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- W8701624 abstract "This article presents an analysis of the sensitiveness of evolutionary algorithms to the change of the random number generator when using a real-world problem --the fitting of a theoretical curve to an experimental data set-- as test. On the one hand, the evolutionary algorithms selected: particle swarm algorithm, differential evolution and genetic algorithm are widely used in optimization problems. And, on the other hand, the random number generator used: Mersenne Twister and GCC rand(), are the most frequently linked to evolutionary algorithms, as well as they are considered as high-quality. As a consequence of this work, an assessment is stated about the sensitiveness of the evolutionary algorithms studied to the choice of the random number generator." @default.
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- W8701624 date "2012-01-01" @default.
- W8701624 modified "2023-10-18" @default.
- W8701624 title "Real-World Problem for Checking the Sensitiveness of Evolutionary Algorithms to the Choice of the Random Number Generator" @default.
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- W8701624 doi "https://doi.org/10.1007/978-3-642-28942-2_35" @default.
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