Title
Constraint satisfaction problems: Convexity makes AllDifferent constraints tractable
Abstract
We examine the complexity of constraint satisfaction problems that consist of a set of AllDiff constraints. Such CSPs naturally model a wide range of real-world and combinatorial problems, like scheduling, frequency allocations, and graph coloring problems. As this problem is known to be NP-complete, we investigate under which further assumptions it becomes tractable. We observe that a crucial property seems to be the convexity of the variable domains and constraints. Our main contribution is an extensive study of the complexity of Multiple AllDiff CSPs for a set of natural parameters, like maximum domain size and maximum size of the constraint scopes. We show that, depending on the parameter, convexity can make the problem tractable even though it is provably intractable in general. Interestingly, the convexity of constraints is the key property in achieving fixed parameter tractability, while the convexity of domains does not usually make the problem easier.
Year
DOI
Venue
2011
10.1016/j.tcs.2012.11.038
Theor. Comput. Sci.
Keywords
DocType
Volume
key property,problem tractable,maximum domain size,crucial property,Multiple AllDiff CSPs,AllDifferent constraints tractable,AllDiff constraint,constraint satisfaction problem,constraint scope,maximum size,combinatorial problem
Conference
472,
ISSN
Citations 
PageRank 
0304-3975
2
0.39
References 
Authors
28
5
Name
Order
Citations
PageRank
Michael R. Fellows14138319.37
Tobias Friedrich245723.56
Danny Hermelin379048.62
Nina Narodytska444939.28
Frances A. Rosamond568434.52