Randomly-generated binary constraint satisfaction problems go through a phase transition
as the constraint tightness varies. Loose constraints give an 'easy-soluble'region, where …

Constraint satisfaction algorithms are often benchmarked on hard, random problems. There
are, however, many reasons for wanting a larger class of problems in our benchmark suites …

This dissertation presents several new algorithms and heuristics for constraint satisfaction
problems, as well as an extensive and systematic empirical evaluation of these new …

It has been observed by several authors that for many NP problems, a sharp peak in the
median cost to find a solution can be seen as an order parameter is varied; the peak occurs …

Most previous theoretical study of the complexity of the constraint satisfaction problem has
considered a simplified version of the problem in which all variables have the same domain …

A constraint satisfaction problem instance consists of a collection of variables that need to
have values assigned to them. The assignments are limited by constraints that force the …

Constraints have emerged as the basis of a representational and computational paradigm
that draws from many disciplines and can be brought to bear on many problem domains …

The many paths to satisfaction Page 1 6 The Many Paths to Satisfaction Eugene C. Freuder I
ABSTRACT Constraint satisfaction problems can be represented in may different ways. Here a …

Thisis theconferencerecordfortheFifthInternational… and Practice of Constraint
Programming (CP'99), held in Alexandria, Virginia, USA, on October 11-14, 1999. The series …

The standard models used to generate random binary constraint satisfaction problems are
described. At the problem sizes studied experimentally, a phase transition is seen as the …