Spanning tree

Capacitated minimum spanning tree

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).

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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]

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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

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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

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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

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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

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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

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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)

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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

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Lecture 14 - Shortest Paths

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

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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

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CMU Discrete Mathematics 4/9

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

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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

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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

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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

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2.10.5 Spanning Trees: Video

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

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Local search (optimization) | Graph (discrete mathematics) | Randomized algorithm | Vertex (graph theory) | Very large-scale neighborhood search | Greedy algorithm | Hash table