Name
Abstract | ||
|---|---|---|
MiniZinc is a solver-agnostic modeling language for defining and solving combinatorial satisfaction and optimization problems. MiniZinc provides a solver-independent modeling language that is now supported by constraint-programming solvers, mixed integer programming solvers, SAT and SAT modulo theory solvers, and hybrid solvers. Every year since 2008 we have run the MiniZinc Challenge, which compares and contrasts the different strengths of different solvers and solving technologies on a set of MiniZinc models. Here we report on what we have learned from running the competition for 6 years. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1609/aimag.v35i2.2539 | AI MAGAZINE |
Field | DocType | Volume |
Modulo,Computer science,Constraint programming,Modeling language,Theoretical computer science,Integer programming,Solver,Optimization problem | Journal | 35 |
Issue | ISSN | Citations |
2 | 0738-4602 | 18 |
PageRank | References | Authors |
0.66 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter J. Stuckey | 1 | 4368 | 457.58 |
| Thibaut Feydy | 2 | 174 | 10.76 |
| Andreas Schutt | 3 | 173 | 14.06 |
| Guido Tack | 4 | 377 | 27.56 |
| Julien Fischer | 5 | 36 | 1.42 |