Do we need visited array in Dijkstra?

Yes, you’re right. There’s no need for the visited vector. If a node is visited then there cannot exist a distance to that node that is shorter, so, as you said, checking alt < dist[v] is enough.

Does Dijkstra visit all nodes?

Do BFS and Dijkstra’s algorithm check all nodes? No, not necessarily. Both of these algorithms discover nodes one-by-one in increasing order of their distance from the source. Once the destination node has been discovered, the algorithm can stop early.

What is the problem with Dijkstra algorithm?

One of the problems with using Dijkstra’s algorithm on the Internet is that you must have a complete representation of the graph in order for the algorithm to run. The implication of this is that every router has a complete map of all the routers in the Internet.

Why is Dijkstra better than a *?

A* is just like Dijkstra, the only difference is that A* tries to look for a better path by using a heuristic function which gives priority to nodes that are supposed to be better than others while Dijkstra’s just explore all possible paths.

Does Dijkstra’s algorithm work with negative weights?

Since Dijkstra’s goal is to find the optimal path (not just any path), it, by definition, cannot work with negative weights, since it cannot find the optimal path.

Does Dijkstra work for disconnected graphs?

This is true no matter whether the input graph is connected or disconnected. The standard algorithm for Dijkstra’s algorithm sets the distance correctly for all vertices in all components (not just the ones in the same connected component as the source).

Why is Dijkstra’s algorithm good?

The main advantage of Dijkstra’s algorithm is its considerably low complexity, which is almost linear. However, when working with negative weights, Dijkstra’s algorithm can’t be used. , if we need to calculate the shortest path between any pair of nodes, using Dijkstra’s algorithm is not a good option.

Is Dijkstra informed or uninformed?

Dijkstra’s algorithm is used for graph searches. It is optimal, meaning it will find the single shortest path. It is uninformed, meaning it does not need to know the target node before hand.