ABC-X: A Configurable Generalized Artificial Bee Colony Algorithm: Supplementary material

by Dogan Aydin, Gürcan Yavuz, Thomas Stützle
January 2017

1. Abstract:

Over the last decade, a large number of variants of the Artificial Bee Colony (ABC) algorithm have been proposed, making it by now a well studied swarm intelligence algorithms. Typically, in a paper on algorithmic variants of ABC algorithms, one or at most two of its algorithmic components are modified. Possible changes include variations on the search equations, the selection of candidate solutions to be explored, or the adoption of features from other algorithmic techniques. In this article, we propose to follow a different direction and to build a generalized ABC algorithm, which we call ABC-X. ABC-X collects algorithmic components available from known ABC algorithms into a common algorithm framework that allows not only to instantiate known ABC variants but, more importantly, also many ABC algorithm variants that have never been explored before in the literature. Automatic algorithm configuration techniques can generate from this template new ABC variants that perform superior to known ABC algorithms, even if their numerical parameters are fine-tuned by the same techniques. Hence, our work also shows that the combination of flexible algorithm frameworks with automatic algorithm configuration techniques allows to obtain algorithms superior to manually designed ones.

Keywords: automatic algorithm configuration, artificial bee colony, rcontinuous optimization, irace

2. Supplementary information: Code

The code implementing ABC-X can be found here: ABC-X.

3. References:

[1] Dogan Aydin, Gürcan Yavuz, and Stützle, T.: ABC-X: A configurable generalized ABC algorithm, submitted.