寻路(路由,行程规划,...)在图形上与时间限制的算法路由、算法、行程、图形

2023-09-10 22:52:53 作者:浅色的泡沫

我有公交/火车/ ...停止,每个日期等到达/离开时间的数据库。我正在寻找一个方式做搜索最快(最短/最低/至少过渡)两个位置之间的往返。我想在未来的任意位置,使用OpenStreetMap的数据做站之间,距离车站步行到开始/结束,但暂时我只是想在数据库中查找两站之间的路径。

现在的问题是,我似乎无法找到有关此主题的很多信息,例如这个维基百科页面有大量的文字,在它绝对没有任何有用的信息。

什么我发现是 GTFS 格式,在谷歌公交使用。虽然我所在的城市没有提供一个公共数据馈送(甚至不是一个私人的),我已经把所有的GTFS包含的重要信息,使转型将是微不足道的。

有一些GTFS为基础的软件,比如像 OpenTripPlanner 的也可以用的 OpenStreetMap的

然而的,路由code是不是有据可查的(至少从我发现),我并不需要整个事情。

所有我要找的是我可以使用的算法,他们的表现,也许一些伪code。

一些很好的概述

因此​​,的问题是,给予停止,路线和到达/离开/旅行时间列表,我怎么能很容易地找到从STOP最快的路径,停止B?

解决方案 型号您的问题,一个图表。每站将一个顶点,和 每个公交/火车将是一个边缘。 创建一个函数 W:Edges-> R ,表示时间/资金/ ...为每条边。 现在,你有一个典型的最小路径问题,可以通过解决 Dijkstra算法,该发现从给定的源的所有顶点最小的路径。

(*)对于至少过渡',你的体重实际上是各1个边,所以你甚至可以通过运行的 BFS 甚至双向 BFS代替Dijkstra算法,正如我在解释post [它是社会距离的解释,却是相同的算法实际上]。

路由器可以限制IP上网吗

修改 作为编辑的图形[时序]您的评论中提到[价格和转换次数,我所提到的上面仍然适用,因为这些图都是静态]的非静态性质,可以使用距离矢量路由算法的,这实际上意味着工作动态图,并且是贝尔曼Ford算法​​。 的算法思路:

在周期性的,每个顶点将其距离向量其 邻居[矢量显示多少成本,从发送顶点旅行,彼此的顶点。 在其邻国尝试更新它们的路由表[通过优势是最好的移动到每个目标] 对于你的情况,每个节点知道什么是让邻国以最快的方式,[行程时间+等待时间],它[顶点/站】增加这个数字在距离向量的每个主菜,以知道如何,这将多少时间,才能到目的地。当校车,出行时间应重新计算所有节点[从此源],和新的载体应该发送给它的邻居

I have a database of bus/train/... stops and the arrival/departure times on each date and so on. I'm looking for a way to do a search for the fastest(shortest/cheapest/least transitions) trip between two locations. I would like to have arbitrary locations in the future, using OpenStreetMap data to do walking between stops and from stops to start/end, however for the time being I just want to find path between two stops in the database.

The problem is I can't seem to find much info about this subject, for example this Wikipedia page has a lot of text with absolutely no useful information in it.

What I've found is the GTFS format, used in Google Transit. While my city doesn't provide a public data feed (not even a private one), I already have all the important information that the GTFS contains and making a transformation would be trivial.

There is some GTFS-based software, like like OpenTripPlanner that can also do pedestrian/car/bike routing using OpenStreetMap.

However, the routing code isn't well documented (at least from I've found) and I don't need the whole thing.

All I'm looking for is some good overview of the algorithms I could use, their performance, maybe some pseudocode.

So, the question is, given a list of stops, routes and arrival/departure/travel times, how can I easily find the fastest path from stop A to stop B?

解决方案

Model your problem as a graph. Each station will be a Vertex, and each bus/train will be an Edge. create a function w:Edges->R,that indicates the time/money/... for each edge. now, you have a typical minimum path problem, which can be solved by Dijkstra algorithm, which finds minimum path to all vertices from a given source.

(*) For 'least transitions', your weight is actually 1 for each edge, so you can even optimize this by running a BFS or even bi-directional BFS instead of dijkstra, as I explained in this post [It is explained for social distance, but it is the same algorithm actually].

EDIT as an edit to the non-static nature of the graph [for timing] you mentioned on comments [for price and number of transitions, what I have mentioned above still applies, since these graphs are static], you can use a distance vector routing algorithm, which actually meant to work for dynamic graphs, and is a distributed variation of Bellman Ford algorithm. The algorithm idea:

periodically, every vertex sends its "distances vector" to its neighbors [the vector indicates how much it 'costs' to travel from the sending vertex, to each other vertex. Its neighbors try to update their routing tables [through which edge is it best to move to the each target] for your case, each node knows what is the fastest way to get to its neighbors, [travel time + wait time] and it [the vertex/station] adds this number to each entree in the distance vector, in order to know how to and how much time it will take, to get to the destination. When a bus leaves, the travel time should be re-calculated to all nodes [from this source], and the new vector should be sent to its neighbors