Spanning tree | Polynomial-time problems
A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected, edge-weighted undirected graph that connects all the vertices together, without any cycles and with the minimum possible total edge weight. That is, it is a spanning tree whose sum of edge weights is as small as possible. More generally, any edge-weighted undirected graph (not necessarily connected) has a minimum spanning forest, which is a union of the minimum spanning trees for its connected components. There are many use cases for minimum spanning trees. One example is a telecommunications company trying to lay cable in a new neighborhood. If it is constrained to bury the cable only along certain paths (e.g. roads), then there would be a graph containing the points (e.g. houses) connected by those paths. Some of the paths might be more expensive, because they are longer, or require the cable to be buried deeper; these paths would be represented by edges with larger weights. Currency is an acceptable unit for edge weight – there is no requirement for edge lengths to obey normal rules of geometry such as the triangle inequality. A spanning tree for that graph would be a subset of those paths that has no cycles but still connects every house; there might be several spanning trees possible. A minimum spanning tree would be one with the lowest total cost, representing the least expensive path for laying the cable. (Wikipedia).
Minimum Spanning Tree In Data Structure | What Is Spanning Tree? | Data Structures|Simplilearn
This video is based on minimum Spanning Trees in Data structures. This Spanning Tree Tutorial will acquaint you with the fundamentals of spanning trees and their importance. It also covers the methodology to generate spanning trees from a given graph. The topics covered in this video are:
From playlist Data Structures & Algorithms [2022 Updated]
From playlist M. Graph Theory
AQA Decision 1 4.01a Introducing Minimum Spanning Trees and Kruskal's Algorithm
I introduce the concept of finding a minimum spanning tree for a network by working through an example of Kruskal's Algorithm.
From playlist [OLD SPEC] TEACHING AQA DECISION 1 (D1)
Networks - Minimal spanning tree
In this lesson on Networks you learn how to draw a minimal spanning tree for a network This topic is taught in Queensland Maths A, Year 11 or Year 12.
From playlist Maths A / General Course, Grade 11/12, High School, Queensland, Australia
OCR MEI MwA E: Minimum Spanning Trees: 01 Introduction & Greedy Algorithms
https://www.buymeacoffee.com/TLMaths Navigate all of my videos at https://sites.google.com/site/tlmaths314/ Like my Facebook Page: https://www.facebook.com/TLMaths-1943955188961592/ to keep updated Follow me on Instagram here: https://www.instagram.com/tlmaths/ Many, MANY thanks to Dea
From playlist TEACHING OCR MEI Modelling with Algorithms
Prim's Minimum Spanning Tree Algorithm | Graph Theory
Prim's Minimum Spanning Tree Algorithm Support me by purchasing the full graph theory course on Udemy which includes additional problems, exercises and quizzes not available on YouTube: https://www.udemy.com/course/graph-theory-algorithms Algorithms repository: https://github.com/william
From playlist Graph Theory Playlist
Kruskal's Algorithm (Decision Maths 1)
Powered by https://www.numerise.com/ Kruskal's Algorithm for finding the minimum spanning tree of a network www.hegartymaths.com http://www.hegartymaths.com/
From playlist Decision Maths 1 OCR Exam Board (A-Level tutorials)
Prim's Algorithm for Minimum Spanning Trees (MST) | Graph Theory
We go over Prim's Algorithm, and how it works to find minimum spanning trees (also called minimum weight spanning trees or minimum cost spanning trees). We'll also see two examples of using Prim's algorithm to find minimum spanning trees in connected weighted graphs. This algorithm is on
From playlist Graph Theory
Kruskals Algorithm | Kruskals Algorithm For Minimum Spanning Trees | Data Structures | Simplilearn
Don't forget to participate in challenging activity at --:-- This video on Kruskal Algorithm will acquaint you with the theoretical explanation and complete drive-through example for constructing a minimum spanning tree for given graph. This data structure tutorial will acquaint you with c
From playlist Data Structures & Algorithms
This is Lecture 14 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 2007. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/2007/lecture13.pdf More informa
From playlist CSE373 - Analysis of Algorithms - 2007 SBU
Lecture 13 - Minimum Spanning Trees
This is Lecture 13 of the CSE373 (Analysis of Algorithms) taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 1997. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/1997/lecture17.pdf
From playlist CSE373 - Analysis of Algorithms - 1997 SBU
Due to the COVID-19 pandemic, Carnegie Mellon University is protecting the health and safety of its community by holding all large classes online. People from outside Carnegie Mellon University are welcome to tune in to see how the class is taught, but unfortunately Prof. Loh will not be o
From playlist CMU 21-228 Discrete Mathematics
Lecture 15 - Exploiting Graph Algorithms
This is Lecture 15 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 2007. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/2007/lecture14.pdf More informa
From playlist CSE373 - Analysis of Algorithms - 2007 SBU
CSE 373 -- Lecture 13, Fall 2020
From playlist CSE 373 -- Fall 2020
Lecture 13 - Minimum Spanning Trees I
This is Lecture 13 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www3.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: https://www.cs.stonybrook.edu/~skiena/373/newlectures/lecture13.pdf More inf
From playlist CSE373 - Analysis of Algorithms 2016 SBU
MIT 6.042J Mathematics for Computer Science, Spring 2015 View the complete course: http://ocw.mit.edu/6-042JS15 Instructor: Albert R. Meyer License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.042J Mathematics for Computer Science, Spring 2015
9 5 Counting Minimum Cuts 7 min
From playlist Algorithms 1
CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2)
This is Lecture 15 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 2012.
From playlist CSE373 - Analysis of Algorithms - 2012 SBU