New Paper: Sensitivity Analysis of the Bee Colony Optimization Algorithm

Tatjana Jaksic Krüger and Tatjana Davidovic (Mathematical Institute of Serbian Academy of Sciences and Arts, Belgrade, Serbia) present a “Sensitivity Analysis of the Bee Colony Optimization Algorithm”.
They refer to the sequential parameter optimization and related methods as follows:
“During the last decade, different tools for experimental analysis were proposed and/or inspected, most of them based on modeling response values with linear or nonlinear models and/or implementing three basic steps: screening, experimentation and exploitation [1, 9, 19].”
The paper can be downloaded here.

[1] T. Bartz-Beielstein and M. Preuß. Experimental analysis of optimization algorithms: Tuning and beyond. In Theory and Principled Methods for the Design of Metaheuristics, pages 205–245, Springer, 2014.
[9] A.E.EibenandS.K.Smit.Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evolutionary Computation, 1(1):19–31, 2011.
[19] X.-S. Yang, S. Deb, M. Loomes, and M. Karamanoglu. A framework for self-tuning optimization algorithm. Neural Computing and Applications, 23(7- 8):2051–2057, 2013.