Name
Abstract | ||
|---|---|---|
A new class of estimation of distribution algorithms (EDAs), known as cellular EDAs (cEDAs), has recently emerged. In these algorithms, the population is decentralized by partitioning it into many small collaborating subpopulations, arranged in a toroidal grid, and interacting only with its neighboring subpopulations. In this work, we study the simplest cEDA —the cellular univariate marginal distribution algorithm (cUMDA). In an attempt to explain its behaviour, we extend the well known takeover time analysis usually applied to other evolutionary algorithms to the field of EDAs. We also give in this work empirical arguments in favor of using the cUMDAs instead of its centralized equivalent. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11844297_25 | PPSN |
Keywords | Field | DocType |
timing analysis,estimation of distribution algorithm,discrete optimization | EDAS,Population,Mathematical optimization,Evolutionary algorithm,Estimation of distribution algorithm,Discrete optimization,Computer science,Parallel algorithm,Marginal distribution,Grid | Conference |
Volume | ISSN | ISBN |
4193 | 0302-9743 | 3-540-38990-3 |
Citations | PageRank | References |
3 | 0.41 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alba Enrique | 1 | 143 | 8.74 |
| Julio Madera | 2 | 4 | 1.10 |
| Bernabé Dorronsoro Díaz | 3 | 356 | 12.96 |
| Alberto Ochoa | 4 | 24 | 6.95 |
| Marta Soto | 5 | 27 | 6.42 |