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• W2998946916 abstract "In recent years, lots of multi-factorial optimization evolutionary algorithms have been developed to optimize multiple tasks simultaneously, which improve the overall efficiency using implicit genetic complementarity between different tasks. In this paper, a novel multitask fireworks algorithm is proposed with novel transfer sparks to solve multitasks optimization problems. For each task, some transfer sparks would be generated with adaptive length and promising direction vector, which are very helpful to transfer useful genetic information between different tasks. Finally, the proposed algorithm is compared against some chosen state-of-the-art evolutionary multitasking algorithms. The experimental results show that the proposed algorithm provides better performance on several single objective and multi-objective MTO test suites." @default.
• W2998946916 created "2020-01-23" @default.
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• W2998946916 date "2020-01-17" @default.
• W2998946916 modified "2023-10-15" @default.
• W2998946916 title "A Fireworks Algorithm Based on Transfer Spark for Evolutionary Multitasking" @default.
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• W2998946916 doi "https://doi.org/10.3389/fnbot.2019.00109" @default.
• W2998946916 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6978702" @default.
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