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This paper presents a comparative study of multiobjective algorithms to solve the routing and wavelength assignment problem in optical networks. The study evaluates five computational intelligence algorithms, namely: the Firefly Algorithm, the Differential Evolutionary Algorithm, the Simulated Annealing Algorithm and two versions of the Particle Swarm Optimization algorithm. Each algorithm is assessed based on the performance provided by two different network topologies under different data traffic loads and with a different number of wavelengths available in the network. The impact of implementing wavelength conversion processes is also taken into account in this study. Simulated results show that, in general, the evaluated algorithms appropriately solve the problem in small-sized networks in which a similar performance was found. However, key differences were found when the size of the network is significant. This means that more suitable algorithms optimize the search space and the fall into local minimums is avoided. [ABSTRACT FROM AUTHOR]

Optical recognition of handwritten numbers was worked by different methods, with satisfactory results. In this paper, we propose fuzzy systems with genetic algorithms, specifically memetic, to do this task. Results with this method are compared with neuronal network of semi-supervised learning, where we was used networks with radial base functions (RBF). To make the comparison, is possible observed that this kind of neuronal network offers advantages regarding error rates and time-to-results of the recognition system, compared with methods based in fuzzy systems. [ABSTRACT FROM AUTHOR]