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eaf

Plots of the Empirical Attainment Function

Computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization. M. López-Ibáñez, L. Paquete, and T. Stützle (2010) <doi:10.1007/978-3-642-02538-9_9>.

README

This directory contains the files needed to reproduce the examples
described in 

     Manuel López-Ibáñez, Luís Paquete, and Thomas Stützle.
     Exploratory Analysis of Stochastic Local Search Algorithms in
     Biobjective Optimization. In T. Bartz-Beielstein, M. Chiarandini,
     L. Paquete, and M. Preuß, editors, Experimental Methods for the
     Analysis of Optimization Algorithms, pages 209-233, Springer, 2010.

The script run.sh contains the commands necessary to reproduce all
examples. Please, read the comments within run.sh.

Versions across snapshots

VersionRepositoryFileSize
2.5.2 rolling linux/jammy R-4.5 eaf_2.5.2.tar.gz 1.4 MiB
2.5.2 rolling linux/noble R-4.5 eaf_2.5.2.tar.gz 1.4 MiB
2.5.2 rolling source/ R- eaf_2.5.2.tar.gz 2.1 MiB
2.5.2 latest linux/jammy R-4.5 eaf_2.5.2.tar.gz 1.4 MiB
2.5.2 latest linux/noble R-4.5 eaf_2.5.2.tar.gz 1.4 MiB
2.5.2 latest source/ R- eaf_2.5.2.tar.gz 2.1 MiB
2.5.2 2026-04-26 source/ R- eaf_2.5.2.tar.gz 2.1 MiB
2.5.2 2026-04-23 source/ R- eaf_2.5.2.tar.gz 2.1 MiB
2.5.2 2026-04-09 windows/windows R-4.5 eaf_2.5.2.zip 1.5 MiB
2.5.2 2025-04-20 source/ R- eaf_2.5.2.tar.gz 2.1 MiB

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