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Optimizing the Ant Colony Optimization using Standard Genetic Algorithm
Published in
2005
Pages: 130 - 133
Abstract
In this paper we propose a new approach towards the relationship between the ACO parameters suggested by Dorigo et al. [1], we propose the usage of the standard genetic algorithm in optimizing the ACO parameters, the algorithm is applied on the classical travelling salesman problem and we test this algorithm on deferent set of cities. The results found are similar to the results found by Dorigo.. We found that that the average value of $\alpha$ (the relative importance of trail) to be equal to 1.5729 and $\beta$ (the visibility) to be equal to 1.3896 while we found that the value of the trial persistence $\rho$ to be equal to 0.52. We found that all the parameters are independent of number of cities.
About the journal
Journal{IASTED} International Conference on Artificial Intelligence and Applications, part of the 23rd Multi-Conference on Applied Informatics, Innsbruck, Austria, February 14-16, 2005