dijkstra

问题 In my implementation of Dijkstra's algorithm I have 1 array with all nodes and 1 priority queue with all nodes. Whenever a node is dequeued I update all adjacent nodes with new distance and where it came from, so I can backtrack the path. The node in the priority queue is updated with new distance and the node in the array is updated where it came from and with new distance. When a node is dequeued the final distance in the array is updated: PathInfo current = pq.remove(); path[current.pos]

问题 All implementation of Dijkstra's algorithms I have seen do not have a recursive function, but I have also read that by definition dynamic programming is an algorithm with a recursive function and "memory" of things already calculated. So is Dijkstra's algorithm with a loop qualified as dynamic programming? Or in order to qualify as dynamic algorithm I have to change a loop into a recursive function. 回答1: You address two questions: Dynamic Algorithms mean breaking a procedure down into simpler

问题 I'm running a Dikjstra's shortest path algorithm on a NetworkX Watts-Strogatz randomly generated graph and I want to color the edges of the path I've found differently from the rest of the edges before I draw the graph. My Dijkstra's algorithm returns a list of the nodes in the path as follows: dijkstra(graph, '5', '67') ['67', '62', '59', '56', '3', '99', '5'] How would I go about changing the color of the edges between these nodes to say blue instead of red? Note that the graph is randomly

问题 Say I have a graph with nodes representing cities and and relations representing possible connections between cities. A connection has a departure and an arrival time. I want to find the shortest path between cities A and B and the cost function is the total travel time. The travel time is the sum of waiting times between connections and connection times. I'm using the Java API and I have tried using the Dijkstra algorithm using GraphAlgoFactory.dijkstra(expander, costEvaluator) . My main

问题 So I've been attempting to analyze a specialized variant of Dijkstras algorithm that I've been working on. I'm after the worst case complexity. The algorithm uses a Fibonacci Heap which in the case of the normal Dijkstra would run in O(E + V log V). However this implementation needs to do a lookup in the inner loop where we update neighbours. This lookup will execute for every edge and will be in logarithmic time, where the lookup is in a datastructure that contains all edges. Also the graph

问题 I am given a directed graph where each edge has a cost.Taking advantage of the fact that there are at most two negative edges in the graph, my goal is to find shortest path distances from a given node s to all the nodes in V. The time complexity of the algorithm should be O(|E| + |V|*log|V|) , so I think I need to apply Dijkstra's algorithm. I am guessing that I need to translate my given graph somehow to a new graph with non-negative weights that a shortest path from s to v in this graph

问题 I am trying to print the shortest path for a specific adjacency matrix using dijktra's algorithm. My dijkstra algorithm works fine, I am getting the correct distances. However when printing out the path I am getting an incorrect path. Here is my code for printing the path: My first class is my driver that takes in an adjacency matrix. The matrix contains the size at the top of the file, the actual matrix in the middle, and the source vertex at the end of the file. That all works fine for

问题 I am working on application by using GraphStream Library. So far I have implemented Dijkstra's Shortest Path Algorithm. My graph is working fine but the readability of graph is not what I was expecting. Here is the screen shot of graph : As you can see that graph is not readable due to alot of edge crossing. Is there any way to make my graph more readable. I am studying Graph Stream Generators BUT I dont think that they will be best in my case. So I am looking for accurate solution to my

问题 I'm working on making the Dijkstra algorithm parallel. Per node threads are made to look at all the edges of the current node. This was made parallel with threads but there is too much overhead. This resulted in a longer time than the sequential version of the algorithm. ThreadPool was added to solve this problem but i'm having trouble with waiting until the tasks are done before I can move on to the next iteration. Only after all tasks for one node is done we should move on. We need the

问题 I was wondering if I can modify Dijkstra’a Alghorithm in this way: Let’s say there are 2 paths between two vertices with following lengths: 5, 8, 6, 9 // sum=28 2, 4, 8, 25 //sum=39 First path is shorter but after ignoring the longest edge in both I get the following sums: 19 and 14, so I choose the second path. Maybe there is different way to solve it, without using Dijkstra? 回答1: I'm not sure is this idea working, but on first it seems to me like it can. For each visited node, beside