Abstract
In this paper, we present a hybridization of an electromagnetic-like mechanism (EM) and the great deluge (GD) algorithm. This technique can be seen as a dynamic approach as an estimated quality of a new solution and a decay rate are calculated each iteration during the search process. These values are depending on a force value calculated using the EM approach. It is observed that applying these dynamic values help generate high quality solutions. Experimental results on benchmark examination timetabling problems demonstrate the effectiveness of this hybrid EM-GD approach compared with previous available methods. Possible extensions upon this simple approach are also discussed.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 60-72 |
| Number of pages | 13 |
| Volume | 5818 LNCS |
| DOIs | |
| Publication status | Published - 2009 |
| Event | 6th International Workshop on Hybrid Metaheuristics, HM 2009 - Udine Duration: 16 Oct 2009 → 17 Oct 2009 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 5818 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 6th International Workshop on Hybrid Metaheuristics, HM 2009 |
|---|---|
| City | Udine |
| Period | 16/10/09 → 17/10/09 |
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Keywords
- Decay rate
- Electromagnetism-like mechanism
- Exam timetabling
- Great deluge
- Hybrid metaheuristic
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
A hybridization of electromagnetic-like mechanism and great deluge for examination timetabling problems. / Abdullah, Salwani; Turabieh, Hamza; McCollum, Barry.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5818 LNCS 2009. p. 60-72 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5818 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A hybridization of electromagnetic-like mechanism and great deluge for examination timetabling problems
AU - Abdullah, Salwani
AU - Turabieh, Hamza
AU - McCollum, Barry
PY - 2009
Y1 - 2009
N2 - In this paper, we present a hybridization of an electromagnetic-like mechanism (EM) and the great deluge (GD) algorithm. This technique can be seen as a dynamic approach as an estimated quality of a new solution and a decay rate are calculated each iteration during the search process. These values are depending on a force value calculated using the EM approach. It is observed that applying these dynamic values help generate high quality solutions. Experimental results on benchmark examination timetabling problems demonstrate the effectiveness of this hybrid EM-GD approach compared with previous available methods. Possible extensions upon this simple approach are also discussed.
AB - In this paper, we present a hybridization of an electromagnetic-like mechanism (EM) and the great deluge (GD) algorithm. This technique can be seen as a dynamic approach as an estimated quality of a new solution and a decay rate are calculated each iteration during the search process. These values are depending on a force value calculated using the EM approach. It is observed that applying these dynamic values help generate high quality solutions. Experimental results on benchmark examination timetabling problems demonstrate the effectiveness of this hybrid EM-GD approach compared with previous available methods. Possible extensions upon this simple approach are also discussed.
KW - Decay rate
KW - Electromagnetism-like mechanism
KW - Exam timetabling
KW - Great deluge
KW - Hybrid metaheuristic
UR - http://www.scopus.com/inward/record.url?scp=71049194463&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71049194463&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04918-7_5
DO - 10.1007/978-3-642-04918-7_5
M3 - Conference contribution
SN - 3642049176
SN - 9783642049170
VL - 5818 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 60
EP - 72
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -