Name
Abstract | ||
|---|---|---|
This paper addresses the solution of timetabling problems using cultural algorithms. The core idea is to extract problem domain information during the evolutionary search, and then combine it with some previously proposed operators, in order to improve performance. The proposed approach is validated using a benchmark of 20 instances, and its results are compared with respect to three other approaches: two evolutionary algorithms and simulated annealing, all of which have been previously adopted to solve timetabling problems. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.asoc.2009.11.024 | Appl. Soft Comput. |
Keywords | Field | DocType |
simulated annealing,problem domain information,core idea,metaheuristics,evolutionary search,timetabling problem,parameter control,evolutionary algorithm,cultural algorithms,cultural algorithm | Simulated annealing,Mathematical optimization,Evolutionary algorithm,Problem domain,Computer science,Operator (computer programming),Artificial intelligence,Cultural algorithm,Parameter control,Machine learning,Metaheuristic | Journal |
Volume | Issue | ISSN |
11 | 1 | Applied Soft Computing Journal |
Citations | PageRank | References |
14 | 1.12 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Soza | 1 | 17 | 1.55 |
| Ricardo Landa Becerra | 2 | 184 | 18.30 |
| María Cristina Riff | 3 | 200 | 23.91 |
| C. A. Coello Coello | 4 | 5799 | 427.99 |