Shana Norman Dec 11, 2003 Final Project

Slides:



Advertisements
Similar presentations
Lecture 21 Paths and Circuits CSCI – 1900 Mathematics for Computer Science Fall 2014 Bill Pine.
Advertisements

MINIMAL CONNECTOR PROBLEMS Problem: A cable TV company is installing a system of cables to connect all the towns in a region. The numbers in the network.
Prim’s Algorithm from a matrix A cable TV company is installing a system of cables to connect all the towns in the region. The numbers in the network are.
Graph Algorithms: Minimum Spanning Tree We are given a weighted, undirected graph G = (V, E), with weight function w:
Is the following graph Hamiltonian- connected from vertex v? a). Yes b). No c). I have absolutely no idea v.
3/29/05Tucker, Sec Applied Combinatorics, 4th Ed. Alan Tucker Section 4.2 Minimal Spanning Trees Prepared by Amanda Dargie and Michele Fretta.
Two Discrete Optimization Problems Problem #2: The Minimum Cost Spanning Tree Problem.
Algorithms on graphs In Decision Mathematics, a graph consists of points (called vertices or nodes) which are connected by lines (edges or arcs). Eg in.
MTH118 Sanchita Mal-Sarkar. Routing Problems The fundamental questions: Is there any proper route for the particular problem? If there are many possible.
The Travelling Salesman Algorithm A Salesman has to visit lots of different stores and return to the starting base On a graph this means visiting every.
Chapter 2: Business Efficiency Lesson Plan Business Efficiency  Visiting Vertices-Graph Theory Problem Hamiltonian Circuits  Vacation Planning Problem.
Discrete Mathematics Lecture 9 Alexander Bukharovich New York University.
Chapter 15 Graph Theory © 2008 Pearson Addison-Wesley. All rights reserved.
GRAPH Learning Outcomes Students should be able to:
Programming for Geographical Information Analysis: Advanced Skills Online mini-lecture: Introduction to Networks Dr Andy Evans.
Minimum spanning trees Aims: To know the terms: tree, spanning tree, minimum spanning tree. To understand that a minimum spanning tree connects a network.
CS 3343: Analysis of Algorithms Lecture 21: Introduction to Graphs.
1 Excursions in Modern Mathematics Sixth Edition Peter Tannenbaum.
Spring 2015 Mathematics in Management Science Euler’s Theorems Euler Circuits & Paths ECT & EPT Burning Bridges Fleury’s Algorithm.
Graph Theory Topics to be covered:
Problem Solving with Networks 18/08/2012 Jamie Sneddon
(CSC 102) Lecture 32 Discrete Structures. Trees Previous Lecture  Matrices and Graphs  Matrices and Directed Graphs  Matrices and undirected Graphs.
© Nuffield Foundation 2011 Nuffield Free-Standing Mathematics Activity Chinese postman problems What route can I take to avoid going along the same street.
Spring 2015 Mathematics in Management Science Network Problems Networks & Trees Minimum Networks Spanning Trees Minimum Spanning Trees.
Chinese postman problem
Structures 7 Decision Maths: Graph Theory, Networks and Algorithms.
6.1 Hamilton Circuits and Paths: Hamilton Circuits and Paths: Hamilton Path: Travels to each vertex once and only once… Hamilton Path: Travels to each.
Module 5 – Networks and Decision Mathematics Chapter 23 – Undirected Graphs.
CS 200 Algorithms and Data Structures
Fundamental Data Structures and Algorithms (Spring ’05) Recitation Notes: Graphs Slides prepared by Uri Dekel, Based on recitation.
Chapter 2: Business Efficiency Lesson Plan Business Efficiency  Visiting Vertices-Graph Theory Problem Hamiltonian Circuits  Vacation Planning Problem.
Michael Walker. From Maps to Graphs  Make Intersections Vertices  Make Roads Edges  Result is Weighted Directed Graph  Weights: Speed Limit Length.
Chapter 14 Section 4 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Graphs A ‘Graph’ is a diagram that shows how things are connected together. It makes no attempt to draw actual paths or routes and scale is generally inconsequential.
Spring 2015 Mathematics in Management Science Network Problems Networks & Trees Minimum Networks Spanning Trees Minimum Spanning Trees.
Mathematics in Management Science
CIRCUITS, PATHS, AND SCHEDULES Euler and Königsberg.
MAT 2720 Discrete Mathematics Section 8.2 Paths and Cycles
Lecture 19 Minimal Spanning Trees CSCI – 1900 Mathematics for Computer Science Fall 2014 Bill Pine.
I can describe the differences between Hamilton and Euler circuits and find efficient Hamilton circuits in graphs. Hamilton Circuits I can compare and.
Chapter 14 Section 3 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Unit 2 Hamiltonian Circuits. Hamiltonian Circuit: A tour that starts at a vertex of a graph and visits each vertex once and only once, returning to where.
Graphs 1 Neil Ghani University of Strathclyde. Where are we …. We studied lists: * Searching and sorting a list Then we studied trees: * Efficient search.
Lower bound algorithm. 1 Start from A. Delete vertex A and all edges meeting at A. A B C D 4 5 E Find the length of the minimum spanning.
Excursions in Modern Mathematics Sixth Edition
Excursions in Modern Mathematics Sixth Edition
Graphs Lecture 19 CS2110 – Spring 2013.
Minimum Spanning Tree Chapter 13.6.
Section 2: Multiple choice
Chapter 2: Business Efficiency Lesson Plan
Short paths and spanning trees
Discrete Maths 9. Graphs Objective
Chapter 2: Business Efficiency Lesson Plan
Spanning Trees Discrete Mathematics.
Graph Algorithm.
Graph Theory.
CSE373: Data Structures & Algorithms Lecture 12: Minimum Spanning Trees Catie Baker Spring 2015.
CSE373: Data Structures & Algorithms Lecture 20: Minimum Spanning Trees Linda Shapiro Spring 2016.
Shortest Path.
Chapter 2: Business Efficiency Business Efficiency
Minimum spanning trees
Minimum spanning trees
Minimum spanning trees
Networks Kruskal’s Algorithm
Discrete Mathematics Lecture 13_14: Graph Theory and Tree
Minimum Spanning tree Select any vertex
Warm Up – Tuesday Find the critical times for each vertex.
Warm Up – 3/14 - Friday 100 seats are to be apportioned.
Prim’s algorithm for minimum spanning trees
7 The Mathematics of Networks
Presentation transcript:

Shana Norman Dec 11, 2003 Final Project Vertex-Edge Graphs Shana Norman Dec 11, 2003 Final Project

Introduction Geometry curriculum is constantly changing NC trying to evolve to NCTM standards Vertex-edge graphs are in the NCTM curriculum for high school geometry

Why study vertex-edge graphs? Think visually Think spatially Has real world applications

Road Map Vertex-edge graphs Using vertex-edge graphs Famous algorithms NCTM standards

What is a vertex-edge graph? 5 vertices 5 edges

Another vertex-edge graph Edges contain distance Vertices represent a location

Useful vertex-edge graphs Optimal Routes Traveling salesman, Paved roads Efficient Scheduling Classes, Jobs, Tasks Planning Lights, Bridges

Paved Road Problem 7 towns, pave roads so people can get from every town to every other town on a paved road. (minimize the distance)

More Paved Road Minimal spanning tree Two types: Minimizes the sum of the distances Two types: Kruskal’s algorithm Prim’s algorithm

Kruskal’s Algorithm Choose shortest distance AB, BD, EF, BF, FG, CD Total length = 88

Prim’s Algorithm Choose connected shortest path Retrace steps if needed AB, BD, DC, BF, EF, FG Total length = 88

More vertex-edge graphs Critical Path 7 Tasks Hours at each vertex

Critical Path Assembly line Baking Chemistry Lab

Assembly Line Critical Path = 1, 4, 5 or 6, 7

Hamiltonian Path Traveling Salesman

Euler’s path Seven Bridges

Quick Review Vertex-edge graph Example of vertex-edge graphs Paved road problem Krusal’s algorithm Prim’s algorithm Critical path Hamiltonian path Euler’s path

National Council of Teachers of Mathematics Want students to think and reason spatially Vertex-edge problems allow students to think beyond what information is given

Answers to problems Fully specify algorithm Compare algorithms Steps taken to achieve goal Compare algorithms Consider which algorithms are more efficient.

Conclusion Vertex-edge graphs should be incorporated into the high school geometry curriculum Think visually Think spatially Has real world applications

Resources Discrete Mathematics with Applications By Susanna S. Epp Published 1990 Summary: I used vertex-edge problems, Kruskal’s algorithm, Prim’s algorithm, Euler’s path, and the Hamiltonian path from this book http://standards.nctm.org/document/chapter3/geom.htm by the National Council of Teachers of Mathematics Summary: I used the geometry standards and some of the problems listed on the website. http://dmoz.org/Science/Math/Education/Personal_and_Class_Pages Summary: I used ideas for classroom activities from this website