In this paper, the authors propose the use of the Lévy probability distribution as leading mechanism for solutions differentiation in an efficient and bio-inspired optimization algorithm, ant colony optimization in continuous domains, ACOR. In the classical ACOR, new solutions are constructed starting from one solution, selected from an archive, where Gaussian distribution is used for parameter diversification. In the proposed approach, the Lévy probability distributions are properly introduced in the solution construction step, in order to couple the ACOR algorithm with the exploration properties of the Lévy distribution. The proposed approach has been tested on mathematical test functions and on a real world problem of structural engineering, the composite laminates buckling load maximization. In the latter case, as in many other cases in real world problems, the function to be optimized is multi-modal, and thus the exploration ability of the Levy perturbation operator allow the attainment of better results.
|Title of host publication||Trends in Applied Intelligent Systems|
|Number of pages||9|
|Publication status||Published - 2010|
|Name||Lecture Notes in Computer Science|
- Theoretical Computer Science
- General Computer Science