| 变权值加快收敛的路径寻优实时算法 |
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| 引用本文： | 谭德荣,严新平.变权值加快收敛的路径寻优实时算法[J].交通运输工程学报,2004,4(1):118-120. |
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| 作者姓名： | 谭德荣 严新平 |
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| 作者单位： | 1. 山东理工大学,交通学院,山东,淄博,255012
2. 武汉理工大学,ITS研究中心,湖北,武汉,430063 |
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| 基金项目： | 教育部博士点基金项目(20010497002) |
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| 摘 要： | 为获得满意解为目标的最优路径选择问题，给出了一种加权的LRTA^*(Learning Real-TimeA^*)算法，通过改变估价函数值更新规则与解时间和解质量的相对折中，加快算法收敛速度。实例应用表明，该方法比LRTA^*算法更快地收敛于满意解，是一种求解大城市稠密路网两点间最优路径的有效方法。
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| 关 键 词： | 智能交通 最优路径 启发式搜索算法 人工智能 值更新规则 |
| 文章编号： | 1671-1637(2004)01-0118-03 |
| 修稿时间： | 2003年4月15日 |
Real-time algorithm of finding optimal path with changing weight to speed up convergence |
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| TAN De-rong,YAN Xin-ping.Real-time algorithm of finding optimal path with changing weight to speed up convergence[J].Journal of Traffic and Transportation Engineering,2004,4(1):118-120. |
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| Authors: | TAN De-rong YAN Xin-ping |
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| Institution: | TAN De-rong~1,YAN Xin-ping~2 |
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| Abstract: | For obtaining a satisfactory shortest path, this paper proposed an improved LRTA~* to speed up search algorithm convergence through changing value-update rules. Through the trade-off of time and quality of solution, the convergence speed was fasted. Application result shows that the method converges suboptimal solution faster than LRTA~*, it is a better algorithm to solve the satisfactory solution between O-D for a big density route network. 1 tab, 1 fig, 8 refs. |
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| Keywords: | intelligent transport optimal path heuristic search algorithm artificial intelligence value-update rules |
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