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Conference Paper

Refined Runtime Analysis of a Basic Ant Colony Optimization Algorithm

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Doerr,  Benjamin
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Johannsen,  Daniel
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Citation

Doerr, B., & Johannsen, D. (2007). Refined Runtime Analysis of a Basic Ant Colony Optimization Algorithm. In IEEE Congress on Evolutionary Computation 2007 (pp. 501-507). Piscataway, NJ: IEEE.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-2080-E
Abstract
Neumann and Witt (2006) analyzed the runtime of the basic ant colony optimization (ACO) algorithm {\sc 1-Ant} on pseudo-boolean optimization problems. For the problem {\sc OneMax} they showed how the runtime depends on the evaporation factor. In particular, they proved a phase transition from exponential to polynomial runtime. In this work, we simplify the view on this problem by an appropriate translation of the pheromone model. This results in a profound simplification of the pheromone update rule and, by that, a refinement of the results of Neumann and Witt. In particular, we show how the exponential runtime bound gradually changes to a polynomial bound inside the phase of transition.