This paper studies the resolution of (augmented) weighted matching problems within a constraint programming framework. The first contribution of the paper is a set of branch-and-bound techniques that improves substantially the performance of algorithms based on constraint propagation and the second contribution is the introduction of weighted matching as a global constraint (MinWeightAllDifferent), that can be propagated using specialized incremental algorithms from Operations Research. We first compare programming techniques that use constraint propagation with specialized algorithms from Operations Research, such as the Busaker and Gowen flow algorithm or the Hungarian method. Although CLP is shown not to be competitive with specialized p...
Constraint programming (CP) is a flexible and modular approach to solve combinatorial optimization p...
In classical constraint satisfaction, combining mutually redundant models using channeling constrain...
Abstract: Despite successful application of constraint programming (CP) to solving many real-life pr...
We study the matching problem and some variants such as b-matching and (g, f)-factors. This thesis a...
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws o...
Research area: Program Analysis and VerificationSystems of weighted constraints are a natural formal...
International audienceIn this paper, we propose mechanisms to improve instantiation heuristics by in...
This paper presents constraint programming (CP) as a natural formalism for modelling problems, and a...
There has been a lot of interest lately from people solving constrained optimization problems for co...
Abstract This paper presents Constraint Programming as a natural formalism for modelling problems, a...
This paper reports promising algorithms that have been built on top of both operations research (OR)...
A complexity analysis based on the structure of perfect matchings is given for the most efficient ba...
AbstractThe weighted m-d matching and m-set packing problems (m≥3) are usually solved through approx...
A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite se...
Branching heuristics based on counting solutions in constraints have been quite good at guiding sear...
Constraint programming (CP) is a flexible and modular approach to solve combinatorial optimization p...
In classical constraint satisfaction, combining mutually redundant models using channeling constrain...
Abstract: Despite successful application of constraint programming (CP) to solving many real-life pr...
We study the matching problem and some variants such as b-matching and (g, f)-factors. This thesis a...
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws o...
Research area: Program Analysis and VerificationSystems of weighted constraints are a natural formal...
International audienceIn this paper, we propose mechanisms to improve instantiation heuristics by in...
This paper presents constraint programming (CP) as a natural formalism for modelling problems, and a...
There has been a lot of interest lately from people solving constrained optimization problems for co...
Abstract This paper presents Constraint Programming as a natural formalism for modelling problems, a...
This paper reports promising algorithms that have been built on top of both operations research (OR)...
A complexity analysis based on the structure of perfect matchings is given for the most efficient ba...
AbstractThe weighted m-d matching and m-set packing problems (m≥3) are usually solved through approx...
A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite se...
Branching heuristics based on counting solutions in constraints have been quite good at guiding sear...
Constraint programming (CP) is a flexible and modular approach to solve combinatorial optimization p...
In classical constraint satisfaction, combining mutually redundant models using channeling constrain...
Abstract: Despite successful application of constraint programming (CP) to solving many real-life pr...