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  • Differential evolution and differential ant-stigmergy on dynamic optimisation problems
    Brest, Janez ...
    Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two ... population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm (jDE) and the differential ant-stigmergy algorithm (DASA). The performances of the jDE and the DASA are evaluated on the set of well-known benchmark problems provided for the special session on Evolutionary Computation in Dynamic and Uncertain Environments. We analyse the results for five algorithms presented by using the non-parametric statistical test procedure. The two proposed algorithms show a consistently superior performance over other recently proposed methods. The results show that both algorithms are appropriate candidates for DOPs.
    Vir: International Journal of Systems Science. - ISSN 0020-7721 (Vol. 44, no. 4, 2013, str. 663-679)
    Vrsta gradiva - članek, sestavni del
    Leto - 2013
    Jezik - angleški
    COBISS.SI-ID - 15354390
    DOI

vir: International Journal of Systems Science. - ISSN 0020-7721 (Vol. 44, no. 4, 2013, str. 663-679)

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