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An improved GT algorithm for solving complicated dynamic function optimization problems |
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| Authors: | Qing Zhang Yan Li Zhuo Kang Lishan Kang |
| Affiliation: | 1. School of Computer, China University of Geosciences, Wuhan, 430074, Hubei, China 2. School of Physics and Technonlogy, Huanggang Normal University, Huanggang, 438000, Hubei, China 3. Computer Center, Wuhan University, Wuhan, 430072, Hubei, China 4. State Key Laboratory of Software Engineering, Wuhan University, Wuhan, 430072, Hubei, China |
| Abstract: | An improved Guo Tao algorithm (IGT algorithm) is proposed for solving complicated dynamic function optimization problems, and a function optimization benchmark problem with constrained condition and two dynamic parameters has been designed. The results achieved by IGT algorithm have been compared with the results from the Guo Tao algorithm (GT algorithm). It is shown that the new algorithm (IGT algorithm) provides better results. This preliminarily demonstrates the efficiency of the new algorithm in complicated dynamic environments. |
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