Name
Abstract | ||
|---|---|---|
In this work two instances of the examination timetabling problem are studied and solved using memetic algorithms. The first is the uncapacitated single-epoch problem instance. In the second problem instance two examination epochs are considered, with different durations. The memetic algorithm, named Shuffled Complex Evolution Algorithm, uses a population organized into sets called complexes which evolve independently using a recombination and local search operators. Population diversity is preserved by means of the recombination operator and a special solution update mechanism. Experimental evaluation was carried out on the public uncapacitated Toronto benchmarks (single epoch) and on the ISEL-DEETC department examination benchmark (two epochs). Results show that the algorithm is competitive on the Toronto benchmarks, attaining a new lower bound on one benchmark. In the ISEL-DEETC benchmark, the algorithm attains a lower cost when compared with the manual solution. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-26393-9_10 | Studies in Computational Intelligence |
Keywords | DocType | Volume |
Examination timetabling,Shuffled complex evolution algorithm,Memetic computing,Great deluge algorithm,Toronto benchmarks,Two-epoch examination timetabling | Conference | 620 |
ISSN | Citations | PageRank |
1860-949X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nuno Leite | 1 | 3 | 3.45 |
| Fernando Melício | 2 | 0 | 0.34 |
| Agostinho C. Rosa | 3 | 324 | 57.50 |