the network simplex method

21
Trees and BFSs Page 1 The Network Simplex Method Spanning Trees and Basic Feasible Solutions

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The Network Simplex Method. Spanning Trees and Basic Feasible Solutions. BFS  Spanning Tree. Theorem 11.10: Every spanning tree of G defines a basis of the MCNFP LP and every basis of the MCNFP LP defines a spanning tree of G . - PowerPoint PPT Presentation

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Page 1: The Network Simplex Method

Trees and BFSs Page 1

The Network Simplex Method

Spanning Trees and Basic Feasible Solutions

Page 2: The Network Simplex Method

Trees and BFSs Page 2

BFS Spanning Tree

• Theorem 11.10: Every spanning tree of G defines a basis of the MCNFP LP and every basis of the MCNFP LP defines a spanning tree of G.

• There is a one-to-one correspondence between spanning trees and basic solutions.

Page 3: The Network Simplex Method

Trees and BFSs Page 3

MCNFP Example

51

4

2

3

(0,4,5) (0,10,2)

(0,5,5)(0,4,7)

(0,10,4) (0,5,8)

(0,5,10)10

4

-4

-3

-7

(, u, c)

Page 4: The Network Simplex Method

Trees and BFSs Page 4

Flow Balance Constraints

7

4

3

4

10

453525

341445

133534

1225

141312

xxxxxxxxxxxxxx

We can drop one of the constraints.

Page 5: The Network Simplex Method

Trees and BFSs Page 5

Basic Feasible Solutions (BFS)

• We can drop the flow balance constraint for one of the nodes.

• The flow balance constraints form a system of 4 equations with 7 variables.

• Thus, A BFS will have 4 basic variables and 7- 4 = 3 non-basic variables.

Page 6: The Network Simplex Method

Trees and BFSs Page 6

An initial BFS (Solution 1)

• Basic arcs (variables)B = {(1,3), (2,5), (3,5), (4,5)}

• Non-basic arcs at their lower boundsL = {(1,2), (1,4)}

• Non-basic arcs at their upper bounds.U = {(3,4)}

Page 7: The Network Simplex Method

Trees and BFSs Page 7

Flow Balance Constraints

45

35

4

10

45

1335

25

13

xxx

xx

Drop flow balance for node 5 andsubstitute and u values for non-basic arcs.

Page 8: The Network Simplex Method

Trees and BFSs Page 8

Vector-Matrix Form of the Flow-Balance Constraints

1

8

4

10

1000

0101

0010

0001

45

35

25

13

xxxx

Page 9: The Network Simplex Method

Trees and BFSs Page 9

Solving Flow Balance Equations

1

2

4

10

1

8

4

10

1000

0101

0010

00011

45

35

25

13

xxxx

Page 10: The Network Simplex Method

Trees and BFSs Page 10

The Basis Matrix

• Let B be a set of n-1 arcs.• Let AB be the n-1 by n-1 submatrix of the

node-arc incidence matrix formed by taking the columns corresponding to the arcs in B and removing one row.

• The Basis Matrix AB must have an inverse in order for it to correspond to a BFS.

Page 11: The Network Simplex Method

Trees and BFSs Page 11

Results from Linear Algebra

• The determinant of a lower triangular matrix is the product of its diagonal elements.

• A set of n-1 column vectors with n-1 elements each has an inverse if and only if the matrix comprised of these columns has a non-zero determinant.

Page 12: The Network Simplex Method

Trees and BFSs Page 12

Vector-Matrix Form of the Flow-Balance Constraints

1

8

4

10

1000

0101

0010

0001

45

35

25

13

xxxx

This basis matrix is lower triangular.All diagonal elements are 1.Thus, this matrix has an inverse.

Page 13: The Network Simplex Method

Trees and BFSs Page 13

Converting Spanning Trees to Basis Matrices

• Perform a DFS of the underlying, undirected tree.• Traverse the nodes with a reverse thread: visit

node i before pred(i)• Order the nodes (rows) according to the order they

were visited in the reverse thread.• Order the arcs (columns): visit the nodes in order,

and for each node i visited, select the unique arc incident to i on the path in the DFS tree.

Page 14: The Network Simplex Method

Trees and BFSs Page 14

BFS 2

51

4

2

3

Page 15: The Network Simplex Method

Trees and BFSs Page 15

Converting the Spanning Tree to a Basis Matrix

5

1

4

23

Reverse Thread: visit i before pred(i).

4

Arc Order:

(4,5) (2,5) (1,2) (1,3)

5

2

31

1-10

00

0-11

00

00

-1

01

000

-11

Page 16: The Network Simplex Method

Trees and BFSs Page 16

LowerTriangular Basis Matrix

(4,5) (2,5) (1,2) (1,3)

45

2

3

1-10

0

0-11

0

00

-1

0

000

-1

All diagonal elements are +1 or –1.

Page 17: The Network Simplex Method

Trees and BFSs Page 17

BFS 3

51

4

2

3

Page 18: The Network Simplex Method

Trees and BFSs Page 18

Converting the Tree to a Basis Matrix

5

1

4

23

Reverse Thread4

Arc Order:

(3,4) (1,3) (2,5) (1,2)

3

5

21

-1 10

00

0-10

01

00

-1

10

000

-11

Page 19: The Network Simplex Method

Trees and BFSs Page 19

General Case

• Suppose arc (i, j) is in the spanning tree and assume j = pred(i) in the DFS.

• Consider the column corresponding to arc (i, j):– This column will have a +1 or a –1 in the row (r)

corresponding to node i.– The only other non-zero entry in the column will be in

the row for node j which will be below row r.– Thus, the matrix is always lower triangular with +1 or –

1 in all the diagonal elements.

Page 20: The Network Simplex Method

Trees and BFSs Page 20

Tree => Basis Matrix

• Theorem 11.9: The rows and columns of the node-arc incidence matrix of any spanning tree can be rearranged to be lower triangular.

• Every spanning tree of G corresponds to a basis of the minimum-cost network flow problem.

Page 21: The Network Simplex Method

Trees and BFSs Page 21

Cycle => Not a Basis Matrix

i

k

j

000?

110?

011?

101?

000?

),(),(),(?)(?,

k

j

i

ikkjji

(k, i) column is a linear combinationof (i, j) and (j, k) columns.