@inproceedings{6a6ca46e428f4d52829991344aead3b8,
title = "How single ant ACO systems optimize pseudo-boolean functions",
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.",
author = "Benjamin Doerr and Daniel Johannsen and Tang, \{Ching Hoo\}",
year = "2008",
month = nov,
day = "27",
doi = "10.1007/978-3-540-87700-4\_38",
language = "English",
isbn = "3540876995",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "378--388",
booktitle = "Parallel Problem Solving from Nature - PPSN X - 10th International Conference, Proceedings",
note = "10th International Conference on Parallel Problem Solving from Nature, PPSN X ; Conference date: 13-09-2008 Through 17-09-2008",
}