Shortest Paths in DAG solved by 164

Feb. 21, 2014, 5:43 p.m. by Rosalind Team

Topics: Graphs


There are two subclasses of graphs that automatically exclude the possibility of negative cycles: graphs without negative edges, and graphs without cycles. We already know how to efficiently handle the former (see the problem “Negative Weight Cycle”). We will now see how the single-source shortest-path problem can be solved in just linear time on directed acyclic graphs.

As before, we need to perform a sequence of updates (recall Bellman-Ford algorithm) that includes every shortest path as a subsequence. The key source of efficiency is that

In any path of a DAG, the vertices appear in increasing linearized order.
Therefore, it is enough to linearize (that is, topologically sort) the DAG by depth-first search, and then visit the vertices in sorted order, updating the edges out of each. The algorithm is given below.

Notice that our scheme doesn’t require edges to be positive. In particular, we can find longest paths in a DAG by the same algorithm: just negate all edge lengths.

Source: Algorithms by Dasgupta, Papadimitriou, Vazirani. McGraw-Hill. 2006.

Given: A weighted DAG with integer edge weights from $-10^{3}$ to $10^3$ and $n \le 10^5$ vertices in the edge list format.

Return: An array $D[1..n]$ where $D[i]$ is the length of a shortest path from the vertex $1$ to the vertex $i$ ($D[1]=0$). If $i$ is not reachable from $1$ set $D[i]$ to x.

Sample Dataset

5 6
2 3 4
4 3 -2
1 4 1
1 5 -3
2 4 -2
5 4 1

Sample Output

0 x -4 -2 -3

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