Abstract
Optimization problem is one of the most important problems encountered in the real world. In order to effectively deal with optimization problem, some intelligence algorithms have been put forward, for example, PSO, GA, etc. To effectively solve this kind of problem, in this paper, crossing strategy of DNA fragments is proposed to explore the effect on intelligence algorithms based on American genetic biologist Morgan theory. We mainly focus on DNA fragment decreasing strategy and DNA fragment increasing strategy based on disturbance in PSO. In order to test the role of the DNA mechanism, three test benchmarks were selected to conduct the analysis of convergence property and statistical property. The simulation results show that the PSO with DNA mechanism have an advantage on algorithm performance efficiency compared with the original proposed PSO. Therefore, DNA mechanism is an effective method for improving swarm Intelligence algorithm performance.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grants nos. 71461027, 71001072, 71271140, 71471158). Guizhou province science and technology fund (Qian Ke He J [2012] 2340 and [2012]2342, LKZS [2012]10 and [2012]22); Guizhou province natural science foundation in China (Qian Jiao He KY [2014]295); The educational reform project in guizhou province department of education (Qian jiao gao fa[2013]446); Guizhou province college students’ innovative entrepreneurial training plan(201410664004); 2013 and 2014 Zunyi 15851 talents elite project funding.
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Liu, Y., Niu, B., Chan, F.T.S., Liu, R., changling, S. (2015). Application of Disturbance of DNA Fragments in Swarm Intelligence Algorithm. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_70
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DOI: https://doi.org/10.1007/978-3-319-22186-1_70
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