Abstract
This paper proposes an improved bacterial forging optimization with differential tumble, perturbation, and cruising mechanisms, abbreviated as DPCBFO. In DPCBFO, the differential information between the population and the optimal individual is used to guide the tumble direction of the bacteria. The strategy of perturbation is employed to enhance the global search ability of the bacteria. While a new cruising mechanism is proposed in this study to improve the possibility of searching for the optimal by comparing the current position with the others obtained in the next chemotaxis steps. In addition, to reduce the computation complexity, the vectorized parallel evaluation is applied in the chemotaxis process. The performance of the proposed DPCBFO is evaluated on eight well-known benchmark functions. And the simulation results illustrate that the proposed DPCBFO achieves the superior performance on all functions.
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Acknowledgment
This work is partially supported by The National Natural Science Foundation of China (Grants No. 61472257), Natural Science Foundation of Guangdong Province (2016A030310074). Lu Xiao and Jinsong Chen contributed equally to this paper and shared the first authorship.
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Xiao, L., Chen, J., Zuo, L., Wang, H., Tan, L. (2018). Differential Structure-Redesigned-Based Bacterial Foraging Optimization. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_29
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DOI: https://doi.org/10.1007/978-3-319-93815-8_29
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