Des explications pour reconnaître et exploiter les structures cachées d'un problème combinatoire

L'identification de structures propres à un problème est souvent une étape clef pour la conception d'heuristiques de recherche comme pour la compréhension de la complexité du problème. De nombreuses approches en Recherche Opérationnelle emploient des stratégies de relaxation ou de décomposition dès lors que certaines structures idoines ont été identifiées. L'étape suivante est la conception d'algorithmes de résolution qui puissent intégrer à la volée, pendant la résolution, ce type d'information. Cet article propose d'utiliser un solveur de contraintes à base d'explications pour collecter une information pertinente sur les structures dynamiques et statiques inhérentes au problème. Identifying structure in a given combinatorial problem is often a key step for designing efficient search heuristics or for understanding the inherent complexity of the problem. Several Operations Research approaches apply decomposition or relaxation strategies upon such a structure identified within a given problem. The next step is to design algorithms that adaptively integrate that kind of information during search. We claim in this paper, inspired by previous work on impact-based search strategies for constraint programming, that using an explanation-based constraint solver may lead to collect invaluable information on the intimate dynamic and static structure of a problem instance

Choco: an Open Source Java Constraint Programming Library

International audienceChoco is a java library for constraint satisfaction problems (CSP), constraint programming (CP) and explanation-based constraint solving (e-CP). It is built on a event-based propagation mechanism with backtrackable structures

Conflict History Based Branching Heuristic for CSP Solving

International audienceAn important feature in designing algorithms to solve Constraint Satisfaction Problems (CSP) is the definition of a branching heuristic to explore efficiently the search space and exploit the problem structure. We propose Conflict-History Search (CHS), a new dynamic and adaptive branching heuristic for CSP solving. It is based on the search history by considering the temporality of search failures. To achieve that, we use the exponential recency weighted average to estimate the evolution of the hardness of constraints throughout the search. The experimental evaluation on XCSP3 instances shows that integrating CHS to solvers based on MAC obtains competitive results and can improve those obtained through other heuristics of the state of the art

Conflict History based Search for Constraint Satisfaction Problem

International audienc