| 改进BFO算法在函数优化问题上的应用 |
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| 引用本文： | 曹天问,雷秀娟.改进BFO算法在函数优化问题上的应用[J].计算机工程与应用,2013,49(13):175-179. |
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| 作者姓名： | 曹天问 雷秀娟 |
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| 作者单位： | 陕西师范大学 计算机科学学院，西安 710062 |
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| 摘 要： | 分析了细菌觅食优化（BFO）算法的原理以及当前的研究状况，主要根据心理学家爱德华·桑代克（E L Thordike）的经典效果律和经济学家巴莱多的巴莱多定律等对标准BFO算法存在的不足进行改进；将改进后的BFO算法在函数优化问题上进行仿真实验，实验结果表明改进后的BFO算法比标准BFO算法具有更快的收敛速度和更强的搜索性能。
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| 关 键 词： | 细菌觅食优化（BFO） 趋向 最大游动步长 复制 择优迁徙 |
Application of improved Bacteria Foraging Optimization algorithm on function optimization |
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| CAO Tianwen,LEI Xiujuan.Application of improved Bacteria Foraging Optimization algorithm on function optimization[J].Computer Engineering and Applications,2013,49(13):175-179. |
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| Authors: | CAO Tianwen LEI Xiujuan |
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| Affiliation: | College of Computer Science, Shanxi Normal University, Xi’an 710062, China |
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| Abstract: | The principle of the Bacterial Foraging Optimization（BFO） algorithm as well as the current research status is analyzed firstly, then the standard BFO algorithm is improved to overcome its insufficiency mainly based on the classic effect law of psychologist Edward Thorndike grams（E L Thordike） and the Pareto’s law of economist Pareto. The experimental results on Benchmark function optimization problems show that the improved BFO algorithm has the higher searching performance and convergence rate than the standard BFO algorithm. |
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| Keywords: | Bacteria Foraging Optimization（BFO） trends the maximum swim step replication preferential migration |
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