Abstract
Firefly algorithm (FA) is a global optimization algorithm with simple, less parameter and faster convergence speed. However, the FA is easy to fall into local optimum, and the solution accuracy of the FA is lower. In order to overcome these problems. An improved Firefly algorithm hybrid with Fireworks (FWFA) is proposed in this paper. Because the local search ability of the fireworks algorithm’s search strategy is strong, we introduce the fireworks algorithm neighborhood search operator of the fireworks algorithm into the firefly algorithm to improve the local search ability of the Firefly algorithm. Through the simulation and analysis of 28 benchmark functions, verify the effectiveness and reliability of the new algorithm. The experimental results show that the new algorithm has excellent search ability in solving unimodal functions and multimodal functions.
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Acknowledgement
This work was supported by The National Science Foundation of China (No. 61763019), The Natural Science Foundation of Heilongjiang Province (General Program: F2017019), The Science and Technology Plan Projects of Jiangxi Province Education Department (No. GJJ161072, No. GJJ161076, No. GJJ170953), The Education Planning Project of Jiangxi Province (No. 15YB138, No. 17YB211).
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Wang, X., Peng, H., Deng, C., Li, L., Zheng, L. (2019). An Improved Firefly Algorithm Hybrid with Fireworks. In: Peng, H., Deng, C., Wu, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2018. Communications in Computer and Information Science, vol 986. Springer, Singapore. https://doi.org/10.1007/978-981-13-6473-0_3
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DOI: https://doi.org/10.1007/978-981-13-6473-0_3
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