Abstract
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied single ant ACO systems on several pseudo-boolean functions. By tracking the behavior of the underlying random processes rather than just regarding the resulting optimization time, we gain additional insight into these systems. A main finding is that in those cases where the single ant ACO system performs well, it basically simulates the much simpler (1+1) evolutionary algorithm. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Doerr, B., Johannsen, D., & Tang, C. H. (2008). How single ant ACO systems optimize pseudo-boolean functions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5199 LNCS, pp. 378–388). https://doi.org/10.1007/978-3-540-87700-4_38
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