dijkstra

I have been working on dijkstra's algorithm for the past one week one I have the correct running code for it in java. It is using array for the computation of standard findMin function which gives you the vertex with smallest distance.Obviously it is O(n) and Now I am looking to implement it using Priority Queue(Min Heaps) What My thought process is: while (there are unseen Vertex) { vertex= get TheVertex WithSmallest Distance Yet;//(In can be done in O(log n) using heap) for this vertex { find all of the adjacent edges and traverse them. for a particular vertex which is not there in heap yet{

Okay, first of all I know Dijkstra does not work for negative weights and we can use Bellman-ford instead of it. But in a problem I was given it states that all the edges have weights from 0 to 1 (0 and 1 are not included). And the cost of the path is actually the product. So what I was thinking is just take the log. Now all the edges are negative. Now I know Dijkstra won't work for negative weights but in this case all the edges are negative so can't we do something so that Dijkstra would work. I though of multiplying all the weights by -1 but then the shortest path becomes the longest path.

朴素版 int dist[maxn], g[40][40]; bool vis[maxn]; void dijkstra(int cc) { //cc是单源节点编号 for (int i = 1; i <= n; i++) { dist[i] = g[i][cc]; } dist[cc] = 0; memset(vis, 0, sizeof(vis)); vis[cc] = 1; for (int i = 1; i <= n; i++) { int mark = -1, mindis = INF; for (int j = 1; j <= n; j++) { if (!vis[j] && dist[j] < mindis) { mindis = dist[j]; mark = j; } } vis[mark] = 1; for (int j = 1; j <= n; j++) { if (!vis[j]) { dist[j] = min(dist[j], dist[mark] + g[mark][j]); } } } } 来源： https://www.cnblogs.com/woxiaosade/p/11883150.html

This question already has answers here : Selecting A combination of minimum cost (5 answers) Closed 4 years ago . I have a interesting problem. I would like to know some good approaches to solve this. I have a small store in which I have 'n' number of products Each product as a non zero price associated with it A product looks like this { productId:productA; productName:ABC; price:20$ } To enhance the customer retention, I would like to bring in combo model to sell. That is, I define m number of combos Each combo looks like this { comboId:1; comboName:2; constituentProducts: {Product1,

I have a large graph, is there any other data structure other than adjacency list and "adjacency matrix" in c++ stl or some other data structure which I can employ for such a large graph, actually the adjacency matrix of my graph does not fit in the main memory. My graph is directed and I am implementing dijkstra algorithm in C++. I have seen the previous posts...but I am searching for a suitable data structure with respect to dijkstra. By large I mean a graph containing more than 100 million nodes and edges. It's common to represent adjacency lists as lists of integers, where the integer is

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? I will expand on comments to the question. The problem is, for some graphs, you can have an exponential number of shortest paths