The Valued (VCSP) framework is a generic optimization framework with a wide range of applications. Soft arc consistency operations transform a VCSP into an equivalent problem by shifting weights between cost functions. The principal aim is to produce a good lower bound on the cost of solutions, an essential ingredient of a branch and bound search. But soft AC is much more complex than traditional AC: there may be several closures (fixpoints) and finding the closure with a maximum lower bound has been shown to be NP-hard for integer costs [Cooper and Schiex, 2004]. We introduce a relaxed variant of soft arc consistency using rational costs. In this case, an optimal closure can be found in polynomial time. Furthermore, for finite rational c...
In many combinatorial problems one may need to model the diversity or similarity of sets of assignme...
In many combinatorial problems one may need to model the diversity or similarity of assignments in a...
International audienceWe propose a framework for computing upper bounds on the optimal value of the ...
AbstractThe Valued Constraint Satisfaction Problem (VCSP) is a generic optimization problem defined ...
Optimizing a combination of local cost functions on discrete variables is a central problem in many ...
Optimizing a combination of local cost functions on dis-crete variables is a central problem in many...
International audienceA valued constraint satisfaction problem (VCSP) is a soft constraint framework...
AbstractThe notion of arc consistency plays a central role in constraint satisfaction [R. Dechter, C...
International audienceWCSP is an optimization problem for which many forms of soft local (arc) consi...
AbstractRecently, a general definition of arc consistency (AC) for soft constraint frameworks has be...
Abstract. WCSP is a soft constraint framework with a wide range of applications. Most current comple...
A large number of problems in Artificial Intelligence and other areas of science can be viewed as sp...
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving proble...
A new local consistency for weighted CSP dedicated to long domains The weighted constraint satisfact...
AbstractValued constraint satisfaction provides a general framework for optimisation problems over f...
In many combinatorial problems one may need to model the diversity or similarity of sets of assignme...
In many combinatorial problems one may need to model the diversity or similarity of assignments in a...
International audienceWe propose a framework for computing upper bounds on the optimal value of the ...
AbstractThe Valued Constraint Satisfaction Problem (VCSP) is a generic optimization problem defined ...
Optimizing a combination of local cost functions on discrete variables is a central problem in many ...
Optimizing a combination of local cost functions on dis-crete variables is a central problem in many...
International audienceA valued constraint satisfaction problem (VCSP) is a soft constraint framework...
AbstractThe notion of arc consistency plays a central role in constraint satisfaction [R. Dechter, C...
International audienceWCSP is an optimization problem for which many forms of soft local (arc) consi...
AbstractRecently, a general definition of arc consistency (AC) for soft constraint frameworks has be...
Abstract. WCSP is a soft constraint framework with a wide range of applications. Most current comple...
A large number of problems in Artificial Intelligence and other areas of science can be viewed as sp...
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving proble...
A new local consistency for weighted CSP dedicated to long domains The weighted constraint satisfact...
AbstractValued constraint satisfaction provides a general framework for optimisation problems over f...
In many combinatorial problems one may need to model the diversity or similarity of sets of assignme...
In many combinatorial problems one may need to model the diversity or similarity of assignments in a...
International audienceWe propose a framework for computing upper bounds on the optimal value of the ...