An ant colony simulator : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand
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Date
2012
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Massey University
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Abstract
In recent years, ant colony algorithms have become more popular research topics in the
artificial intelligence area of computer science. This biological modeling algorithm simulates
the natural behavior of an ant colony looking for food among the insect kingdom. This
algorithm was initially proposed by Marco Dorigo in 1992 in his PhD thesis – the first
algorithm was aiming to search for an optimal path in a graph based on the behavior of ants
seeking a path between their colony and a source of food. The original idea has since been
diversified to solve a wider class of numerical problems, and as a result, several problems
have emerged, drawing on various aspects of the behavior of ants (Ant colony optimization,
2010).
The famous science journal “Nature” has published articles relating to ant colony algorithms
several times, and lots of other publishers around the world have produced quite a few
books for ant colony optimization. These days, ant colony algorithms have become a hot
topic for the international artificial intelligence computing.
The biological modeling optimization algorithm is an important branch in the artificial
intelligence research area, which includes simulation biosphere natural selection and
heredity mechanism genetic algorithm (Duan, 2005). This thesis continues research on the
original ant colony algorithm, and creates a simulator to handle the ant colony’s natural
behavior to find food.
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Keywords
Ant algorithms, Ant behaviour, Ant colonies, Computer simulation, Computer science, Mathematical optimisation