Shortest path problem in bipartite graph

In summary, the Bellman-Ford-Moore algorithm is used to compute shortest paths in a directed bipartite graph in O(nm) time. The number of iterations in this situation is min{n1, n2} + 1 = n1 + 1, and the algorithm takes O(m) time per iteration. However, there is uncertainty about the correctness of the number of iterations and how to explain it accurately. The goal is to prove that the number of iterations is not ##O(n_1+n_2)##, as it is normally on the order of the number of vertices. Any helpful ideas would be appreciated.
  • #1
SadPaul
2
0
Homework Statement
Let G = (N1 U N2, A) be a bipartite directed network. Suppose that n1 = |N1|, n2 = |N2|
and n1 < n2. Show that the Bellman Ford algorithm solves the shortest path
problem in this network in O(n1m) time.
Relevant Equations
-
Hey guys, I need a little help with this exercise so I know I'm on the right path.

My explanation:
The Bellman-Ford-Moore algorithm computes shortest paths in O(nm) time, so in this situation we say that in a directed bipartite graph the number of iterations that the algorithm will do is min{n1, n2} + 1 = n1 + 1 and the algorithm takes O(m) time per iteration, so the final time is O(n1m).

So far so good, but I' m not really certain if I compute the number of iterations correctly, or how to explain it better.
Any usefull ideas would be welcome!
 
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  • #2
I think the point here is to prove the number of iterations is not ##O(n_1+n_2)##, since normally the number of iterations is on the order of the number of vertices. You just kind of asserted it to be true.
 

Related to Shortest path problem in bipartite graph

1. What is a bipartite graph?

A bipartite graph is a type of graph where the vertices can be divided into two disjoint sets, such that all edges connect a vertex from one set to a vertex in the other set. In other words, there are no edges that connect vertices within the same set.

2. What is the shortest path problem in a bipartite graph?

The shortest path problem in a bipartite graph is the task of finding the shortest path between two vertices, where the starting vertex and ending vertex belong to different sets in the bipartite graph. This problem is commonly solved using algorithms such as Dijkstra's algorithm or the Bellman-Ford algorithm.

3. Why is the shortest path problem in a bipartite graph important?

The shortest path problem in a bipartite graph has many real-world applications, such as finding the most efficient route for transportation networks, optimizing supply chain logistics, and determining the shortest communication path in computer networks. It is also a fundamental problem in graph theory and has been extensively studied by mathematicians and computer scientists.

4. What are some challenges in solving the shortest path problem in a bipartite graph?

One of the main challenges in solving the shortest path problem in a bipartite graph is the large number of possible paths that need to be considered. In some cases, there may be an exponential number of paths to evaluate, making it computationally expensive. Additionally, some bipartite graphs may have negative edge weights, which can make it difficult to find the shortest path using traditional algorithms.

5. Are there any efficient algorithms for solving the shortest path problem in a bipartite graph?

Yes, there are several efficient algorithms for solving the shortest path problem in a bipartite graph. Some of the most commonly used algorithms include Dijkstra's algorithm, the Bellman-Ford algorithm, and the Floyd-Warshall algorithm. These algorithms have varying time complexities and can be chosen based on the specific characteristics of the bipartite graph and the desired level of accuracy.

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