Name
Abstract | ||
|---|---|---|
In this paper we introduce a simple ant-based algorithm for solving a copper mine planning problem. In the last 10 years this real-world problem has been tackled using linear integer programming and constraint programming. However, because it is a large scale problem, the model must be simplified by relaxing many constraints in order to obtain a near-optimal solution in a reasonable time. We now present an algorithm which takes into account most of the problem constraints and it is able to find better feasible solutions than the approach that has been used until now. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11552253_30 | IDA |
Keywords | Field | DocType |
ant colony,copper,constraint programming | Constraint satisfaction,Scale model,Mathematical optimization,Constraint (mathematics),Computer science,Constraint programming,Integer programming,Cutting stock problem,Linear programming,Artificial intelligence,Distributed computing,Scaling law | Conference |
Volume | ISSN | ISBN |
3646 | 0302-9743 | 3-540-28795-7 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| María Cristina Riff | 1 | 200 | 23.91 |
| Michael Moossen | 2 | 6 | 0.90 |
| Xavier Bonnaire | 3 | 85 | 11.88 |