MEIO/UPC-UB : NETWORK FLOWS
Network Flows
UPCOPENCOURSEWARE number 34414
Topic 10: Generalized Flows
F.-Javier Heredia
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• Definitions.
• Applications.
• Properties and optimality conditions.
• Generalized Network Simplex Algorithm.
• Source material:
– R.K. Ahuja, Th.L. Magnanti, J. Orlin “Network Flows”, chap. 15.
– J. Orlin “Network Optimization” http://ocw.mit.edu/courses/sloanschool-of-management/15-082j-network-optimization-fall-2010/
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 2
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Generalized Flows
• Suppose one unit of flow is sent in (i,j). We
relax the assumption that one unit arrives at
node j.
• If 1 unit is sent from i, µij units arrive at j:
i
µij = 7
j
µij is called the multiplier of (i,j)
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 3
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Overview of Generalized Flows
xij = amount of flow sent in (i,j)
µij = multiplier of (i,j)
b(i) = supply at node i
cij = unit cost of flow in (i,j)
uij = upper bound on flow in (i,j)
Minimize
subject to
∑
∑
c xij
( i , j )∈ A ij
j:( i , j )∈ A
xij − ∑ j:( j ,i )∈A µ ji x=
b( i ) ∀ i ∈ N
ji
0 ≤ xij ≤ uij
∀ (i , j ) ∈ A
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 4
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
LP Formulation of Generalized Flows
i
µij = 1.05
4/1/03
i
coal
j
(i,j) represents a 1 year
investment in an equity
4/1/04
µij = .4
j
electricity
(i,j) represents a
conversion of coal into
electricity
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 5
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Conversions of physical entities
i
job
µij = 3
j
machine
It takes 3 hours to make
one unit of job i on
machine j.
xij = units of product i made on machine j
µij = number of hours to make product i on machine j
d(i) = number of units of product i that need to be made.
d(j) = total time available on machine j.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 6
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Machine Scheduling
• Suppose that 1 incremental unit is sent from node 1,
that flow is conserved in 2, 3, and 4, arrives at node 5.
1
1
µ12 = 3
2
3
µ23 = .5
3
µ34 = 4
1.5
4
µ45 = 1
6
5
6
• For a directed path P from i to j, if one unit of flow is
sent from i, then the amount arriving at j is:
µ ( P ) = ∏ ( i , j )∈P µ ij
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 7
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Flows Along Directed Paths
• Suppose that 1 incremental unit is sent from node 1,
that flow is conserved in 2, 3, and 4, arrives at node 5.
µ12 = 4
1
1
1
2
4
µ23 = 2
-2
3
µ34 = 6
2
2
• Let P be a path from i to j.
P = Forward arcs of P
P = Backward arcs of P
µ45 = 4
4
-3
12
5
3
Flow reduction
• If one unit of flow is sent from i, then the amount
arriving at j is:
µ ( P ) = ∏ ( i , j )∈P µ ij / ∏ ( i , j )∈P µ ij
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 8
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Flows Along Non-directed Paths
• Suppose 1 unit is sent
2
4
1
4
1
-2
1
3
W
1.5
-1.5
3
around W starting and
ending at node 1.
2
2
6
2
5
4
-3
2
µ (W ) = ∏ ( i , j )∈W µ ij / ∏ ( i , j )∈W µ ij
µ(W) = 1.5
4
12
• If µ(W) ≠ 1, then the amount of flow arriving at node
1 is different than the amount leaving node 1.
• If µ (W) = 1, W is called a breakeven cycle.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 9
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Flows Along Cycles
2
4
1
4
• Suppose θ units are
2
s
send around W starting
and ending at node s.
3
• The net amount
W
1.5
6
2
3
5
4
2
4
12
arriving at node 1 is:
θ[µ(W)- 1 ].
• To create a “supply” of “a”
units at node s, send
θ =a/[µ(W)- 1 ]
units of flow.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 10
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Flows Along Cycles
Minimize
s. t.:
∑
∑
c xij
( i , j )∈ A ij
j:( i , j )∈ A
xij − ∑ j:( i , j )∈A µ ji x ji =
b( i ) i ∈ N
0 ≤ xij ≤ uij
∀ ( i , j ) ∈ A.
• The equality constraints have full row rank, which is n.
• A basis consists of n columns that are linearly
independent.
• Equivalently, a basis has n columns such that no subset
of these columns is dependent.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 11
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
On the LP for Generalized Flows
r
W
• An augmented tree T is a connected subset of k
nodes and k arcs for some k i.e. T it is a spanning
tree plus an extra arc.
• It usually has a root.
• T is called good if the cycle is non-breakeven.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 12
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Augmented Trees
1
4
12
5
7
W1
10
9
11
6
2
W2
3
8
• An augmented forest is a collection of node disjoint
augmented trees including all nodes.
• The augmented forest is good if each cycle is nonbreakeven.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 13
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Augmented Forests
1
4
12
5
7
W1
10
9
11
6
2
W2
3
8
• Def.: (F, L, U) is an augmented forest structure
− F are the arcs in the augmented forest.
− L are the arcs at their lower bound: xij = 0 for (i,j)∈ L
− U are the arcs at their upper bound: xij = uij for (i,j)∈ U
• Th. (good augmented forests and basis):
A set B of arcs defines a basis of the generalized network flow
problem if and only if B is a good augmented forest
proof: AMO, pag. 582-583
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 14
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Augmented Forest Structure
• Let π(i) be the node potential for node i.
π
c
• The reduced cost of arc (i,j) is: ij =cij − π ( i ) + µijπ ( j )
i
µij
j
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 15
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Node Potentials and Reduced Costs
Th. (Generalized Flow Sufficient Optimality Conditions)
A flow x* is an optimal solution of the generalized network
flow problem if it is feasible and for some vector π of node
potentials, the pair (x*, π) satisfies the following optimality
conditions:
(a) If 0 < xij* < uij , then cijπ =
0
=
(b) If xij* 0, then cijπ ≥ 0
=
(c) If xij* uij , then cijπ ≤ 0
proof: AMO pag.: 576-577
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 16
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Optimality Conditions (1/2)
Property
(Augmented Forest Structure Optimality Conditions)
A feasible augmented forest structure (F, L, U) with the
associated flow x* is an optimal augmented forest
structure if for some vector π of node potentials, the pair
(x*, π) satisfies the following optimality conditions.
(a) For all ( i , j ) ∈ F , cijπ =
0
(b) For all ( i , j ) ∈ L, cijπ ≥ 0
(c) For all ( i , j ) ∈ U , cijπ ≤ 0
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 17
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Optimality Conditions (2/2)
algorithm generalized network simplex
begin
determine the initial feasible augmented forest structure (F, L, U);
let x be the flow and π be the node potentials;
while some nonbasic arc violates its optimality condition do
begin
select an entering arc (k,l) violating its opt. condition;
add arc (k,l) to the forest and determine the leaving arc;
perform a forest update, and update x and π;
end;
end;
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 18
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Generalized Network Simplex
1. Find an initial feasible augmented forest structure (F, L, U).
(This is often an artificial solution, see AMO, pag 584).
2. Compute node potentials π reduced costs cπij .
3. Find feasible flow x.
4. Simplex leaving arc rule.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 19
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The generalized simplex algorithm
1
Compute node potentials
$3,2
1. Set the potential of the root
node to θ. We will
determine θ later.
2. Determine the node
potentials of all other
nodes so that tree arcs
have a reduced cost of 0.
cij
uij
7
$1,4
$0,2
$2, 4
10
8
4
$1,3
3. Determine θ so that the
extra arc also has a
reduced cost of 0.
$1,1
12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 20
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials for an Augmented
Forest Structure
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
θ 1
π
c17
=c17 − π (1) + µ17π (7) =0
3 - θ + 2 π(7) = 0
π(7) = (θ - 3)/2
$3,2
(θ-3)/2 7
$1,4
$0,2
$2, 4
10
8
4
$1,3
$1,1
12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 21
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials
θ 1
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
$3,2
π
c7,10
=c7,10 − π (7) + µ 7,10π (10) =0
0 - (θ - 3)/2 + 2 π(10) = 0
π(10) = (θ - 3)/4
(θ-3)/2 7
$1,4
$0,2
$2, 4
(θ-3)/4 10
8
4
$1,3
$1,1
12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 22
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials
θ 1
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
$3,2
π
c8,7
=c8,7 − π (8) + µ 8,7π (7) =0
1 - π(8) + 4(θ - 3)/2 = 0
π(8) = 2θ - 5
(θ-3)/2 7
$1,4
$0,2
$2, 4
(θ-3)/4 10
8 2θ-5
4
$1,3
$1,1
12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 23
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials
θ 1
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
$3,2
π
c7,4
=c7,4 − π (7) + µ 7,4π (4) =0
2 - (θ - 3)/2 + 4 π(4) = 0
π(4) = (θ - 7)/8
(θ-3)/2 7
$1,4
$0,2
$2, 4
(θ-3)/4 10
8 2θ-5
4
(θ-7)/8
$1,3
$1,1
12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 24
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials
θ 1
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
$3,2
π
c4,12
=c4,12 − π (4) + µ 4,12π (12) =0
1 - (θ - 7)/8 + π(12) = 0
π(12) = (θ - 15)/8
(θ-3)/2 7
$1,4
$0,2
$2, 4
(θ-3)/4 10
8 2θ-5
4
$1,3
(θ-7)/8
$1,1
(θ-15)/8 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 25
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Computing Node Potentials
θ 1
0
cijπ =
cij − π ( i ) + µ ijπ ( j ) =
$3,2
π
c4,10
=c4,10 − π (4) + µ 4,10π (10) =0
1 - (θ - 7)/8 + 3(θ - 3)/4 = 0
8 - θ + 7 + 6θ - 18 = 0
θ = 3/5
(θ-3)/2 7
$2, 4
(θ-3)/4 10
• This equation has a feasible solution
whenever the cycle is non-breakeven
(exercise 15.20).
$1,4
$0,2
8 2θ-5
4
$1,3
(θ-7)/8
$1,1
(θ-15)/8 12
• To compute the node potentials for a basis structure (F, L, U),
compute the node potentials for each connected component of F.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 26
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
NEXT: Look at the extra arc and compute θ
• Compute reduced
costs in the usual
way.
3/5 1
$3,7
$3,2
-6/5 7
$1,4
$0,2
cijπ =
cij − π ( i ) + µ ijπ ( j )
$2, 4
π
c10,1
=c10,1 − π (10) + µ10,1π (1)
-3/5 10
4
$1,3
-4/5
$1,1
π
c10,1 =+
3 3 / 5 + 7(3 / 5) =
39 / 5
8 -19/5
-9/5 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 27
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The reduced costs
• The node numbers are
1 1
supplies/demands.
The arc numbers are the
multipliers.
2
0 7
• To compute the arc
flows, set the flow in
the extra arc to θ
and then compute
the tree arcs in the
usual way as a
function of θ.
4
2
-11 10
4
3
4
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
-6
1
8 1
GF- 28
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The Arc Flows
• Set the flow in the extra
1 1
arc to θ.
2
• Compute the flow in
0 7
(4,12)
x4,12 = 1
4
2
-11 10
4
3,
3 θ
4
-6
1,
1 1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 29
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 12 is -1
• Compute the flow in (8,7)
1 1
2
x8,7 = 1
0 7
4,1
2
-11 10
4
3, θ
4
-6
1, 1
1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 30
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 8 is 1
• Compute the flow in (7,10)
1 1
2
2 x7,10 + 3 x4,10 = 11
(11 - 3θ)/2
0 7
4,1
2
x7,10 = (11 - 3θ)/2
-11 10
4
3, θ
4
-6
1,
1 1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 31
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 10 is -11
• Compute the flow in (1,7)
1 1
2 1
2,
x1,7 = 1
(11 - 3θ)/2
0 7
4,1
2
-11 10
4
3, θ
4
-6
1, 1
1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 32
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 1 is 1
• Compute the flow in (7,4)
1 1
2 1
2,
- 4x7,4 + x4,12 + x4,10 = -6
(11 - 3θ)/2
x7,4 = (6 + 1 + θ )/4
= (7 + θ )/4
0 7
4,1
2
-11 10
4
3, θ
4
8 1
-6
(7 + θ)/4
1
1, 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 33
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 4 is -6
1 1
2 1
2,
(11 - 3θ)/2
x7,10 + x7,4 - 4x8,7 – 2 x1,7 = 0
0 7
4,1
2
(11 - 3θ)/2 + (7 + θ)/4 – 4 – 2 = 0
-11 10
(22 - 6θ) + (7 + θ) – 24 = 0
4
3, θ
4
θ=1
8 1
-6
1 1 (7 + θ)/4
1,
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 34
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The supply of node 7 determines θ
θ=1
1 1
2 1
2,
4
• But how do we know
that there will be a
solution for θ? We next
present an alternative
approach that shows
that there is a solution
to the system of
equations.
0 7
4,1
2
-11 10
4
3, 1
4
-6
1 1 2
1,
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
8 1
GF- 35
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
The basic flows
1 1
• Choose a node of the
2
cycle. Say node 7.
0 7
• Satisfy supply/demand
constraints using tree
arcs but ignoring node 7.
2
-11 10
4
4
4
• Satisfy flow in node 7
by sending flow
around the cycle.
-6
1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 36
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
An alternative approach
1 1
x4,12 = 1
2,
2 1
x8,7 = 1
2 5.5
2,
x7,10 = 5.5
0 7
4 1
4,
4
-11 10
4
x1,7 = 1
-6
1
1, 1
8 1
-1 12
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 37
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
An alternative approach
1 1
x4,12 – 4 x7,4 = - 6
2 1
2,
1 – 4 x7,4 = - 6
0 7
2 5.5
2,
4 1
4,
x7,4 = 1.75
4, 1,75
4
• Now send flow around
-11 10
the cycle 7-4-10-7 to
cancel the excess flow
of -1.25 units at node 7.
3
4
-6
1
1, 1
8 1
-1 12
• Since the cycle is not breakeven, this is possible. Thus
there is a feasible solution to this set of equations.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 38
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
An alternative approach
• Send one unit out of 7 and
6
satisfy conservation of flow at
nodes 4 and 10:
µ(W) = 4*3/2 = 6
1
• Currently, there is a deficit of
1.25 units at node 7. So, we
need to send another 1.25 units
to node 7.
• Sending
7
e(7)=-1.25
2
10
(5/4) /[µ(W)- 1 ] = 1/4
3
12
units around the cycle balances node 7 (⇒θ=1).
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
4
4
4
GF- 39
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Sending flow around the cycle
• In computing flows, we assumed that all non-
basic flows are 0. If U ≠ ∅, then we first
compute the flows of arcs in U, and adjust the
supplies and demands (or excess and deficits)
accordingly, and then compute flows in arcs in F.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 40
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
What happens if U ≠ ∅ ?
• Suppose (i,j) enters the basis. Let y be the flow
obtained in F + (i,j) by setting yij = 1, and determining
flows in F so that there is conservation of flow
everywhere.
• Let x* be the basic feasible flow for (F, L, U).
• Choose λ maximal so that x* + λy satisfies upper and
lower bound constraints. Pivot out an arc
(r, s) that has hit its upper or lower bound for this
choice of λ.
• Time to determine leaving arc is O(n).
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 41
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Finding the leaving arc
• Suppose x* = (2, 1, 3, 1, 0, 0, 5)
• Suppose y = (1, 2, -1, 0, 1, 0, 0)
• Suppose u = (4, 4, 4, 3, 6, 2, 5)
0
0
0
0
0
0
0
≤
2
1
3
1
0
0
5
+
λ
1
2
-1
0
1
0
0
≤
4
4
4
3
6
2
5
λ≤2
λ ≤ 1.5
λ≤3
λ≤6
• So, we pick λ = 1.5. and variable 2 drops out of the basis.
• Exercise.
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 42
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
A quick illustration of choosing λ
• The bases for generalized flow problems are
good augmenting forests assuming that the
graph is
– connected and
– has a non-breakeven cycle
• Complexity:
– Theoretical: the number of iterations cannot be
polinomial bounded (neither pseudopolinomial)
– Practical: O(nm) (2 or 3 times slower than the
network simplex)
F.-Javier Heredia http://gnom.upc.edu/heredia
J. Orlin http://jorlin.scripts.mit.edu/
GF- 43
Generalized Flows
MEIO/UPC-UB : NETWORK FLOWS
Summary