Benchmark Sequences for Online Archiving of Objective Vectors

Manuel López-Ibáñez, Joshua Knowles, and Marco Laumanns.

We examine the problem of maintaining an approximation of the set of nondominated points visited during a multiobjective optimization, a problem commonly known as archiving. The main scenario considered is the restricted case where the archive must be updated online as points are generated one by one, and at most a fixed number of points are to be stored in the archive at any one time.

This page collects benchmark sequences of objective vectors for the analysis and comparison of archiving algorithms (archivers). We have also made available the source code of several popular archivers.

We place these sequences in the public domain. If you write a scientific paper describing research that made substantive use of these sequences, the appropriate citation for each sequence is given in the Ref. column of the Table below. Moreover, we would appreciate it if you would email manuel.lopez-ibanez@manchester.ac.uk with citations of papers referencing this work so we can mention them to our funding agent and/or tenure committee. We also welcome new interesting sequences.

Relevant literature:

[1]
Manuel López-Ibáñez, Joshua D. Knowles, and Marco Laumanns. On Sequential Online Archiving of Objective Vectors. In R. Takahashi et al., editors, Evolutionary Multi-criterion Optimization (EMO 2011), volume 6576 of Lecture Notes in Computer Science, pages 46–60. Springer, Heidelberg, Germany, 2011.
[ bibtex | software | Technical report (revised version) ]
File Details Ref.
seq-smallPF-2d-10000.txt.gz Small PF, 2D, 10000 points. It causes problems to e-approx and e-Pareto archivers. [1]
seq-smallPF-3d-10000.txt.gz Small PF, 3D, 10000 points [1]
seq-clustered-2d-900.txt.gz Clustered PF, 2D, 900 points [1]
seq-1to2-2d-2000.txt.gz 2D, 2000 points. Sequence of 2000 nondominated points in a straight line, sorted in increasing order of their first dimension. [1]
seq-nsga2-deteriorates-2d-59.txt 2D, 59 points. Small sequence that shows how the archive stored by the NSGA-II archiver deteriorates over time. [1]
seq-mga-no-nep-2d-7.txt 2D, 7 points. Small sequence that shows that MGA is not negatively efficient preserving. [1]