An Optimum Vehicular Path Solution with Multi-heuristics

机译：具有多种启发式的最优车辆路径解决方案

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Heuristics have been widely used in artificial intelligence related fields including path finding. In this paper, the author argue that different heuristics can be integrated to solve the path finding problems and set forward a solution integrating greedy heuristic, directional heuristic and hierarchical heuristic. In greedy heuristic, an improved Dijkstra's algorithm based on quad heap is set forward. Then an MBR for ellipse is presented to limit the searching extent. Thirdly, hierarchical spatial reasoning is used to build another heuristic considering the hierarchical structure of road network, which makes the optimum path selection completed in higher hierarchies as much as possible. A case study is carried out with a real road network to verify the efficiency and validation of the solution integrating the above algorithms.

机译：启发式方法已广泛应用于人工智能相关领域，包括路径查找。在本文中，作者认为可以集成不同的启发式方法来解决寻路问题，并提出一种将贪婪启发式，定向启发式和分层启发式结合起来的解决方案。在贪婪启发式算法的基础上，提出了一种改进的基于四堆的Dijkstra算法。然后提出了一种椭圆的MBR来限制搜索范围。第三，考虑路网的层次结构，采用层次空间推理来构建另一种启发式方法，从而使最佳路径选择尽可能地在较高层次中完成。通过一个真实的道路网络进行案例研究，以验证集成上述算法的解决方案的效率和有效性。

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来源
《International Conference on Computational Science pt.4; 20040606-20040609; Krakow; PL》|2004年|P.964-971|共8页
会议地点 Krakow(PL);Krakow(PL)
作者
Feng Lu; Yanning Guan;
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作者单位

State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R.China;

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原文格式 PDF
正文语种 eng
中图分类理论、方法;
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An Optimum Vehicular Path Solution with Multi-heuristics

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