3. Description of the Catalogue

3.1. Which global constraints are included?
3.2. Which global constraints are missing?
3.3. Searching in the catalogue
3.4. Figures of the catalogue
3.5. Constraints argument patterns
- 3.5.1. Constraints with 1 argument
- 3.5.2. Constraints with 2 arguments
- 3.5.3. Constraints with 3 arguments
- 3.5.4. Constraints with 4 arguments
- 3.5.5. Constraints with 5 arguments
- 3.5.6. Constraints with 6 arguments
- 3.5.7. Constraints with 8 arguments
- 3.5.8. Constraints with 10 arguments
3.6. Meta-keywords attached to the keywords
- 3.6.1. Application area
- 3.6.2. Characteristic of a constraint
- 3.6.3. Combinatorial object
- 3.6.4. Complexity
- 3.6.5. Constraint network structure
- 3.6.6. Constraint type
- 3.6.7. Constraint arguments
- 3.6.8. Filtering
- 3.6.9. Final graph structure
- 3.6.10. Geometry
- 3.6.11. Heuristics
- 3.6.12. Miscellaneous
- 3.6.13. Modelling
- 3.6.14. Modelling exercises
- 3.6.15. Problems
- 3.6.16. Puzzles
- 3.6.17. Symmetry
3.7. Keywords attached to the global constraints
- 3.7.1. 3-dimensional-matching
- 3.7.2. 3-SAT
- 3.7.3. Abstract interpretation
- 3.7.4. Acyclic
- 3.7.5. Aggregate
- 3.7.6. Air traffic management
- 3.7.7. Alignment
- 3.7.8. All different
- 3.7.9. Alpha-acyclic constraint network(2)
- 3.7.10. Alpha-acyclic constraint network(3)
- 3.7.11. Apartition
- 3.7.12. Arc-consistency
- 3.7.13. Arithmetic constraint
- 3.7.14. Array constraint
- 3.7.15. Assigning and scheduling tasks that run in parallel
- 3.7.16. Assignment
- 3.7.17. Assignment dimension
- 3.7.18. Assignment to the same set of values
- 3.7.19. At least
- 3.7.20. At most
- 3.7.21. Automaton
- 3.7.22. Automaton with array of counters
- 3.7.23. Automaton with counters
- 3.7.24. Automaton with same input symbol
- 3.7.25. Automaton without counters
- 3.7.26. Autoref
- 3.7.27. Balanced assignment
- 3.7.28. Balanced tree
- 3.7.29. Berge-acyclic constraint network
- 3.7.30. Binary constraint
- 3.7.31. Bioinformatics
- 3.7.32. Bipartite
- 3.7.33. Bipartite matching
- 3.7.34. Bipartite matching in convex bipartite graphs
- 3.7.35. Boolean channel
- 3.7.36. Boolean constraint
- 3.7.37. Border
- 3.7.38. Bound-consistency
- 3.7.39. Business rules
- 3.7.40. Centered cyclic(1) constraint network(1)
- 3.7.41. Centered cyclic(2) constraint network(1)
- 3.7.42. Centered cyclic(3) constraint network(1)
- 3.7.43. Channel routing
- 3.7.44. Channelling constraint
- 3.7.45. Circuit
- 3.7.46. Circular sliding cyclic(1) constraint network(2)
- 3.7.47. Cluster
- 3.7.48. Coloured
- 3.7.49. Compulsory part
- 3.7.50. Conditional constraint
- 3.7.51. Configuration problem
- 3.7.52. Connected component
- 3.7.53. Consecutive loops are connected
- 3.7.54. Consecutive values
- 3.7.55. Constraint between two collections of variables
- 3.7.56. Constraint between three collections of variables
- 3.7.57. Constraint involving set variables
- 3.7.58. Constraint on the intersection
- 3.7.59. Constructive disjunction
- 3.7.60. Contact
- 3.7.61. Contractible
- 3.7.62. Convex
- 3.7.63. Convex bipartite graph
- 3.7.64. Convex hull relaxation
- 3.7.65. Conway packing problem
- 3.7.66. Core
- 3.7.67. Costas arrays
- 3.7.68. Cost filtering constraint
- 3.7.69. Cost matrix
- 3.7.70. Counting constraint
- 3.7.71. Cumulative longest hole problems
- 3.7.72. Cycle
- 3.7.73. Cyclic
- 3.7.74. Data constraint
- 3.7.75. Deadlock breaking
- 3.7.76. Decomposition
- 3.7.77. Decomposition-based violation measure
- 3.7.78. Demand profile
- 3.7.79. Degree of diversity of a set of solutions
- 3.7.80. Derived collection
- 3.7.81. DFS-bottleneck
- 3.7.82. Difference
- 3.7.83. Difference between pairs of variables
- 3.7.84. Directed acyclic graph
- 3.7.85. Disequality
- 3.7.86. Disjunction
- 3.7.87. Domain channel
- 3.7.88. Domain definition
- 3.7.89. Dominating queens
- 3.7.90. Domination
- 3.7.91. Dual model
- 3.7.92. Duplicated variables
- 3.7.93. Dynamic programming
- 3.7.94. Empty intersection
- 3.7.95. Entailment
- 3.7.96. Equality
- 3.7.97. Equality between multisets
- 3.7.98. Equivalence
- 3.7.99. Euler knight
- 3.7.100. Excluded
- 3.7.101. Extensible
- 3.7.102. Extension
- 3.7.103. Facilities location problem
- 3.7.104. Floor planning problem
- 3.7.105. Flow
- 3.7.106. Frequency allocation problem
- 3.7.107. Functional dependency
- 3.7.108. Geometrical constraint
- 3.7.109. Glue matrix
- 3.7.110. Golomb ruler
- 3.7.111. Graph colouring
- 3.7.112. Graph constraint
- 3.7.113. Graph partitioning constraint
- 3.7.114. Guillotine cut
- 3.7.115. Hall interval
- 3.7.116. Hamiltonian
- 3.7.117. Heuristics
- 3.7.118. Heuristics and Berge-acyclic constraint network
- 3.7.119. Heuristics and lexicographical ordering
- 3.7.120. Heuristics for two-dimensional rectangle placement problems
  - 3.7.120.1. Dual strategy for rectangle placement problems with no slack
  - 3.7.120.2. Strategy that gradually creates a compulsory part
- 3.7.121. Hungarian method for the assignment problem
- 3.7.122. Hybrid-consistency
- 3.7.123. Hypergraph
- 3.7.124. Included
- 3.7.125. Inclusion
- 3.7.126. Incompatible pairs of values
- 3.7.127. Indistinguishable values
- 3.7.128. Interval
- 3.7.129. Involution
- 3.7.130. Joker value
- 3.7.131. Klee's measure problem
- 3.7.132. Labelling by increasing cost
- 3.7.133. Latin square
- 3.7.134. Lexicographic order
- 3.7.135. Limited discrepancy search
- 3.7.136. Linear programming
- 3.7.137. Line segments intersection
- 3.7.138. Logic
- 3.7.139. Logigraphe
- 3.7.140. Magic hexagon
- 3.7.141. Magic series
- 3.7.142. Magic square
- 3.7.143. Matching
- 3.7.144. Matrix
- 3.7.145. Matrix model
- 3.7.146. Matrix symmetry
- 3.7.147. Maximum
- 3.7.148. Maximum clique
- 3.7.149. Maximum number of occurrences
- 3.7.150. maxint
- 3.7.151. Metro
- 3.7.152. Minimum
- 3.7.153. Minimum cost flow
- 3.7.154. Minimum feedback vertex set
- 3.7.155. Minimum hitting set cardinality
- 3.7.156. Minimum number of occurrences
- 3.7.157. Modulo
- 3.7.158. Multi-site employee scheduling with calendar constraints
- 3.7.159. Multiset
- 3.7.160. Multiset ordering
- 3.7.161. No cycle
- 3.7.162. No loop
- 3.7.163. n-Amazons
- 3.7.164. n-queens
- 3.7.165. Non-deterministic automaton
- 3.7.166. Non-overlapping
- 3.7.167. Number of changes
- 3.7.168. Number of distinct equivalence classes
- 3.7.169. Number of distinct values
- 3.7.170. Obscure
- 3.7.171. One succ
- 3.7.172. Open automaton constraint
- 3.7.173. Open constraint
- 3.7.174. Order constraint
- 3.7.175. Orthotope
- 3.7.176. Overlapping alldifferent
- 3.7.177. Pair
- 3.7.178. Packing almost squares
- 3.7.179. Pallet loading
- 3.7.180. Partition
- 3.7.181. Path
- 3.7.182. Partridge
- 3.7.183. Pattern sequencing
- 3.7.184. Pentomino
- 3.7.185. Periodic
- 3.7.186. Permutation
- 3.7.187. Permutation channel
- 3.7.188. Phi-tree
- 3.7.189. Phylogeny
- 3.7.190. Pick-up delivery
- 3.7.191. Planarity test
- 3.7.192. Polygon
- 3.7.193. Positioning constraint
- 3.7.194. Predefined constraint
- 3.7.195. Preferences
- 3.7.196. Producer-consumer
- 3.7.197. Product
- 3.7.198. Program verification
- 3.7.199. Proximity constraint
- 3.7.200. Pure functional dependency
- 3.7.201. Quadtree
- 3.7.202. Range
- 3.7.203. Rank
- 3.7.204. RCC8
- 3.7.205. Rectangle clique partition
- 3.7.206. Regret based heuristics
- 3.7.207. Regret based heuristics in matrix problems
- 3.7.208. Reified automaton constraint
- 3.7.209. Reified constraint
- 3.7.210. Relation
- 3.7.211. Relaxation
- 3.7.212. Relaxation dimension
- 3.7.213. Resource constraint
- 3.7.214. Reverse of a constraint
- 3.7.215. Run of a permutation
- 3.7.216. SAT
- 3.7.217. Scalar product
- 3.7.218. Sequence
- 3.7.219. Sequence dependent set-up
- 3.7.220. Sequencing with release times and deadlines
- 3.7.221. Set channel
- 3.7.222. Set packing
- 3.7.223. Shikaku
- 3.7.224. Scheduling constraint
- 3.7.225. Scheduling with machine choice, calendars and preemption
- 3.7.226. Shared table
- 3.7.227. Schur number
- 3.7.228. SLAM problem
- 3.7.229. Sliding cyclic(1) constraint network(1)
- 3.7.230. Sliding cyclic(1) constraint network(2)
- 3.7.231. Sliding cyclic(1) constraint network(3)
- 3.7.232. Sliding cyclic(2) constraint network(2)
- 3.7.233. Sliding sequence constraint
- 3.7.234. Smallest square for packing consecutive dominoes
- 3.7.235. Smallest rectangle area
- 3.7.236. Smallest square for packing rectangles with distinct sizes
- 3.7.237. Soft constraint
- 3.7.238. Sort
- 3.7.239. Sort based reformulation
- 3.7.240. Sparse functional dependency
- 3.7.241. Sparse table
- 3.7.242. Sport timetabling
- 3.7.243. Squared squares
- 3.7.244. Statistics
- 3.7.245. Strip packing
- 3.7.246. Strong articulation point
- 3.7.247. Strong bridge
- 3.7.248. Strongly connected component
- 3.7.249. Subset sum
- 3.7.250. Sudoku
- 3.7.251. Sum
- 3.7.252. Sweep
- 3.7.253. Symmetric
- 3.7.254. Symmetry
- 3.7.255. System of constraints
- 3.7.256. Table
- 3.7.257. Temporal constraint
- 3.7.258. Ternary constraint
- 3.7.259. Timetabling constraint
- 3.7.260. Time window
- 3.7.261. Touch
- 3.7.262. Tree
- 3.7.263. Tuple
- 3.7.264. Two-dimensional orthogonal packing
- 3.7.265. Unary constraint
- 3.7.266. Undirected graph
- 3.7.267. Value constraint
- 3.7.268. Value partitioning constraint
- 3.7.269. Value precedence
- 3.7.270. Variable-based violation measure
- 3.7.271. Variable indexing
- 3.7.272. Variable subscript
- 3.7.273. Vector
- 3.7.274. Vpartition
- 3.7.275. Weighted assignment
- 3.7.276. Workload covering
- 3.7.277. Zebra puzzle
- 3.7.278. Zero-duration task

3.1. Which global constraints are included?

The global constraints of this catalogue come from the following sources:

Existing constraint systems like:
- ALICE [Lauriere78],
- CHARME in C [OplobeduMarcovitchTourbier89],
- CHIP [DincbasVanHentenryckSimonisAggounGrafBerthier88] in Prolog, C and C++ (http://www.cosytec.com),
- Choco [Laburthe00] in Java (http://choco.emn.fr/),
- ECLAIR [Platon03] in Claire,
- ECLiPSe [ECLiPSe03], [AptWallace07] in Prolog (http://eclipseclp.org/),
- FaCile in OCaml (http://www.recherche.enac.fr/opti/facile/),
- Gecode in C++ [Gecode06] (http://www.gecode.org/),
- IF/PROLOG in Prolog
  
  (http://www.ifcomputer.com/IFProlog/Constraints/home_en.html),
- Ilog Solver [Puget94] in C++ and later in Java (http://www.ilog.com),
- JaCoP in Java (http://www.jacop.eu/),
- Koalog in Java,
- Minion [GentJeffersonMiguel06] (http://minion.sourceforge.net/index.html),
- Mozart [Smolka96], [Mozart06] in Oz (http://www.mozart-oz.org/),
- SICStus [CarlssonOttossonCarlson97] in Prolog (http://www.sics.se/sicstus/).
When available, the Systems slot of a global constraint entry of the catalogue provides the name of the corresponding global constraint in the context of the Choco, Gecode, JaCoP, MiniZinc, and SICStus systems.
Constraint programming articles mostly from conferences like:
- The Principles and Practice of Constraint Programming (CP)
  
  (http://www.informatik.uni-trier.de/~ley/db/conf/cp/index.html),
- The International Joint Conference on Artificial Intelligence (IJCAI)
  
  (http://www.informatik.uni-trier.de/~ley/db/conf/ijcai/index.html),
- The National Conference on Artificial Intelligence (AAAI)
  
  (http://www.informatik.uni-trier.de/~ley/db/conf/aaai/index.html),
- The International Conference on Logic Programming (ICLP)
  
  (http://www.informatik.uni-trier.de/~ley/db/conf/iclp/index.html),
- The International Conference of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems (CPAIOR)
  
  (http://www.informatik.uni-trier.de/~ley/db/conf/cpaior/).
Graph constraints from the CP(Graph) computation domain [Dooms06].
New constraints inspired by variations of existing constraints, practical applications, combinatorial problems, puzzles or discussions with colleagues.