Module 5 – Networks and Decision Mathematics Chapter 24 – Directed Graphs.

Slides:



Advertisements
Similar presentations
Maximum Flow and Minimum Cut Problems In this handout: Duality theory Upper bounds for maximum flow value Minimum Cut Problem Relationship between Maximum.
Advertisements

Lecture 5: Network Flow Algorithms Max-Flow Min-Cut Single-Source Shortest-Path (SSSP) Job Sequencing.
Orthogonal Drawing Kees Visser. Overview  Introduction  Orthogonal representation  Flow network  Bend optimal drawing.
R. Johnsonbaugh Discrete Mathematics 5 th edition, 2001 Chapter 8 Network models.
Module 5 – Networks and Decision Mathematics Chapter 24 – Directed Graphs.
MAX FLOW APPLICATIONS CS302, Spring 2013 David Kauchak.
Module 5 – Networks and Decision Mathematics Chapter 24 – Directed Graphs.
Chapter 4: Network Layer
Chapter 10: Iterative Improvement The Maximum Flow Problem The Design and Analysis of Algorithms.
C++ Programming: Program Design Including Data Structures, Third Edition Chapter 21: Graphs.
1 Network Coding: Theory and Practice Apirath Limmanee Jacobs University.
CSC 2300 Data Structures & Algorithms April 17, 2007 Chapter 9. Graph Algorithms.
CSE 421 Algorithms Richard Anderson Lecture 22 Network Flow.
Chapter 11 Network Models. What You Need to Know For each of the three models: –What is the model? (what are given and what is to calculate) –What is.
A network is shown, with a flow f. v u 6,2 2,2 4,1 5,3 2,1 3,2 5,1 4,1 3,3 Is f a maximum flow? (a) Yes (b) No (c) I have absolutely no idea a b c d.
Network Flow & Linear Programming Jeff Edmonds York University Adapted from NetworkFlow.ppt.
A B C D The diagram below shows water flowing through a pipework system. The values on the edges are the capacities of water that they.
Here is an example that involves what is called ‘back flow’ 0 A C B D S T Arrows have already been drawn initially.
Chapter 15 Graph Theory © 2008 Pearson Addison-Wesley.
Engineering Mechanics: Statics
Example 15.4 Distributing Tomato Products at the RedBrand Company
More Graph Algorithms 15 April Applications of Graphs Graph theory is used in dealing with problems which have a fairly natural graph/network.
MAX FLOW CS302, Spring 2013 David Kauchak. Admin.
Maximum Flow Chapter 26.
Basic Electric Circuits. A series connection has a single path from the battery, through each circuit element in turn, then back to the battery. Resistors.
9/23/2015ACM-ICPC1 Maximum Flow Problem Source t fg e 42 Target (sink) flow capacity b s c a de 2/3/ actual flow 1/2/ 1/ 2/ 1.Actual flow  capacity.
Boundary layer concept
CS774. Markov Random Field : Theory and Application Lecture 13 Kyomin Jung KAIST Oct
Lecture 5: Network Flow Algorithms Single-Source Shortest-Path (SSSP) (Dijkstra's Algorithm) Max Flow - Min Cut (Ford-Fulkerson) Job Sequencing.
Module 5 – Networks and Decision Mathematics Chapter 23 – Undirected Graphs.
Network Flow How to solve maximal flow and minimal cut problems.
Module 5 – Networks and Decision Mathematics Chapter 23 – Undirected Graphs.
Network Flow. Network flow formulation A network G = (V, E). Capacity c(u, v)  0 for edge (u, v). Assume c(u, v) = 0 if (u, v)  E. Source s and sink.
10. Lecture WS 2006/07Bioinformatics III1 V10: Network Flows V10 follows closely chapter 12.1 in on „Flows and Cuts in Networks and Chapter 12.2 on “Solving.
1 12/2/2015 MATH 224 – Discrete Mathematics Formally a graph is just a collection of unordered or ordered pairs, where for example, if {a,b} G if a, b.
Circuit Theory Chapter 2 Basic Laws
The diagram below shows water flowing through a pipework system. The values on the edges are the capacities of water that they can carry.
1 CPSC 320: Intermediate Algorithm Design and Analysis July 14, 2014.
ENGM 631 Maximum Flow Solutions. Maximum Flow Models (Flow, Capacity) (0,3) (2,2) (5,7) (0,8) (3,6) (6,8) (3,3) (4,4) (4,10)
CSC 172 DATA STRUCTURES.
Engineering Economics (2+0)
Network Flow.
Maximum Flow c v 3/3 4/6 1/1 4/7 t s 3/3 w 1/9 3/5 1/1 3/5 u z 2/2
Minimum Spanning Tree Chapter 13.6.
EKT101 Electric Circuit Theory
V12: Network Flows V12 follows closely chapter 12.1 in
Load Weighting and Priority
Network Flow.
Maximum Flow Solutions
Network Flows – Labelling procedure
Network Flows – Back flow
Maximum Flow c v 3/3 4/6 1/1 4/7 t s 3/3 w 1/9 3/5 1/1 3/5 u z 2/2
MATS Quantitative Methods Dr Huw Owens
Introduction Basic formulations Applications
Lial/Hungerford/Holcomb/Mullins: Mathematics with Applications 11e Finite Mathematics with Applications 11e Copyright ©2015 Pearson Education, Inc. All.
Flow Networks Topics Flow Networks Residual networks
Network Flows – Multiple sources and sinks
R. Johnsonbaugh Discrete Mathematics 5th edition, 2001
Richard Anderson Lecture 21 Network Flow
Network Models 7-1.
Project Selection Bin Li 10/29/2008.
Chapter 6 Network Flow Models.
X y y = x2 - 3x Solutions of y = x2 - 3x y x –1 5 –2 –3 6 y = x2-3x.
Maximum Flow c v 3/3 4/6 1/1 4/7 t s 3/3 w 1/9 3/5 1/1 3/5 u z 2/2
Lecture 21 Network Flow, Part 1
Network Flows – Minimum capacities
Richard Anderson Lecture 22 Network Flow
Maximum Flow Problems in 2005.
CHAPTER 9 Compound Inequalities.
EMIS The Maximum Flow Problem: Flows and Cuts Updated 6 March 2008
Presentation transcript:

Module 5 – Networks and Decision Mathematics Chapter 24 – Directed Graphs

24.2 Network Flows 0 An application of weighted digraphs involves the concept of flows. 0 A flow is the quantity of material that can move along a given channel; for example, traffic flow along a highway or water flow through a pipe.

Flow Capacities 0 The network’s starting node(s) is called the source. This is where all flows commence. 0 The flow goes through the network to the end node(s) which is called the sink. 0 The flow capacity (capacity) of an edge is the amount of flow that an edge can allow through if it is not connected to any other edges.

0 The inflow of a node is the total of the flows of all edges leading into the node. 0 The outflow of a node is the minimum value obtained when one compares the inflow to the sum of the capacities of all the edges leaving the node.

Consider the following figures:

Example – Maximum Flow by inspection Flights connect the airports at Sydney, Melbourne, Brisbane, Adelaide and Canberra. The numbers in this graph represent the maximum number of passengers that can be carried in a fixed time. Note: There are no direct flights between Melbourne and Brisbane or between Sydney and Adelaide in the time period considered. a) By inspection: Find the maximum number of passengers that can be carried between Sydney and Adelaide (in the fixed time). b) Indicate how this can be achieved.

Solution: a) The maximum number between Sydney and Adelaide is = 1700 b) 700 passengers through Brisbane to Adelaide passengers to Melbourne and of these 600 go directly to Adelaide and an additional 400 go via Canberra. The maximum flow through most simple networks can be determined using inspection, but more complex networks require differing methods to be used….

Minimum cut – Maximum flow method 0 To determine the maximum flow, the network first needs to be divided or ‘cut’ into two parts. A cut in a network diagram is a line drawn through a number of edges which stops all flow from the source to the sink (it is defined as a collection of edges). 0 The value or capacity of the cut is the total flow of the edges that are cut (the sum of the capacities (weights) of the edges).

0 The minimum cut is the cut with the minimum value. 0 The maximum flow through a network is equal to the value of the minimum cut. 0 Maximum flow = Capacity of Minimum cut

0 In some networks it is possible to produce a cut in which an edge actually heads back inside the cut rather than being directed out of the cut. 0 If an edge does this, then its flow value is set to zero in the calculation of the cut value. 0 The inside of a cut is the side on which the source node lies. 0 Sometimes the inside of a cut is shaded.

Example 1: Determine the values of the cuts made on the network diagram below and find the maximum flow: Solution: Minimum cut = Maximum Flow, therefore the maximum flow is 18.

Example 2: For the network diagram below: Determine the value of all possible cuts to give the value of the minimum cut and hence the maximum flow through the network.

Solution:

Example 3: Determine the capacities of each of the cuts in the graph shown, and also the value of the minimum cut and hence the maximum flow.

Solution:

Example 4: Determine the maximum flow for the directed graph. Solution: Cut includes segment AT, AB, BC, CT. Ignore AB as it heads back. Cut = Maximum flow = 7