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Network Optimization Models: Maximum Flow ProblemsPowerPoint Presentation

Network Optimization Models: Maximum Flow Problems

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Network Optimization Models:Maximum Flow Problems

- In this handout:
- The problem statement
- Augmenting path algorithm for solving the problem

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Maximum Flow Problem- Given: Directed graph G=(V, E),
Supply (source) node O,demand (sink) node T

Capacity function u: E R .

- Goal: Given the arc capacities,
send as much flow as possible

from supply node O to demand node T

through the network.

- Example:

Towards the Augmenting Path Algorithm

- Idea: Find a path from the sourceto the sink,
and use it to send as much flow as possible.

- In our example,
5 units of flow can be sent through the path O B D T ;

Then use the path O C T to send 4 units of flow.

The total flow is 5 + 4 = 9 at this point.

- Can we send more?

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Towards the Augmenting Path Algorithm

- If we redirect 1 unit of flow
from path O B D T to path O B C T,

then the freed capacity of arc D T could be used

to send 1 more unit of flow through path O A D T,

making the total flow equal to 9+1=10 .

- To realize the idea of redirecting the flow in a systematic way,
we need the concept of residual capacities.

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Residual capacities

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- Suppose we have an arc with capacity 6 and current flow 5:
- Then there is a residual capacity of 6-5=1
for any additional flow through B D .

- On the other hand,
at most 5 units of flow can be sent back from D to B, i.e.,

5 units of previously assigned flow can be canceled.

In that sense, 5 can be considered as

the residual capacity of the reverse arc D B .

- To record the residual capacities in the network,
we will replace the original directed arcs with undirected arcs:

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The number at B is the residual capacity of BD;

the number at Dis the residual capacity of DB.

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Residual Network- The network given by the undirected arcs and residual capacities
is called residual network.

- In our example,
the residual network before sending any flow:

Note that the sum of the residual capacities on both ends of an arc

is equal to the original capacity of the arc.

- How to increase the flow in the network
based on the values of residual capacities?

Augmenting paths

- An augmenting path is a directed path
from the source to the sink in the residual network

such that

every arc on this path has positive residual capacity.

- The minimum of these residual capacities
is called the residual capacity of the augmenting path.

This is the amount

that can be feasibly added to the entire path.

- The flow in the network can be increased
by finding an augmenting path

and sending flow through it.

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Updating the residual network by sending flow through augmenting pathsContinuing with the example,

- Iteration 1: O B D T is an augmenting path
with residual capacity 5 = min{5, 6, 5}.

- After sending 5 units of flow
through the path O B D T,

the new residual network is:

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Updating the residual network by sending flow through augmenting paths- Iteration 2:
O C T is an augmenting path

with residual capacity 4 = min{4, 5}.

- After sending 4 units of flow
through the path O C T,

the new residual network is:

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Updating the residual network by sending flow through augmenting paths- Iteration 3:
O A D B C T is an augmenting path

with residual capacity 1 = min{4, 4, 5, 4, 1}.

- After sending 1 units of flow
through the path O A D B C T ,

the new residual network is:

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Terminating the Algorithm:Returning an Optimal Flow

- There are no augmenting paths in the last residual network.
So the flow from the source to the sink cannot be increased further, and the current flow is optimal.

- Thus, the current residual network is optimal.
The optimal flow on each directed arc of the original network

is the residual capacity of its reverse arc:

flow(OA)=1, flow(OB)=5, flow(OC)=4,

flow(AD)=1, flow(BD)=4, flow(BC)=1,

flow(DT)=5, flow(CT)=5.

The amount of maximum flow through the network is

5 + 4 + 1 = 10

(the sum of path flows of all iterations).

The Summary of the Augmenting Path Algorithm

- Initialization: Set up the initial residual network.
- Repeat
- Find an augmenting path.
- Identify the residual capacity c* of the path; increase the flow in this path by c*.
- Update the residual network: decrease by c* the residual capacity of each arc on the augmenting path; increase by c* the residual capacity of each arc in the opposite direction on the augmenting path.
Until no augmenting path is left

- Return the flow corresponding to
the current optimal residual network

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