Ahuja-Orlin: Difference between revisions
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# We start with some feasible flow, for example, the zero flow. | # We start with some feasible flow, for example, the zero flow. | ||
# For each <math>v\in V</math>, <math>d(v)</math> is initialized to be the smallest number of arcs from <math>v</math> to <math>t</math>. | # For each <math>v\in V</math>, <math>d(v)</math> is initialized to be the smallest number of arcs from <math>v</math> to <math>t</math>. | ||
# Stack <math>S</math> is initialized so as to contain <math>s</math> and no other node. | |||
# The current arc of each node <math>v\in V</math> is reset to be the very first out | |||
'''Implementation:''' | '''Implementation:''' | ||
# For all <math>a \in A</math>, set <math>f(a):=0. </math> | # For all <math>a \in A</math>, set <math>f(a):=0. </math> | ||
# Run a [[Breadth-first search|BFS]] on the [[Basic graph definitions|transpose]] of <math>G</math> with start node <math>t</math> and unit arc lengths | # Run a [[Breadth-first search|BFS]] on the [[Basic graph definitions|transpose]] of <math>G</math> with start node <math>t</math> and unit arc lengths; the resulting distances are the <math>d</math>-labels. | ||
# Create <math>S</math> and push <math>s</math> onto <math>S</math>. | |||
# Reset the current arcs. | |||
'''Proof:''' | '''Proof:''' |
Revision as of 10:27, 13 October 2014
General Information
Algorithmic problem: Max-Flow Problems
Type of algorithm: loop
Abstract View
Invariant: After [math]\displaystyle{ i \ge 0 }[/math] iterations:
- The flow [math]\displaystyle{ f }[/math] is a fleasible flow.
- If all upper bounds are integral, [math]\displaystyle{ f }[/math] is integral as well.
- There is a valid distance labeling [math]\displaystyle{ d }[/math] with respect to [math]\displaystyle{ f }[/math].
- Each node [math]\displaystyle{ v\in V\setminus\{t\} }[/math] has a current arc, which is either void or one of the outgoing arcs of [math]\displaystyle{ v }[/math].
- There is a current flow-augmenting path with respect to [math]\displaystyle{ f }[/math]. This path starts with [math]\displaystyle{ s }[/math] and ends at an arbitrary node of [math]\displaystyle{ G }[/math]. Each arc on this path is the current arc of its tail node.
Variant: Exactly one of the following actions will take place in the current iteration:
- An arc is appended to the current path.
- At least one arc is saturated.
- The distance label of some node is increased.
Break condition: [math]\displaystyle{ d(s)\geq n }[/math].
Induction basis
Abstract view:‘‘‘
- We start with some feasible flow, for example, the zero flow.
- For each [math]\displaystyle{ v\in V }[/math], [math]\displaystyle{ d(v) }[/math] is initialized to be the smallest number of arcs from [math]\displaystyle{ v }[/math] to [math]\displaystyle{ t }[/math].
- Stack [math]\displaystyle{ S }[/math] is initialized so as to contain [math]\displaystyle{ s }[/math] and no other node.
- The current arc of each node [math]\displaystyle{ v\in V }[/math] is reset to be the very first out
Implementation:
- For all [math]\displaystyle{ a \in A }[/math], set [math]\displaystyle{ f(a):=0. }[/math]
- Run a BFS on the transpose of [math]\displaystyle{ G }[/math] with start node [math]\displaystyle{ t }[/math] and unit arc lengths; the resulting distances are the [math]\displaystyle{ d }[/math]-labels.
- Create [math]\displaystyle{ S }[/math] and push [math]\displaystyle{ s }[/math] onto [math]\displaystyle{ S }[/math].
- Reset the current arcs.
Proof: Obvious.
Induction step
Complexity
Remark
This algorithm may be seen as a "lazy" variant on Edmonds-Karp. In fact, the most expensive step there is the computation of a flow-augmenting [math]\displaystyle{ (s,t) }[/math]-path. This task amounts to computing the true distance from every node to [math]\displaystyle{ t }[/math]. A valid distance labeling may be seen as "lazily evaluated" true distances.