Constraint satisfaction problems and global cardinality constraints

Parameterized Algorithms for Constraint Satisfaction Problems Above Average with Global Cardinality Constraints

Given a constraint satisfaction problem (CSP) on n variables, x1, x2, . . . , xn ∈ {±1}, and m constraints, a global cardinality constraint has the form of ∑n i=1 xi = (1−2p)n, where p ∈ (Ω(1), 1−Ω(1)) and pn is an integer. Let AV G be the expected number of constraints satisfied by randomly choosing an assignment to x1, x2, . . . , xn, complying with the global cardinality constraint. The CSP ...

Hybrid tractability of constraint satisfaction problems with global constraints

A wide range of problems can be modelled as constraint satisfaction problems (CSPs), that is, a set of constraints that must be satisfied simultaneously. Constraints can either be represented extensionally, by explicitly listing allowed combinations of values, or intensionally, whether by an equation, propositional logic formula, or other means. Intensionally represented constraints, known as g...

Global constraints in distributed constraint satisfaction

Global constraints have been crucial for the success of centralized constraint programming. Here, we propose the inclusion of global constraints in distributed constraint satisfaction. We show how this inclusion can be done, considering different decompositions for global contraints. We provide experimental evidence of their benefits on several benchmarks solved with the ABT algorithm.

Solving Cardinality Constraints in ( Constraint )

Global Constraints in Distributed Constraint Satisfaction and Optimization

Global constraints are an essential component in the efficiency of centralized constraint programming. We propose to include global constraints in distributed constraint satisfaction and optimization problems (DisCSPs and DCOPs). We detail how this inclusion can be done, considering different representations for global constraints (direct, nested, binary). We explore the relation of global cons...