Abstract
QUasi-Affine TRansformation Evolution (QUATRE) algorithm is a new simple but powerful stochastic optimization algorithm proposed recently. The QUATRE algorithm aims to tackle the representational/positional bias inborn with DE algorithm and secures an overall better performance on commonly used Conference of Evolutionary Computation (CEC) benchmark functions. Recently, several QUATRE variants have been already proposed since its inception in 2016 and performed very well on many benchmark functions. In this paper, we mainly have a brief overview of all these proposed QUATRE variants first and then make simple contrasts between these QUATRE variants and several state-of-the-art DE variants under CEC2013 test suites for real-parameter single objective optimization benchmark functions. Experiment results show that the movement trajectory of individuals in the QUATRE structure is much more efficient than DE structure on most of the tested benchmark functions.
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Acknowledgement
This work is partially funded by Shenzhen Innovation and Entrepreneurship Project (GRCK20160826105935160) and National Natural Science Foundation of China (61371178).
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Meng, Z., Pan, JS., Li, X. (2018). The QUasi-Affine TRansformation Evolution (QUATRE) Algorithm: An Overview. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_35
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DOI: https://doi.org/10.1007/978-3-319-68527-4_35
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