Analyzing the BBOB Results by Means of Benchmarking Concepts

Mersmann O, Preuss M, Trautmann H, Bischl B, Weihs C


Abstract
We present methods to answer two basic questions that arise when benchmarking opti- mization algorithms. The first one is: which algorithm is the “best” one? and the second one is: which algorithm should I use for my real-world problem? Both are connected and neither is easy to answer. We present a theoretical framework for designing and analyzing the raw data of such benchmark experiments. This represents a first step in answering the aforementioned questions. The 2009 and 2010 BBOB benchmark results are analyzed by means of this framework and we derive insight regarding the answers to the two questions. Furthermore, we discuss how to properly aggregate rankings from algorithm evaluations on individual problems into a consensus, its theoretical background and which common pitfalls should be avoided. Finally, we address the grouping of test problems into sets with similar optimizer rankings and investigate whether these are reflected by already proposed test problem characteristics, finding that this is not always the case.



Publication type
Article in Journal

Peer reviewed
Yes

Publication status
Published

Year
2015

Journal
Evolutionary Computation Journal

Volume
23

Issue
1

Start page
161

End page
185

Language
English