Abstract
Among the variants of GP, GEP stands out for its simplicity of encoding method and MEP catches our attention for its multi-expression capability. In this paper, a novel GP variant-MGEP (Multi-expression based Gene Expression Programming) is proposed to combine these two approaches. The new method preserves the GEP structure, however unlike the traditional GEP, its genes, like those of MEP, can be disassembled into many expressions. Therefore in MGEP, the traditional GEP gene can contain multiple solutions for a problem. The experimental result shows the MGEP is more effective than the traditional GEP and MEP in solving problems.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 61170199), Hunan Provincial Innovation Foundation for Postgraduate (CX2012B367), Guangxi Key Laboratory of Trusted Software (Guilin University of Electronic Technology), and the Scientific Research Fund of Education Department of Hunan Province, China (Grant No. 11A004).
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Deng, W., He, P., Huang, Z. (2013). Multi-Expression Based Gene Expression Programming. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_49
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DOI: https://doi.org/10.1007/978-3-642-38466-0_49
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