Abstract
Dynamic multimodal optimization (DMO) problem is introduced and solved with brain storm optimization (BSO) algorithms in this paper. A dynamic multimodal optimization problem is defined as an optimization problem with multiple global optima and characteristics of global optima are changed during the search process. The effectiveness of BSO algorithm is validated on a test problem which was constructed based on the dynamic optimization and multimodal optimization. Results show that BSO algorithm is an efficient and robust optimization method for solving dynamic multimodal optimization problems.
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Acknowledgments
This work was jointly supported by National Natural Science Foundation of China (No. 61671041, 61773119, 61771297, and 61703256), and the Fundamental Research Funds for the Central Universities under Grant GK201703062.
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Cheng, S., Lu, H., Song, W., Chen, J., Shi, Y. (2018). Dynamic Multimodal Optimization Using Brain Storm Optimization Algorithms. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 951. Springer, Singapore. https://doi.org/10.1007/978-981-13-2826-8_21
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DOI: https://doi.org/10.1007/978-981-13-2826-8_21
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