Abstract
In this work, the authors focus on the quantum evolutionary quantum hybridization and its contribution in solving the binary decision diagram ordering problem. Therefore, a problem formulation in terms of quantum representation and evolutionary dynamic borrowing quantum operators are defined. The sifting search strategy is used in order to increase the efficiency of the exploration process, while experiments on a wide range of data sets show the effectiveness of the proposed framework and its ability to achieve good quality solutions. The proposed approach is distinguished by a reduced population size and a reasonable number of iterations to find the best order, thanks to the principles of quantum computing and to the sifting strategy.
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More From: International Journal of Cognitive Informatics and Natural Intelligence
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