Enhanced Bacterial Foraging Optimization with Dynamic Disturbance Learning and Bilayer Nested Structure
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-7181-3_12
Reference18 articles.
1. Guo, C., Tang, H., Niu, B., Lee, C.B.P.: A survey of bacterial foraging optimization. Neurocomputing 452, 728–746 (2021)
2. Singhal, S., Sharma, A.: Mutative BFO-based scheduling algorithm for cloud environment. In: Goyal, V., Gupta, M., Trivedi, A., Kolhe, M.L. (eds.) Proceedings of International Conference on Communication and Artificial Intelligence. Lecture Notes in Networks and Systems, vol. 192, pp. 589–599. Springer, Singapore (2021). https://doi.org/10.1007/978-981-33-6546-9_56
3. Wu, X., Zhou, T., Qiu, Z.: Bacterial foraging optimization based on levy flight for fuzzy portfolio optimization. In: Tan, Y., Shi, Y., Tuba, M. (eds.) Advances in Swarm Intelligence. ICSI 2020. Lecture Notes in Computer Science, vol. 12145, pp. 287–298. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53956-6_26
4. Zhang, Y., Lv, Y., Zhou, Y.: Research on economic optimal dispatching of microgrid based on an improved bacteria foraging optimization. Biomimetics 8(2), 150 (2023)
5. Ruhin Kouser, R., Manikandan, T.: A novel clustering and optimal resource scheduling in vehicular cloud networks using MKMA and the CM-CSO algorithm. J. Commun. Syst. 36(5), e5424 (2023)
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