One of the two main algorithms in finding the minimum spanning tree algorithms is the algorithm of Kruskal. Before getting into the details, let’s get back to the principles of the minimum spanning tree.
We have a weighted graph and of all spanning trees we’d like to find the one with minimal weight. As an example on the picture above you see a spanning tree (T) on the graph (G), but that isn’t the minimum weight spanning tree!
Here’s a classical task on graphs. We have a group of cities and we must wire them to provide them all with electricity. Out of all possible connections we can make, which one is using minimum amount of wire.
To wire N cities, it’s clear that, you need to use at least N-1 wires connecting a pair of cities. The problem is that sometimes you have more than one choice to do it. Even for small number of cities there must be more than one solution as shown on the image bellow.
Here we can wire these four nodes in several ways, but the question is, which one is the best one. By the way defining the term “best one” is also tricky. Most often this means which uses least wire, but it can be anything else depending on the circumstances.
As we talk on weighted graphs we can generally speak of a minimum weight solution through all the vertices of the graph.
By the way there might be more the one equally optimal (minimal) solutions. Continue reading Computer Algorithms: Minimum Spanning Tree
Along with breadth-first search, depth-first search is one of the two main methods to walk through a graph. This approach though is different. Breadth-first search (BFS) looks pretty much like starting from a vertex and expanding the searching process level by level. This means that first we get some information of all the successors of the given node and then we go further with the next level. In other words BFS is like a wave. Depth-first search is based on a different approach, which can be very useful in some specific algorithms.
Both methods can be useful in solving different tasks. Continue reading Computer Algorithms: Graph Depth-First Search