Capacitated minimum spanning tree is a minimal cost spanning tree of a graph that has a designated root node and satisfies the capacity constraint . The capacity constraint ensures that all subtrees (maximal subgraphs connected to the root by a single edge) incident on the root node have no more than nodes. If the tree nodes have weights, then the capacity constraint may be interpreted as follows: the sum of weights in any subtree should be no greater than . The edges connecting the subgraphs to the root node are called gates. Finding the optimal solution is NP-hard. (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
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
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
Kruskal's Algorithm for Minimum Spanning Trees (MST) | Graph Theory
We go over Kruskal'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 Kruskal's algorithm to find minimum spanning trees in connected weighted graphs. This algorithm
From playlist Graph Theory
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
Chandra Chekuri: On element connectivity preserving graph simplification
Chandra Chekuri: On element-connectivity preserving graph simplification The notion of element-connectivity has found several important applications in network design and routing problems. We focus on a reduction step that preserves the element-connectivity due to Hind and Oellerman which
From playlist HIM Lectures 2015
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)
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
9 5 Counting Minimum Cuts 7 min
From playlist Algorithms 1
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
Determine the Possible Minimum and Maximum from a Histogram
This video explains how to determine the possible minimum and maximum from a histogram. http://mathispower4u.com
From playlist Statistics: Describing Data
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