Maintaining explicit diversity within individual ant colonies

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Abstract

Natural ants have the property that they will follow one another
along a trail between the nest and the food source (and vice versa). While
this is a desirable biological property, it can lead to stagnation behaviour
within artificial systems that solve combinatorial optimisation problems.
Although the evaporation of pheromone within local update rules, mutating
pheromone values or the bounding of pheromone values may alleviate
this, they are only implicit forms of diversification within a colony. Hence,
there is no guarantee that stagnation will not occur. In this paper, a new
explicit diversification measure is devised that balances between the restriction
and freedom of incorporating various solution components. In terms
of the target applications, the travelling salesman problem and quadratic
assignment problem, this form of diversification allows for the comparison
of sequences of common solution components. If an ant is considered too
close to another member of the colony, it is explicitly forced to select another
component. This restriction may also be lifted if necessary as part
of the aspiration criteria. The results reveal improved performance over a
control ant colony system
Original languageEnglish
Title of host publicationRecent Advances in Artificial Life: Advances in Natural Computation: Volume 3
Subtitle of host publication Sydney, Australia, 5 – 8 December 2005
EditorsH. A. Abbass, T. Bossomaier, J. Wiles
Place of PublicationSingapore
PublisherWorld Scientific Publishing
Chapter17
Pages227-238
Number of pages12
ISBN (Electronic)978-981-270-149-7
ISBN (Print)978-981-256-615-7 , 9812566155
DOIs
Publication statusPublished - Dec 2005
EventAustralian Conference on Artificial Life - Sydney, Australia
Duration: 5 Dec 20058 Dec 2005

Conference

ConferenceAustralian Conference on Artificial Life
Abbreviated titleACAL05
CountryAustralia
CitySydney
Period5/12/058/12/05

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Cite this

Randall, M. (2005). Maintaining explicit diversity within individual ant colonies. In H. A. Abbass, T. Bossomaier, & J. Wiles (Eds.), Recent Advances in Artificial Life: Advances in Natural Computation: Volume 3: Sydney, Australia, 5 – 8 December 2005 (pp. 227-238). Singapore: World Scientific Publishing. https://doi.org/10.1142/9789812701497_0017