Abstract
DE is challenging to maintain a balance between exploration and exploitation behaviors, and also the neighborhood and direction information of the difference vector is not completely utilized. In this paper, a completely novel DE variant, SODE, is proposed with the second order difference information, which is introduced to DE for even more fully utilizing the heuristic direction information. The second order difference information also enriches the neighborhood structure and enlarges the neighborhood domain with more heuristic information. Preliminary experimental results show that SODE is better than, or at least comparable to, the classical first order DE algorithms in terms of convergence performance and accuracy.
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Acknowledgment
This research is partially supported by National Natural Science Foundation of China (61375066, 61374204, 11471052).
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Zhao, X., Liu, D., Zuo, X., Liu, H., Li, R. (2016). Differential Evolution Algorithm with the Second Order Difference Vector. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_27
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DOI: https://doi.org/10.1007/978-981-10-3614-9_27
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