Creating a undirected graph and traversing it using BFS in QuickGraph

breadth first search shortest path
dfs and bfs graph traversal example
dfs on undirected graph
depth first search
bfs pseudocode
depth first search python
breadth first search in artificial intelligence
bfs using adjacency matrix

I'm trying to figure out how to create a new instance of a undirected weighted graph using QuickGraph for C#.

My goal is to create a undirected weighted graph populated with a random number of nodes and randomly generated start and finish nodes whose shortest path can found using Breadth-First Search algorithm.

There's not much to the documentation, so if anyone can provide any assistance that would be appreciated.

Richard, QuickGraph does not do any of this for you, it only makes events available which you can subscribe to. By subscribing to those events you can respond accordingly. From the admittedly lacking QuickGraph documentation on Depth First Search (yes, I realize you're doing BFS and not DFS, but the concept of how to subscribe to events is the same):

  1. InitializeVertex, invoked on each vertex before starting the computation,
  2. DiscoverVertex, invoked when a vertex is encountered for the first time,
  3. ExamineEdge, invoked on every out-edge of each vertex after it is discovered,
  4. TreeEdge, invoked on each edge as it becomes a member of the edges that form the search tree.
  5. FinishVertex, invoked on a vertex after all of its out edges have been added to the search tree and all of the adjacent vertices have been discovered (but before their out edges have been examined).

By the way, open up Reflector and take a look at QuickGraph.Algorithms.Observers. And your shortest path requirement would be easier with a different method than BFS.

Find all paths between two graph nodes, obviously if you are using a directed graph and you want all undirected paths between //Behaves identical to Dijkstra's algorithm, override to make it A* } private It only calculates the extra steps needed and doesnt traverse any old paths twice. The following functions (modified BFS with a recursive path-finding function� I'm trying to figure out how to create a new instance of a undirected weighted graph using QuickGraph for C#. My goal is to create a undirected weighted graph populated with a random number of nodes and randomly generated start and finish nodes whose shortest path can found using Breadth-First Search algorithm.

There's no documentation for this algorithm yet; but there's the next best thing (or perhaps even a better thing): a Unit Test!

If you download the QuickGraph sources, and find the BreadthFirstAlgorithmSearchTest.BreadthFirstSearchAll(), you will see an example usage of the algorithm which runs BFS on all the directed graphs in the test project.

Breadth First Search or BFS for a Graph, source vertex. BFS(int s) traverses vertices This class represents a directed graph using Create a graph given in the above diagram. Graph� Hope DFS Traversal is clear, let’s move to our next Graph Traversal that is BFS. BFS Traversal. In BFS traversal, we start from a source vertex, explore that vertex (Visit and print all the neighbours of that vertex) before moving to the next vertex. Let’s take an example to understand it, Tree Data Structure

There was a brief thread on Github which had a useful basic example of how to setup BFS and get some results from it.

The other details specific to your application (creating a random graph, etc.) are obviously not part of this example.

Source: https://github.com/YaccConstructor/QuickGraph/issues/189#issuecomment-487493207

Here's a complete example:

UndirectedGraph<string, Edge<string>> g = new UndirectedGraph<string, Edge<string>>();

g.AddVerticesAndEdge(new Edge<string>("0", "1"));
g.AddVerticesAndEdge(new Edge<string>("0", "2"));
g.AddVerticesAndEdge(new Edge<string>("2", "3"));

var algo = new UndirectedBreadthFirstSearchAlgorithm<string, Edge<string>>(g);

var observer = new UndirectedVertexPredecessorRecorderObserver<string, Edge<string>>();

var rootVertex = "0";
using (observer.Attach(algo))
{
    algo.Compute(rootVertex);
}

var targetVertex = "3";
bool foundPath = observer.TryGetPath(targetVertex, out IEnumerable<Edge<string>> path);

path will then contain the two edges:

[0]: "0"->"2"
[1]: "2"->"3"

Shortest path in an unweighted graph, The idea is to use a modified version of Breadth-first search in which we keep storing the Creating graph given in the above diagram. Since you are using an undirected graph, the alg probably is working as intended. Creating a undirected graph and traversing it using BFS in QuickGraph. 2.

Depth-first search, Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures DFS may also be used to collect a sample of graph nodes. However, incomplete DFS, similarly to incomplete BFS, is biased towards nodes If the original graph is undirected then all of its edges are tree edges or back edges. To solve this problem, we will find all connected nodes of the undirected graph using any of the traversal techniques (BFS or DFS) and then create a visited array for all nodes that are visited for that no double visit is not there. On visiting connected nodes that are connected directly or indirectly, we will find the minimum of all connections.

Best 20 NuGet dfs Packages, QuickGraph provides generic directed/undirected graph datastructures and algorithms for .Net, Silverlight You can use this package in your project to traverse the graph in BFS and DFS manner. Score: 3.5 Library to create simple Mazes. Breadth First Search (BFS) This is a very different approach for traversing the graph nodes. The aim of BFS algorithm is to traverse the graph as close as possible to the root node. Queue is used in the implementation of the breadth first search. Let’s see how BFS traversal works with respect to the following graph:

Namespaces - QuickGraph, Equality comparer for array of T using Equals1 method. ArrayUndirectedGraph<' TVertex, 'TEdge>. An immutable undirected graph data structure based on� Breadth First Traversal (or Search) for a graph is similar to Breadth First Traversal of a tree (See method 2 of this post). The only catch here is, unlike trees, graphs may contain cycles, so we may come to the same node again. To avoid processing a node more than once, we use a boolean visited