chapter 3 restriction
DESCRIPTION
Chapter 3 Restriction. (2) Greedy k-restricted Steiner tree Ding-Zhu Du. A general result on greedy algorithm With non-integer potential function. Consider a monotone increasing , submodular function. Consider the following problem:. where. is a nonnegative cost function. - PowerPoint PPT PresentationTRANSCRIPT
![Page 2: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/2.jpg)
A general result on greedy algorithmWith non-integer potential function
Consider a monotone increasing, submodular function
Rf E 2:}0)(:|{)( AfExEAf x
Consider the following problem:
)( subject to
)()( min
fA
xcAcAx
where REc : is a nonnegative cost function
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.output
};{ and
)(
)( maximize to choose
do )( while
;
A
xAA
xc
AfEx
fA
A
x
Greedy Algorithm G
![Page 4: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/4.jpg)
Theorem
Suppose in Greedy Algorithm G, selected x always satisfies
1)(/)( xcAfx
Then its p.r. opt
ff )(*ln1
where )(for )(* fAAff
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Proof. Let },...,,{ 21 gg xxxA
}.,...,,{ 21 ii xxxA
},...,,{* 21 kyyyA
be obtained by
Greedy Algorithm G.
Denote
Let be an optimal solution.
Denote ).(* iAi Afa
)(
)(*)(
)(*)(
)()(
1
11
*1*1
ix
ii
ii
iAiAii
Af
AfAAf
AfAAf
AfAfaa
i
![Page 6: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/6.jpg)
)(
)(
)(
)(max
)(
)(11
11
1 11
i
ix
j
iy
kjk
j j
k
j iyi
xc
Af
yc
Af
yc
Af
opt
aijj
)(11
i
iii
xc
aa
opt
a
optxcxc
optxci
iii
i
i
ea
eaopt
xcaa
/))()((0
/)(11
1
))(
1(
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0)()*()(* gggAg AfAAfAfa
Note that
g
ii
g
iix
g
optxcAf
fAfAffa
i11
1
00
.)()(
)()()(*
There exists i such thatii aopta 1
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.1)(
)(
''
''
'
'
such that ''')(
. ''')(
thatso '' ,'
1
1
1
1
1
1
i
ix
i
ixii
ii
xc
Af
c
a
c
a
ccxc
aaAfaa
aoptaoptaa
i
i
Let
Let
.)(
)(
' 1
1
opt
a
xc
Af
c
opta i
i
ixi i
Note that
.ln)()('
)'
1(
01
/))()('(0
1
opt
aoptxcxcc
eaopt
caopt
i
optxcxcci
i
So
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.
)()(''
)()(''
1211
11
2
2
opt
aaaaaopt
AfAfa
xcxcc
ggiii
gxix
gi
gi
Note
Hence,
).*
ln1()(opt
foptAc g
![Page 10: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/10.jpg)
),:()()( HPmstPmstHf
is the length of MST on P after terminals in eachconnected component of H are contracted into a point.
Consider
where ):( HPmst
Consider
the set of all full component of size at most k.
kQ
Theorem. is a monotone increasing submodular
function on f
.kQ
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).()(
by from induced is 2:
. of subsets of collection a is
.submodular is 2 : Suppose
SgAf
gRf
EC
Rg
As
C
E
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)()( BfAfBA xx
)()( SgSgBA BsxAsx
.submodular and increasing monotone is g
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For k >2, consider each
as a set of edges in a spanning treeon terminals.
kQT
)(Te
)).(()( TefAfAT
For ,kQA
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)()()(},{ AfAfAf yxyx
)(}){( AfxAf yy
submodular increasing monotone is f
iff
i.e.,
}){:():()(}){( xAPmstAPmstAfxAf
}),{:():(
)(}),{(
yxAPmstAPmst
AfyxAf
}){:():()(}){( yAPmstAPmstAfyAf
)()( BfAfBA xx iff
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}){:():(
)(}){(
xAPmstAPmst
AfxAf
x
x
For k=2,
is the length of a longest edge in the path connectingtwo endpoints of , in MST(A).x
![Page 16: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/16.jpg)
}),{:():(
)(}),{(
yxAPmstAPmst
AfyxAf
. and
cycles twocontains ):(
21 CC
yxAPMST
).(\in edgelongest thebe ''Let
. cycle a contains ')(
).(in edgelongest thebe 'Let
3
321
21
yxCe
CeyxCC
yxCCe
).''(length)'(length ee
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y
x
x
x
x
}),{:():(
)(}),{(
yxAPmstAPmst
AfyxAf
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y
x x
x
}),{:():(
)(}),{(
yxAPmstAPmst
AfyxAf
![Page 19: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/19.jpg)
Theorem Greedy Algorithm G is
)()ln1()()ln1(
)()(
)()
)(
)()()(
ln1()())(
)(ln1(
21
2
PsmtPsmt
PsmtPsmt
Psmt
Psmt
PsmtPsmtPmst
PsmtPsmt
Pmst
kk
k
kk
k
))(
)(ln1(
Psmt
Pmst
k
-approximation for .)(Psmtk
Greedy Algorithm G produces approximation solutionfor SMT with length at most
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Loss(T)
TTv
QTTeTvmstTloss k
ofset vertex the)(
for ))(:)(()(
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Loss(T)
)(2
1)( TlengthTloss
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Operation BA
B
A
BA
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)).(()()(
, and eeSteiner tr aFor
KTmstTcAg
QAT
AKT
k
Function )(AgT
T 2K
1K
![Page 24: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/24.jpg)
Lemma
)'()'(
.,.
)'()')(()(
.,.
)'()'()(
.,.
)'()()'(
)( KgKg
ei
KgKKTmstmstKTmst
ei
KgKKTmstKTmst
ei
KgKgKKg
TKTMST
T
T
TTT
![Page 25: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/25.jpg)
Function )'( and )'( )( KgKg KTMSTT
T
'KK
![Page 26: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/26.jpg)
Lemma
function. dpolymatroi a is )(AgT
Proof.
)()(
)'()(
})',({
)')(())((
)(})',{()(
'
))(())((
))((
',
AgAg
KgKg
KKg
KKYTmstYTmst
AgKKAgAg
TKTK
YTMSTYTMST
YTMST
AYAY
TTTKK
AYAY
AY
![Page 27: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/27.jpg)
.output
);( and
)(
)( maximize to choose
do ]0)([ while
);(
A
KTMSTT
Kc
KgQK
KgQK
PMSTT
Tk
Tk
Greedy Algorithm
![Page 28: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/28.jpg)
)()()(
then,0)(,any for If
ee.Steiner tr restricted- a be Let
TlossPsmtTc
KgQK
kT
k
Tk
Lemma
Proof
)()(
)()(
.0)()()(
. )( Suppose
1
11
1
TlossPsmt
KKTmstTc
KgKgKKg
KKPSMT
k
p
pTTpT
pk
![Page 29: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/29.jpg)
.output
);( and
)(
)( maximize to choose
do ]0)([ while
);(
A
KTMSTT
Kloss
KgQK
KgQK
PMSTT
Tk
Tk
Greedy Algorithm
![Page 30: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/30.jpg)
.output
));((
)( and
size)smaller with one choose tied,(if
)(
)( maximize to choose
do ]0)([ while
)(
);(
A
KTMSTH
KTMSTT
Kloss
KgQK
KgQK
PMSTH
PMSTT
Hk
Hk
Robin-Zelikvosky
![Page 31: Chapter 3 Restriction](https://reader036.vdocuments.us/reader036/viewer/2022062422/5681305d550346895d9627e8/html5/thumbnails/31.jpg)
What is ? )(K
)(Kpoint. a into contracted is
)(in edgeEach KLoss
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Lemma
)()()()(
iteration.
th theof end at the thebe and
iterationth at the selected be Let
11 iiiiH
i
i
HcHcKlossKg
iHH
iK
i