimento di Informatica, Corso Italia 40, 56125 Pisa, Italy. E-mail: [email protected] 2: University of Paris 6, LIP6, case 169, 4, Place Jussieu, 75 252 Paris Cedex 05, France. E-mail: [email protected] 3: INRIA Rocquencourt, BP 105, 78153 Le Chesnay, France. E-mail: [email protected]...

Boolean surfaces with shape constraints

In this paper, we present a new method for the construction of parametric surfaces reproducing an object from a set of spatial data. We adopt a hybrid scheme, based on the Boolean sum of variable degree spline operators, which both interpolate a set of grid lines and approximate the data. As usual the variable degrees can be chosen to satisfy proper shape constraints. c © 2007 Elsevier Ltd. All...

Abstracting soft constraints: Framework, properties, examples