Improving GAC-4 for table and MDD constraints
Abstract We introduce GAC-4R, MDD-4, and MDD-4R three new algorithms for maintaining
arc consistency for table and MDD constraints. GAC-4R improves the well-known GAC-4 …
arc consistency for table and MDD constraints. GAC-4R improves the well-known GAC-4 …
XCSP3: an integrated format for benchmarking combinatorial constrained problems
F Boussemart, C Lecoutre, G Audemard… - arXiv preprint arXiv …, 2016 - arxiv.org
We propose a major revision of the format XCSP 2.1, called XCSP3, to build integrated
representations of combinatorial constrained problems. This new format is able to deal with …
representations of combinatorial constrained problems. This new format is able to deal with …
Xcsp3-core: A format for representing constraint satisfaction/optimization problems
F Boussemart, C Lecoutre, G Audemard… - arXiv preprint arXiv …, 2020 - arxiv.org
In this document, we introduce XCSP3-core, a subset of XCSP3 that allows us to represent
constraint satisfaction/optimization problems. The interest of XCSP3-core is multiple:(i) …
constraint satisfaction/optimization problems. The interest of XCSP3-core is multiple:(i) …
The smart table constraint
Table Constraints are very useful for modeling combinatorial problems in Constraint
Programming (CP). They are a universal mechanism for representing constraints, but …
Programming (CP). They are a universal mechanism for representing constraints, but …
Generalized arc consistency algorithms for table constraints: A summary of algorithmic ideas
Constraint Programming is a powerful paradigm to model and solve combinatorial problems.
While there are many kinds of constraints, the table constraint (also called a CSP) is perhaps …
While there are many kinds of constraints, the table constraint (also called a CSP) is perhaps …
[PDF][PDF] Optimizing Simple Tabular Reduction with a Bitwise Representation.
Abstract Maintaining Generalized Arc Consistency (GAC) during search is considered an
efficient way to solve non-binary constraint satisfaction problems. Bit-based representations …
efficient way to solve non-binary constraint satisfaction problems. Bit-based representations …
[HTML][HTML] STR3: A path-optimal filtering algorithm for table constraints
C Lecoutre, C Likitvivatanavong, RHC Yap - Artificial Intelligence, 2015 - Elsevier
Constraint propagation is a key to the success of Constraint Programming (CP). The
principle is that filtering algorithms associated with constraints are executed in sequence …
principle is that filtering algorithms associated with constraints are executed in sequence …
Optimizing STR algorithms with tuple compression
Table constraints define an arbitrary constraint explicitly as a set of solutions (tuples) or non-
solutions. Thus, space is proportional to number of tuples. Simple Tabular Reduction (STR) …
solutions. Thus, space is proportional to number of tuples. Simple Tabular Reduction (STR) …
Arc consistency revisited
Binary constraints are a general representation for constraints and is used in Constraint
Satisfaction Problems (CSPs). However, many problems are more easily modelled with non …
Satisfaction Problems (CSPs). However, many problems are more easily modelled with non …
Extending STR to a higher-order consistency
One of the most widely studied classes of constraints in constraint programming (CP) is that
of table constraints. Numerousspecialized filtering algorithms, enforcing the wellknown …
of table constraints. Numerousspecialized filtering algorithms, enforcing the wellknown …