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| 贪婪光线寻优算法的局部收敛性分析 | |
| 引用本文： | 沈继红,李加莲. 贪婪光线寻优算法的局部收敛性分析[J]. 吉林大学学报(理学版), 2012, 50(2): 208-212 |
| 作者姓名： | 沈继红 李加莲 |
| 作者单位： | 1. 哈尔滨工程大学 理学院, 哈尔滨 150001,2. 哈尔滨工程大学 自动化学院, 哈尔滨 150001 |
| 基金项目： | 黑龙江省自然科学基金(批准号:F200931) |
| 摘 要： | 光线寻优算法局部搜索能力弱和收敛性理论完善困难的问题, 提出一种贪婪光线寻优算法, 并通过理论推导证明了该算法的局部收敛性. 数值实验结果表明, 对于单极值非线性标准测试函数, 与粒子群算法和模拟退火算法相比, 贪婪光线寻优算法具有更高的收敛精度和稳定性. |
| 关 键 词： | 费马原理 智能优化 光线寻优算法 局部收敛性 |
| 收稿时间： | 2011-04-25 |
Local Convergence Analysis of Greedy Light Ray Optimization Algorithm |
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| SHEN Ji-hong,LI Jia-lian. Local Convergence Analysis of Greedy Light Ray Optimization Algorithm[J]. Journal of Jilin University: Sci Ed, 2012, 50(2): 208-212 | |
| Authors: | SHEN Ji-hong LI Jia-lian |
| Affiliation: | 1. College of Science, Harbin Engineering University, Harbin 150001, China;2. College of Automation, Harbin Engineering University, Harbin 150001, China |
| Abstract: | Light ray optimization algorithm is a new intelligent optimization algorithm with the weak local optimization ability and the difficulty of perfection of convergence theory.To solve these problems,greedy light ray optimization algorithm was proposed.Local convergence of the proposed algorithm was proved via theoretical derivation.Numerical experimental results show that for single extremal nonlinear standard testing functions,greedy light ray optimization algorithm has a higher convergent accuracy and stability compared with particle swarm optimization and simulated annealing. |
| Keywords: | Fermat’s principle intelligent optimization light ray optimization algorithm local convergence |
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