Maximal flow problem: ford-fulkerson algorithm

In summary: I do not see how this argument is going to work. If adding an arc se with a capacity of 1 increases the flow then so will adding one of capacity 100.
  • #1
binbagsss
1,259
11

Homework Statement



Question attached:
ford-fulk part c.png


Homework Equations



see below

The Attempt at a Solution



- The theorem without prove i require needed is that the cut of maximum flow is given by the cut of minimal capacity.
My proof would be along the lines of:
- using this theorem, obviously 100 is a large capacity compared to the other values so i would perhaps justify this more explictly by :
- computing how many distinct cuts there are, and summing the capacity of all of all to show that all cuts containing arc SE have a greater capacity.
- as for a short-cut without needing to compute all distinct cuts, I'm not really sure how to prove to it, it appears that it should be pretty trivial given the theorem and the large capacity, but I'm unsure what to write down properly.

Any help much appreciated.
 
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  • #2
binbagsss said:
My proof would be along the lines of:
- using this theorem, obviously 100 is a large capacity compared to the other values so i would perhaps justify this more explictly by :
- computing how many distinct cuts there are, and summing the capacity of all of all to show that all cuts containing arc SE have a greater capacity.
I do not see how this argument is going to work. If adding an arc se with a capacity of 1 increases the flow then so will adding one of capacity 100.
I would look at the max flow from s to e in the network as it is.
 
  • #3
binbagsss said:

Homework Statement



Question attached:View attachment 203334

Homework Equations



see below

The Attempt at a Solution



- The theorem without prove i require needed is that the cut of maximum flow is given by the cut of minimal capacity.
My proof would be along the lines of:
- using this theorem, obviously 100 is a large capacity compared to the other values so i would perhaps justify this more explictly by :
- computing how many distinct cuts there are, and summing the capacity of all of all to show that all cuts containing arc SE have a greater capacity.
- as for a short-cut without needing to compute all distinct cuts, I'm not really sure how to prove to it, it appears that it should be pretty trivial given the theorem and the large capacity, but I'm unsure what to write down properly.

Any help much appreciated.

Have you solved the max-flow problem from part (a)? That would tell you the min-cut capacity, and then all you need to do is look for a cut having that capacity. There is no need to enumerate all the cuts (although that should also work, of course). You should think more about part (c): remember the max-flow, min-cut theorem.
 
Last edited:
  • #4
haruspex said:
I do not see how this argument is going to work. If adding an arc se with a capacity of 1 increases the flow then so will adding one of capacity 100. .
because the route of maximum flow is given by the cut of minimum capacity?
 
  • #5
binbagsss said:
because the route of maximum flow is given by the cut of minimum capacity?

In part, yes. Does adding the new arc change the min cut?
 
Last edited:
  • #6
Ray Vickson said:
I part, yes. Does adding the new arc change the min cut?

is that in part sorry?

yes I agree, to see whether it changes the minimal cut or not I need to do part a
 
  • #7
binbagsss said:
is that in part sorry?

yes I agree, to see whether it changes the minimal cut or not I need to do part a

Typo fixed above.
 

Related to Maximal flow problem: ford-fulkerson algorithm

What is the maximal flow problem?

The maximal flow problem is a mathematical optimization problem that involves finding the maximum flow possible in a directed graph. It is commonly used in network flow analysis to determine the maximum amount of flow that can be transported through a network from a source to a sink.

What is the Ford-Fulkerson algorithm?

The Ford-Fulkerson algorithm is a popular method for solving the maximal flow problem. It is an iterative algorithm that uses a depth-first search approach to find the augmenting paths and increase the flow in each iteration until the maximum flow is reached.

How does the Ford-Fulkerson algorithm work?

The Ford-Fulkerson algorithm works by finding an augmenting path, which is a path from the source to the sink that has available capacity for more flow. It then increases the flow along this path until all paths are saturated. This process is repeated until no more augmenting paths can be found, at which point the maximum flow is reached.

What are the assumptions of the Ford-Fulkerson algorithm?

The Ford-Fulkerson algorithm assumes that the network has a single source and sink, and that each edge has a capacity limit. It also assumes that the capacities are non-negative and that the flow can only be increased, not decreased, along an augmenting path.

What are some applications of the maximal flow problem and the Ford-Fulkerson algorithm?

The maximal flow problem and the Ford-Fulkerson algorithm have many applications in various fields, such as transportation and logistics, computer networks, and water and power distribution systems. They can be used to optimize the flow of resources and determine the maximum capacity of a system.

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