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Home > Archive>Volume 12, Issue 5, 2020 >569-576. DOI:10.13878/j.cnki.jnuist.2020.05.007
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A hybrid ant colony optimization algorithm based on MIMIC algorithm and RPCA
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    Abstract:

    To improve the optimization performance of the ant colony optimization algorithm for continuous domains and reduce the correlation among decision variables,a hybrid ant colony optimization algorithm based on MIMIC (Mutual Information Maximization for Input Clustering) algorithm and RPCA (Robust Principal Component Analysis) is designed.Firstly,the ant colony optimization algorithm for continuous domains is introduced.Then,a definition of effective correlation to deal with multivariable correlation is given and a hybrid ant colony optimization algorithm based on MIMIC algorithm and RPCA is proposed.Finally,through solving the standard test functions and comparing the results with that of the ant colony optimization algorithm for continuous domains,the proposed algorithm is proved to have great improvement in optimization ability and convergence,therefore,it is an effective optimization algorithm.

    Reference
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GUAN Juan, LIU Guohua, LIU Tianqi, QIN Jian, ZHANG Miaosen. A hybrid ant colony optimization algorithm based on MIMIC algorithm and RPCA[J]. Journal of Nanjing University of Information Science & Technology,2020,12(5):569-576

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  • Received:July 01,2020
  • Online: October 29,2020
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