Abstract
This paper proposes a new framework for the optimization of logistic processes using ant colonies. The application of the method to real data does not allow to test different parameter settings on a trial and error basis. Therefore, a sensitive analysis of the algorithm parameters is done in a simulation environment, in order to provide a correlation between the different coefficients. The proposed algorithm was applied to a real logistic process at Fujitsu-Siemens Computers, using the set of parameters defined by the analysis. The presented results show that the ant colonies provide a good scheduling methodology to logistic processes.
This work is supported by the German Ministry of Education and Research (BMBF) under Contract no.13N7906 (project Nivelli) and by the Portuguese Fundation for Science andTechnology (FCT) under Grant no. SFRH/BD/6366/2001.
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Silva, C.A., Runkler, T.A., Sousa, J.M., Palm, R. (2002). Ant Colonies as Logistic Processes Optimizers. In: Dorigo, M., Di Caro, G., Sampels, M. (eds) Ant Algorithms. ANTS 2002. Lecture Notes in Computer Science, vol 2463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45724-0_7
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DOI: https://doi.org/10.1007/3-540-45724-0_7
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