Omicron ACO

Osvaldo Gómez (1), Benjamín Barán (1)

e-mails: ogomez@cnc.una.py, bbaran@cnc.una.py

(1) Universidad Nacional de Asunción - Centro Nacional de Computación, Asunción Paraguay

Abstract

Ant Colony Optimization (ACO) is a metaheuristic inspired by the foraging behavior of ant colonies that has been successful in the resolution of hard combinatorial optimization problems like the TSP. This paper proposes the Omicron ACO (OA), a novel population-based ACO alternative designed as an analytical tool. To experimentally prove OA advantages, this work compares the behavior between the OA and the MMAS as a function of time in two well-known TSP problems. A simple study of the behavior of the OA as a function of its parameters proves its robustness.

Keywords:Artificial Intelligence, Ant Colony Optimization, Omicron ACo, MAX-MIN Ant System

BibTex

@INPROCEEDINGS{gomez04:311,
                  AUTHOR       = {Osvaldo Gómez and Benjamín Barán},
                  TITLE        = {Omicron ACO},
                  BOOKTITLE    = {30ma Conferencia Latinoamericana de Informática (CLEI2004)},
                  YEAR         = {2004},
                  editor       = {Mauricio Solar and David Fernández-Baca and Ernesto Cuadros-Vargas},
                  pages        = {932--939},
                  address      = {},
                  month        = Sep,
                  organization = {Sociedad Peruana de Computación},
                  note         = {ISBN 9972-9876-2-0},
                  file         = {http://clei2004.spc.org.pe/es/html/pdfs/311.pdf}
}

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