Name
Abstract | ||
|---|---|---|
This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along with a user int erface designed for it. New results are given concerning repair of poor recombi nation choices during local search. New methods are described and evaluated tha t allow timetables to be produced which have minimal changes compared to a full or partial reference timetable. The paper concludes with a discussion of scale-up issues, and gives some initial results that are very encouraging. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/BFb0056928 | PPSN |
Keywords | Field | DocType |
entire university,evolutionary algorithm,local search | Search algorithm,Evolutionary algorithm,Computer science,Theoretical computer science,Schedule,Artificial intelligence,Local search (optimization),User interface,Timetabling problem,Machine learning | Conference |
Volume | ISSN | ISBN |
1498 | 0302-9743 | 3-540-65078-4 |
Citations | PageRank | References |
30 | 2.83 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ben Paechter | 1 | 514 | 65.78 |
| R. C. Rankin | 2 | 37 | 4.42 |
| Andrew Cumming | 3 | 30 | 2.83 |
| T C Fogarty | 4 | 1147 | 152.53 |