In this paper, we propose a new Multi-Population QUasi-Affine TRansformation Evolution (MP-QUATRE) algorithm for global optimization. The proposed MP-QUATRE algorithm divides the population into three sub-populations with a sort strategy to maintain population diversities, and each sub-population adopts a different mutation scheme to make a good balance between exploration and exploitation capability. In the experiments, we compare the proposed algorithm with DE algorithm and QUATRE algorithm on CEC2013 test suite for real-parameter optimization. The experimental results indicate that the proposed MP-QUATRE algorithm has a better performance than the competing algorithms.
CITATION STYLE
Liu, N., Pan, J. S., Liao, X., & Chen, G. (2019). A Multi-population QUasi-Affine TRansformation Evolution Algorithm for Global Optimization. In Advances in Intelligent Systems and Computing (Vol. 834, pp. 19–28). Springer Verlag. https://doi.org/10.1007/978-981-13-5841-8_3
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