Abstract
Aiming at the problems of unbalanced exploitation and exploration and falling into local optimization in black widow algorithm. In this paper, differential evolution strategy is introduced to avoid unnecessary exploration. At the same time, the random disturbance factor is used to improve the local exploitation performance of the black widow algorithm, and the memory function is added to the individual to improve the population's reproductive strategy, it further reduces the possibility of falling into local and ensures the balance between exploitation and exploration. By testing benchmark optimization functions and engineering problems, it shows the advantages of the improved algorithm, and has better progress in global search ability and convergence speed.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grants 62102374, 62072417, and U1804262 and in part by the Henan provincial science and technology research project under Grants 202102210177 and 212102210028.
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Wang, S., Zhang, X., Wang, Y., Niu, Y. (2022). Black Widow Spider Algorithm Based on Differential Evolution and Random Disturbance. In: Pan, L., Cui, Z., Cai, J., Li, L. (eds) Bio-Inspired Computing: Theories and Applications. BIC-TA 2021. Communications in Computer and Information Science, vol 1565. Springer, Singapore. https://doi.org/10.1007/978-981-19-1256-6_5
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DOI: https://doi.org/10.1007/978-981-19-1256-6_5
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