Name
Abstract | ||
|---|---|---|
This paper reports on the use of an evolutionary algorithm (EA) to search a space of heuristic combinations for the uncapacitated examination timetabling problem. The representation used by an EA has an effect on the difficulty of the search and hence the overall success of the system. The paper examines three different representations of heuristic combinations for this problem and compares their performance on a set of benchmark problems for the uncapacitated examination timetabling problem. The study has revealed that certain representations do result in a better performance and generalization of the hyper-heuristic. An EA-based hyper-heuristic combining the use of all three representations (CEA) was implemented and found to generalize better than the EA using each of the representations separately. Journal of the Operational Research Society (2012) 63, 47-58. doi: 10.1057/jors.2011.12 Published online 6 April 2011 |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1057/jors.2011.12 | JORS |
Keywords | Field | DocType |
information technology,operational research,location,computer science,evolutionary algorithm,operations research,communications technology,logistics,project management,information systems,investment,production,forecasting,marketing,scheduling,inventory,management science,reliability | Heuristic,Evolutionary algorithm,Computer science,Scheduling (computing),Heuristics,Timetabling problem,Management science,Operations management,Project management | Journal |
Volume | Issue | ISSN |
63 | 1 | 0160-5682 |
Citations | PageRank | References |
10 | 0.54 | 14 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nelishia Pillay | 1 | 237 | 33.72 |