Name
Abstract | ||
|---|---|---|
Bulk material blending systems still mostly implement static and non-reactive material blending methods like the well-known Chevron stacking. The optimization potential in the existing systems which can be made available using quality analyzing methods as online X-ray fluorescence measurement is inspected in detail in this paper using a multi-objective optimization approach based on steady state evolutionary algorithms. We propose various Baldwinian and Lamarckian repair algorithms, test them on real world problem data and deliver optimized solutions which outperform the standard techniques. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-32937-1_48 | PPSN (1) |
Keywords | Field | DocType |
real world problem data,existing system,lamarckian repair algorithm,optimization potential,non-reactive material blending method,evolutionary optimization approach,multi-objective optimization approach,online x-ray fluorescence measurement,evolutionary algorithm,optimized solution,bulk material blending system | Chevron (geology),Mathematical optimization,Evolutionary algorithm,Computer science,Algorithm,Steady state,Stacking | Conference |
Citations | PageRank | References |
1 | 0.39 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael P. Cipold | 1 | 2 | 0.74 |
| Pradyumn Kumar Shukla | 2 | 274 | 23.97 |
| Claus C. Bachmann | 3 | 2 | 0.74 |
| Kaibin Bao | 4 | 19 | 3.90 |
| Hartmut Schmeck | 5 | 1034 | 120.58 |