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| 差分演化算法中变异策略的改进与算法的优化 | |
| 引用本文： | 刘志军,唐柳,刘克铜,吴冬方.差分演化算法中变异策略的改进与算法的优化[J].化工自动化及仪表,2010,37(9):5-8. |
| 作者姓名： | 刘志军 唐柳 刘克铜 吴冬方 |
| 作者单位： | 1. 北京工业大学,北京,100124;河北机电职业技术学院,河北,邢台,054048 2. 北京工业大学,北京,100124 3. 河北机电职业技术学院,河北,邢台,054048 |
| 摘 要： | 自然界生物体进化现象可以形式化成一些优化算法,如差分演化算法、粒子群算法等。其中,差分演化算法在数值函数优化方面的性能要优于其它的优化算法。通过对差分演化算法的变异策略改进,使优化后的差分演化算法在函数优化方面性能得到进一步提高。通过十个基准函数的仿真测试可以验证这一结果。 |
| 关 键 词： | 差分演化算法 变异策略 基准函数 优化 |
Differential Evolution Algorithm in the Mutation Strategy Improvement and Algorithm Optimization |
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| LIU Zhi-jun,TANG Liu,LIU Ke-tong,WU Dong-fang.Differential Evolution Algorithm in the Mutation Strategy Improvement and Algorithm Optimization[J].Control and Instruments In Chemical Industry,2010,37(9):5-8. | |
| Authors: | LIU Zhi-jun TANG Liu LIU Ke-tong WU Dong-fang |
| Affiliation: | LIU Zhi-jun1,2,TANG Liu1,LIU Ke-tong2,WU Dong-fang2(1.Beijing University of Technology,Beijing 100124,China,2.The Mechanic and Electronic Technology Institute of Hebei,Xingtai 054048,China) |
| Abstract: | Natural organism evolution phenomenon can be formalized into some optimization algorithms,such as differential evolution algorithm(DE),particle swarm optimization algorithm.The performance of DE algorithm is superior to other algorithm in numerical function optimization.The mutation strategy was improved so that the optimized DE algorithm performance was further improved on function optimization.The results validated through simulation tests on 10 benchmark functions. |
| Keywords: | DE algorithm mutation strategy benchmark functions optimization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
