Description Functions Data Author(s) References See Also Examples

The empirical attainment function (EAF) describes the probabilistic distribution of the outcomes obtained by a stochastic algorithm in the objective space. This package implements plots of summary attainment surfaces and differences between the first-order EAFs. These plots may be used for exploring the performance of stochastic local search algorithms for biobjective optimization problems and help in identifying certain algorithmic behaviors in a graphical way.

`eafdiffplot()` | Empirical attainment function differences |

`eafplot()` | Plot the Empirical Attainment Function for two objectives |

`read_datasets()` | Read several data.frame sets |

`gcp2x2`

Metaheuristics for solving the Graph Vertex Coloring Problem

`HybridGA`

Results of Hybrid GA on vanzyl and Richmond water networks

`SPEA2minstoptimeRichmond`

Results of SPEA2 when minimising electrical cost and maximising the minimum idle time of pumps on Richmond water network

Extras are available at `system.file(package="eaf")`

:

`extdata` | External data sets (see `read_datasets` ) |

`scripts/eaf` | EAF command-line program |

`scripts/eafplot` | Perl script to generate plots of attainment surfaces |

`scripts/eafdiff` | Perl script to generate plots of EAF differences |

Maintainer: Manuel López-Ibáñez manuel.lopez-ibanez@manchester.ac.uk

Contributors: Carlos Fonseca, Luis Paquete, Thomas Stützle, Manuel López-Ibáñez, Marco Chiarandini and Mickaël Binois.

Grunert01eaf

\insertRefGruFon2009:emaaeaf

\insertRefLopPaqStu09emaaeaf

Useful links:

Report bugs at https://github.com/MLopez-Ibanez/eaf/issues

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(gcp2x2)
tabucol<-subset(gcp2x2, alg!="TSinN1")
tabucol$alg<-tabucol$alg[drop=TRUE]
eafplot(time+best~run,data=tabucol,subset=tabucol$inst=="DSJC500.5")
eafplot(time+best~run|inst,groups=alg,data=gcp2x2)
eafplot(time+best~run|inst,groups=alg,data=gcp2x2,
percentiles = c(0,50,100), cex = 1.4, lty = c(2,1,2),lwd = c(2,2,2),
col = c("black","blue","grey50"))
extdata_path <- system.file(package="eaf","extdata")
A1 <- read_datasets(file.path(extdata_path,"ALG_1_dat.xz"))
A2 <- read_datasets(file.path(extdata_path,"ALG_2_dat.xz"))
eafplot(A1, percentiles=c(50))
eafplot(list(A1=A1, A2=A2), percentiles=c(50))
eafdiffplot(A1, A2)
## Save to a PDF file
# dev.copy2pdf(file="eaf.pdf", onefile=TRUE, width=5, height=4)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.