Name
Abstract | ||
|---|---|---|
The talent scheduling problem is a simplified version of the real-world film shooting problem, which aims to determine a shooting sequence so as to minimize the total cost of the actors involved. We devise a branch-and-bound algorithm to solve the problem. A novel lower bound function is employed to help eliminate the non-promising search nodes. Extensive experiments over the benchmark instances suggest that our branch-and-bound algorithm performs better than the currently best exact algorithm for the talent scheduling problem. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-07455-9_22 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Branch-and-bound,talent scheduling,dynamic programming | Dynamic programming,Branch and bound,Mathematical optimization,Job shop scheduling,Fair-share scheduling,Exact algorithm,Upper and lower bounds,Computer science,Rate-monotonic scheduling,Dynamic priority scheduling | Conference |
Volume | ISSN | Citations |
8481 | 0302-9743 | 2 |
PageRank | References | Authors |
0.39 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaocong Liang | 1 | 5 | 1.12 |
| Zizhen Zhang | 2 | 100 | 17.27 |
| Hu Qin | 3 | 201 | 16.49 |
| Songshan Guo | 4 | 46 | 6.50 |
| Andrew Lim | 5 | 937 | 89.78 |