| A hybrid genetic algorithm based on mutative scale chaos optimization strategy |
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| 作者姓名： | YanWang HongweiSun |
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| 作者单位： | [1]SchoolofInformationScienceandEngineering,JinanUniversity,Jinan250022,China；InformationEngineeringSchool,UniversityofScienceandTechnologyBeijing,Beijing100083,China [2]SchoolofScience,JinanUniversity,Jinan250022,China；InformationEngineeringSchool,UniversityofScienceandTechnologyBeijing,Beijing100083,China |
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| 摘 要： | In order to avoid such problems as low convergent speed and local optimal solution in simple genetic algorithms,a new hybrid gentic algorithm is proposed.In this algorithm,a mutative scale chaos optimization strategy is operated on the population after a genetic operation.And according to the searching process.The searching space of the optimal variables is gradually diminished and the regulating coefficient of the secondary searching process is gradually changed which will lead to the quick evolution of the population.The algorithm has such advantages as fast search,precise results and convenient using etc.The simulation results show that the performance of the method is better than that of simple genetic algorithms.
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| 关 键 词： | 浑沌 遗传算法 优化技巧 |
A hybrid genetic algorithm based on mutative scale chaos optimization strategy |
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| Yan Wang,Hongwei Sun,Yikang Sun.A hybrid genetic algorithm based on mutative scale chaos optimization strategy[J].Journal of University of Science and Technology Beijing,2002,9(6):470-473. |
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| Authors: | Yan Wang Hongwei Sun Yikang Sun |
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| Abstract: | In order to avoid such problems as low convergent speed and local optimal solution in simple genetic algorithms, a new hybrid genetic algorithm is proposed. In this algorithm, a mutative scale chaos optimization strategy is operated on the population after a genetic operation. And according to the searching process, the searching space of the optimal variables is gradually diminished and the regulating coefficient of the secondary searching process is gradually changed which will lead to the quick evolution of the population. The algorithm has such advantages as fast search, precise results and convenient using etc. The simulation results show that the performance of the method is better than that of simple genetic algorithms. |
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| Keywords: | genetic algorithm chaos imitative scale optimization |
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