shortest-path

问题 Consider the following image which is from Mathworks: I have labelled the blobs with [L, num]= bwlabel(I); How do I connect all the blobs iteratively,i.e.start with one blob and find the nearest one to it.Consider the left-most two blobs, there can be many lines that can be drawn from many points of a blob to connect to the other blob, but the shortest one would be obtained by finding the pixel of a blob that is nearest to the other blob, find a similar pixel in the other blob and connect

问题 Given a directed graph G=(V,E) , two vertices s , t and two weight functions w1 , w2 , I need to find the shortest path from s to t by w2 among all the shortest paths between s to t by w1 . First of all , how could I find all the shortest paths between two vertices s and t ? Dijkstra's algorithm helps us find shortest path from a vertex to to every other accessible vertex, is it possible to modify it in order to get all the shortest paths between two vertices? 回答1: I will expand on comments

问题 In a directed graph with non-negative edge weights I can easily find shortest path from u to v using dijkstra's. But is there any simple tweak to Dijkstra's so that I can find shortest path from u to v through a given vertex w. Or any other algorithm suggestions? 回答1: Find the shortest path from u to w, then the shortest path from w to v. 回答2: Find shortest path from u to w Find shortest path from w to v Then u->w->v is the shortest path. You can do it by running Dijkstra for two times, but

问题 On the Wikipedia page for Dijkstra's algorithm, they mark visited nodes so they wouldn't be added to the queue again. However, if a node is visited then there can be no distance to that node that is shorter, so doesn't the check alt < dist[v] already account for visited nodes? Am I misunderstanding something about the visited set? for each neighbor v of u: alt := dist[u] + dist_between(u, v); // accumulate shortest dist from source if alt < dist[v] && !visited[v]: dist[v] := alt; // keep the

问题 I am looking for an explanation why the AStar / A* algorithm is called AStar. All similar (shortest path problem) algorithms are often named like its developer(s), so what is AStar standing for? 回答1: There were algorithms called A1 and A2. Later, it was proved that A2 was optimal and in fact also the best algorithm possible, so he gave it the name A* which symbolically includes all possible version numbers. Source: In 1964 Nils Nilsson invented a heuristic based approach to increase the speed

问题 I have a graph with an s and t vertex that I need to find the shortest path between. The graph has a lot of special properties that I would like to capitalize on: The graph is a DAG (directed acyclic graph). I can create a topological sort in O(|V|) time, faster than the traditional O(|V + E|). Within the topological sort, s is the first item in the list and t is the last. I was told that once I have a topological sort of the vertices I could find the shortest path faster than my current

问题 So I came to this beautiful problem that asks you to write a program that finds whether a negative infinity shortest path exists in a directed graph. (Also can be thought of as finding whether a "negative cycle" exists in the graph). Here's a link for the problem: http://uva.onlinejudge.org/index.php?option=com_onlinejudge&Itemid=8&page=show_problem&problem=499 I successfully solved the problem by running Bellman Ford Algorithm twice by starting with any source in the graph. The second time I

问题 There is a custom implementation of KSPA which needs to be re-written. The current implementation uses a modified Dijkstra's algorithm whose pseudocode is roughly explained below. It is commonly known as KSPA using edge-deletion strategy i think so. (i am a novice in graph-theory). Step:-1. Calculate the shortest path between any given pair of nodes using the Dijkstra algorithm. k = 0 here. Step:-2. Set k = 1 Step:-3. Extract all the edges from all the ‘k-1’ shortest path trees. Add the same

问题 There is a custom implementation of KSPA which needs to be re-written. The current implementation uses a modified Dijkstra's algorithm whose pseudocode is roughly explained below. It is commonly known as KSPA using edge-deletion strategy i think so. (i am a novice in graph-theory). Step:-1. Calculate the shortest path between any given pair of nodes using the Dijkstra algorithm. k = 0 here. Step:-2. Set k = 1 Step:-3. Extract all the edges from all the ‘k-1’ shortest path trees. Add the same

问题 Suppose I have 10 points. I know the distance between each point. I need to find the shortest possible route passing through all points. I have tried a couple of algorithms (Dijkstra, Floyd Warshall,...) and they all give me the shortest path between start and end, but they don't make a route with all points on it. Permutations work fine, but they are too resource-expensive. What algorithms can you advise me to look into for this problem? Or is there a documented way to do this with the above