Abstract
This paper proposes a heuristic to improve the convergence speed of the standard ant clustering algorithm. The heuristic is based on the behavior of termites that, when building their nests, add some pheromone to the objects they carry. In this context, pheromone allows artificial ants to get more information, at the local level, about the work in progress at the global level. A sensitivity analysis of the algorithm is performed in relation to the proposed modification on a benchmark problem, leading to interesting results.
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Sherafat, V., Nunes de Castro, L., Hruschka, E.R. (2004). TermitAnt: An Ant Clustering Algorithm Improved by Ideas from Termite Colonies. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_169
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DOI: https://doi.org/10.1007/978-3-540-30499-9_169
Publisher Name: Springer, Berlin, Heidelberg
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