Name
Abstract | ||
|---|---|---|
Constraint satisfaction problems (CSPs) are used to solve real-life problems with inherent structures that contain vectors for repeating sets of variables and constraints. Often, the structure of the problem is a part of the problem, since the number of elements in the vector is not known in advance. We propose a method to solve such problems, even when there is no maximal length provided. Our method is based on constructing a vector size CSP from the problem description, and solving it to get the number of elements in the vector. We then use the vector size to construct and solve a CSP that has a specific number of elements. Experimental results show that this method enables fast solving of problems that cannot be solved or even constructed by existing methods. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-66158-2_4 | PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING (CP 2017) |
Keywords | Field | DocType |
Constraint satisfaction problems, Unbounded vector size | Mathematical optimization,Local consistency,Computer science,Constraint graph,Decomposition method (constraint satisfaction),Constraint satisfaction problem,Complexity of constraint satisfaction,Constraint satisfaction dual problem,Backtracking,Hybrid algorithm (constraint satisfaction) | Conference |
Volume | ISSN | Citations |
10416 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erez Bilgory | 1 | 1 | 0.37 |
| Eyal Bin | 2 | 56 | 6.74 |
| Avi Ziv | 3 | 465 | 72.49 |