| 用自组织迁移算法改进的社会认知优化算法 |
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| 引用本文： | 王玲娟,蔚承建,李承相. 用自组织迁移算法改进的社会认知优化算法[J]. 计算机工程, 2008, 34(22): 201-203 |
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| 作者姓名： | 王玲娟 蔚承建 李承相 |
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| 作者单位： | 南京工业大学信息科学与工程学院,南京,210009;南京工业大学信息科学与工程学院,南京,210009;南京工业大学信息科学与工程学院,南京,210009 |
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| 摘 要： | 结合自组织迁移算法和社会认知优化的优点，在社会认知优化中融入自组织迁移的过程，通过增加2个参数协调两者的优化进程。经过大量的实验确定这2个参数的适当取值，完善了算法。该算法对最终的优化结果产生的影响微小，且在早期可以就获得较快的收敛 速度。
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| 关 键 词： | 演化计算 社会认知优化 自组织迁移算法 |
| 修稿时间： | |
Society Cognitive Optimization Algorithm Modified with Self-organizing Migrating Algorithm |
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| WANG Ling-juan,WEI Cheng-jian,LI Cheng-xiang. Society Cognitive Optimization Algorithm Modified with Self-organizing Migrating Algorithm[J]. Computer Engineering, 2008, 34(22): 201-203 |
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| Authors: | WANG Ling-juan WEI Cheng-jian LI Cheng-xiang |
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| Affiliation: | (College of Information Science and Engineering, Nanjing University of Technology, Nanjing 210009) |
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| Abstract: | To combine the advantages of Self-Organizing Migrating Algorithm(SOMA) and Society Cognitive Optimization(SCO), two parameters are used in the optimization to put SOMA process in SCO, resulting in a good improvement. Large number of experiments have been done and two parameters have been chosen which fit the algorithm most and perfect it. Although it causes a slight effect to the optimization solution, the improved optimization algorithm puts the convergence speed to a more quickly level. |
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| Keywords: | evolutionary computation Society Cognitive Optimization(SCO) Self-Organizing Migrating Algorithm(SOMA) |
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