Chapter 2 Graph Theory Flashcards

1
Q

What is definition of a connected graph

A

Where each node can TAKE AN INDIRECT path to get to all other nodes

So there is a path that can connect one node to another somehow

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2
Q

What are having multiple edges or a loop?

A

Multiple edge = two edges or more going from one node to another

Loop = a loop around one node , takes back to same node (so like website on homepage click on something takes back to homepage)

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3
Q

What is a SIMPLE graph

A

A graph with NO LOOPS or MULTIPLE EDGES

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4
Q

Remember do simple graphs need to be connected?

A

NO, they can just be inviduak nodes on their own, so that can give extra variants

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5
Q

What is a COMPLETE GRAPH

A

a graph where ALL THE NODES are all connected DIRECTLY TO EACH OTHER

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6
Q

What is the formula , Kn for the minimum number of EDGES in a complete graph with n nodes and how to find out

A

= 1/2n (n-1)

Start with n= 2 = 1 node
N=3 = 3 node
N=4 = 6 node (draw them out)

This is triangle number = 1/2n (n+1)

HOWEVER sequence starts at 2 rather than one, so need to shift whole seauence back one = 1/2n (n-1)

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7
Q

Again what’s the nth term for the minimum number of edges Kn for a complete graph with n nodes

A

1/2n (n-1)

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8
Q

What is a Bipartite graph

What does it mean when it says find a complete matching
What’s the best way to do this

What is a COMPLETE bipartite graph

A

This is when you have two subsets of nodes, which CAN NOT BE CONNECTED TI EACH OTHER IN SAME SET, and these connected across Esch other

Could represent a group of workers and the jobs they can do, some can do multiple

2) this is when each worker has one task (do by inspection algorithm not needed)
- MATCH THE TASK THATS UNIQUE TO A WORKER FIRST, then complete the rest

3) this is where each node on left is connected to every node in right

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9
Q

Notation for complete bipartite graph?
K, r,s what this mean

A

K, r, s

Means r nodes on left all connected to s nodes on right

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10
Q

Remember to circle Esch subset on left snd right when drawing bipartite graphs!

A

Two circles thus, shows they are separate

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11
Q

What does ORDER / degree of a vertex mean

What about for a loop?

A

It means the NUMBER OF ROUTES COMING OUT OF THE NODE

For a loop, there are still two different ways you can take (left right, think like benzene cover it)

So two ways out of a loop!

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12
Q

Okay so defintions for simply connected vs complete

A

Simple = no loops or multiple edges
Connected = all nodes are indirectly connected to esch other

Complete = all nodes are directly connected to each other

So simply connected means connected graoh with no loops edges, but not all nodes have to be connected to Esch other

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13
Q

What’s definition if a tree then

A

A SIMPLY CONNECTED (not complete) graoh with the MINIMUM NUMBER OF EDGES

(The minimum number if edges removed the complete)

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14
Q

For n nodes of a tree, what’s the NUMBER OF EDGES IT WILL HAVE

A

Try and derive for 2 3 4

= n-1

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15
Q

What’s a cycle in a graoh

Do trees have these!

A

Where you can go around and around ,

Trees have NO CYCLES, as this makes it not minimum arcs for simple connected

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16
Q

What is network simple definition

A

Just a network with weigths in nodes, which could represent time, cost etc

17
Q

What’s a MINIMUM SPANNING TREE

How do we find these solutions ( algorithms ?)

A

this is a TREE (simple connected minimum arc + no cycle)

+ where its connected with the LEAST AMOUNT OF TOTAL WEIGHT to get everyhwere

To find these solutions we use Kruskal and prims algorithms

18
Q

How to do incidence matrix

How many ways is a loop connected to itself!

A

Incidence matrix =
- write down all nodes labelled as row and column
- then A with A just means how many ways is A connected to A

Fill this out and there WILL BE SYMMETRY along diagonal,

2) loop connected 2 TIMES DONT LACM

19
Q

What does isomorphic mean

A

Where two graphs are the same after manipulating how they look as long as edges not added or broken

20
Q

What will incidence matrix look like for two ISOMOROPHIC GRAPHS

A

Same exact incidence matrix !