Abstract
This paper introduces a method to minimize distributed PSO algorithm execution time in a grid computer environment, based on a reduction in the information interchanged among the demes involved in the process of finding the best global fitness solution. Demes usually interchange the best global fitness solution they found at each iteration. Instead of this, we propose to interchange information only after an specified number of iterations are concluded. By applying this technique, it is possible to get a very significant execution time decrease without any loss of solution quality.
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Parra, F., Galan, S.G., Yuste, A.J., Prado, R.P., Muñoz, J.E. (2009). A Method to Minimize Distributed PSO Algorithm Execution Time in Grid Computer Environment. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_51
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DOI: https://doi.org/10.1007/978-3-642-02267-8_51
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