行人导航的路由算法比较

发布于 2024-11-24 06:39:27 字数 132 浏览 2 评论 0原文

我目前正在开发行人导航软件,对我来说很难的主题是找到最适合该任务的路由算法。我听说A*是这类软件中实际使用的算法之一。

您能建议解决这个问题的其他算法吗?他们的表现如何比较?它们需要多少内存和空间?

预先感谢您的答复。

I'm currently working on software for pedestrian navigation and the topic that is hard for me is to find the routing algorithm best suited for that task. I heard that A* is one of the algorithms actually used in that kind of software.

Could you suggest other algorithms that solve this problem? How do they compare regarding performances? How much memory and space do they require?

Thanks in advance for answers.

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稳稳的幸福 2024-12-01 06:39:30

好吧,你可以看看迭代深化搜索。在我看来,这是解决您的问题的一种非常聪明的方法,但是由于该算法旨在进行完整的探索,因此您可能会面临相对于 A* 而言具有良好启发式的相当糟糕的时间复杂度的风险。

来自维基百科:

IDDFS 结合了深度优先搜索的空间效率和广度优先搜索
搜索的完整性(当分支因子有限时)。这是
当路径成本是深度的非递减函数时是最优的
节点的。 IDDFS 的空间复杂度为 O(bd),其中 b 是
分支因子,d 是最浅目标的深度。自从
迭代深化多次访问状态,看起来可能
浪费,但事实证明它并不那么昂贵,因为在树上最
的节点位于底层,因此如果
上层被多次访问。

再次,关于时间复杂度:

平衡良好的树中 IDDFS 的时间复杂度为
与深度优先搜索相同:O(bd)。

Well you could have a look at iterative deepening search. It's a very smart approach to your problem in my opinion, but you risk to have a quite bad time complexity with respect to A* with a good heuristic since the algorithm is designed to make a complete exploration.

From wikipedia:

IDDFS combines depth-first search's space-efficiency and breadth-first
search's completeness (when the branching factor is finite). It is
optimal when the path cost is a non-decreasing function of the depth
of the node. The space complexity of IDDFS is O(bd), where b is the
branching factor and d is the depth of shallowest goal. Since
iterative deepening visits states multiple times, it may seem
wasteful, but it turns out to be not so costly, since in a tree most
of the nodes are in the bottom level, so it does not matter much if
the upper levels are visited multiple times.

And again, for what concerns time complexity:

The time complexity of IDDFS in well-balanced trees works out to be
the same as Depth-first search: O(bd).

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