I
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ne
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ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
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Co
m
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t
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Science
Vo
l.
23
,
No
.
2
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A
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1011
J
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ttp
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cs.ia
esco
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A self
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a
tor to impro
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he ef
ficiency
o
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g
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o
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o
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sho
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M
rinm
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Cha
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Uda
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ni Vina
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urt
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Co
m
p
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ti
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g
&
IT
,
REV
A Un
iv
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rsity
,
Be
n
g
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lu
ru
,
I
n
d
ia
Art
icle
I
nfo
AB
S
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A
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ticle
his
to
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y:
R
ec
eiv
ed
Feb
15
,
2
0
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1
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ev
is
ed
May
29
,
2
0
2
1
Acc
ep
ted
J
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n
1
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2
0
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te
p
la
n
n
i
n
g
is
a
n
imp
o
r
tan
t
p
a
rt
o
f
ro
a
d
n
e
two
rk
.
To
se
lec
t
a
n
o
p
ti
m
ize
d
ro
u
te
se
v
e
ra
l
fa
c
to
rs
su
c
h
a
s
f
lo
w
o
f
traffic,
sp
e
e
d
li
m
it
s
o
f
ro
a
d
.
a
re
c
o
n
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e
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e
d
.
To
tal
c
o
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o
f
s
u
c
h
a
n
e
two
rk
d
e
p
e
n
d
s
o
n
t
h
e
n
u
m
b
e
r
o
f
ju
n
c
ti
o
n
s
b
e
twe
e
n
th
e
so
u
rc
e
a
n
d
th
e
d
e
sti
n
a
ti
o
n
.
D
u
e
to
t
h
e
g
ro
wt
h
o
f
t
h
e
n
o
d
e
s
in
t
h
e
n
e
two
rk
i
t
b
e
c
o
m
e
s
a
to
u
g
h
jo
b
t
o
d
e
term
in
e
t
h
e
e
x
a
c
t
p
a
th
u
sin
g
d
e
term
in
isti
c
a
lg
o
rit
h
m
s
so
in
s
u
c
h
c
a
se
s
g
e
n
e
ti
c
a
lg
o
rit
h
m
s
(GA
)
p
lay
s
a
v
it
a
l
ro
le
to
f
in
d
th
e
o
p
ti
m
ize
d
r
o
u
te.
Cro
ss
o
v
e
r
is
a
n
imp
o
r
tan
t
o
p
e
ra
to
r
i
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
.
Th
e
e
fficie
n
c
y
o
f
th
e
g
e
n
e
ti
c
a
lg
o
rit
h
m
i
s
d
irec
tl
y
in
flu
e
n
c
e
d
b
y
th
e
ti
m
e
o
f
a
c
ro
ss
o
v
e
r
o
p
e
ra
ti
o
n
.
I
n
th
is p
a
p
e
r
a
n
e
w
c
ro
ss
o
v
e
r
o
p
e
ra
to
r
c
l
o
se
st
-
n
o
d
e
p
a
iri
n
g
c
r
o
ss
o
v
e
r
(CNPC)
is
re
c
o
m
m
e
n
d
e
d
wh
ic
h
is
e
x
p
li
c
it
l
y
d
e
si
g
n
e
d
to
imp
ro
v
e
th
e
p
e
rfo
rm
a
n
c
e
o
f
th
e
g
e
n
e
ti
c
a
lg
o
rit
h
m
c
o
m
p
a
re
d
to
o
th
e
r
we
ll
-
k
n
o
wn
c
ro
ss
o
v
e
r
o
p
e
ra
t
o
rs
su
c
h
a
s
p
o
in
t
b
a
se
d
c
ro
ss
o
v
e
r
a
n
d
o
r
d
e
r
c
ro
ss
o
v
e
r
.
T
h
e
d
istan
c
e
a
sp
e
c
t
o
f
th
e
n
e
two
r
k
p
ro
b
lem
h
a
s
b
e
e
n
e
x
p
l
o
it
e
d
i
n
t
h
is
c
ro
ss
o
v
e
r
o
p
e
ra
to
r
.
Th
is
p
ro
p
o
se
d
tec
h
n
iq
u
e
g
iv
e
s
a
b
e
tt
e
r
re
su
lt
c
o
m
p
a
re
d
to
t
h
e
o
t
h
e
r
c
ro
ss
o
v
e
r
o
p
e
ra
to
r
with
t
h
e
fi
tn
e
ss
v
a
lu
e
o
f
0
.
0
0
4
8
.
T
h
e
CNPC
o
p
e
ra
to
r
g
i
v
e
s
b
e
tt
e
r
ra
te
o
f
c
o
n
v
e
rg
e
n
c
e
c
o
m
p
a
re
d
to
th
e
o
t
h
e
r
c
ro
ss
o
v
e
r
o
p
e
ra
to
rs.
K
ey
w
o
r
d
s
:
C
h
r
o
m
o
s
o
m
e
r
e
p
r
esen
tatio
n
C
o
n
v
er
g
en
ce
Gen
etic
alg
o
r
i
th
m
Or
d
er
cr
o
s
s
o
v
er
Po
in
t b
ased
cr
o
s
s
o
v
er
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Mr
in
m
o
y
ee
C
h
atto
r
aj
Sch
o
o
l o
f
C
o
m
p
u
tin
g
&
I
T
R
E
VA
Un
iv
er
s
ity
Kattig
en
ah
alli,
Yela
h
an
k
a,
B
e
n
g
alu
r
u
,
I
n
d
ia
E
m
ail: m
r
in
m
o
y
ee
2
0
0
5
@
g
m
a
il.c
o
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
th
e
r
ec
e
n
t
er
a,
r
o
u
te
o
p
tim
izatio
n
is
g
ain
in
g
a
l
o
t
o
f
im
p
o
r
tan
ce
.
T
h
er
e
ar
e
v
ar
io
u
s
tec
h
n
iq
u
es
to
f
in
d
th
e
co
r
r
ec
t
p
ath
.
A
lo
t
o
f
s
ig
n
if
ican
ce
is
g
iv
e
n
to
g
en
et
ic
alg
o
r
ith
m
s
s
in
ce
it
h
elp
s
u
s
to
g
iv
e
an
en
d
-
to
-
en
d
o
p
tim
ized
s
o
l
u
tio
n
.
I
n
ca
s
e
o
f
th
e
cu
r
r
en
t
r
o
ad
n
etwo
r
k
as
th
e
r
ate
o
f
tr
af
f
ic
in
c
r
ea
s
es,
th
e
s
er
v
ice
q
u
ality
also
d
ec
r
ea
s
es.
I
n
ca
s
e
o
f
g
en
etic
alg
o
r
ith
m
s
f
r
o
m
in
d
iv
id
u
al
s
ea
r
ch
s
p
ac
e
is
g
en
er
ated
wh
er
e
a
r
esp
ec
tiv
e
in
d
iv
id
u
al
g
iv
es
a
s
p
ec
if
ic
s
o
lu
tio
n
.
g
en
etic
alg
o
r
ith
m
s
(
GAs)
wh
ich
was
d
ev
elo
p
ed
b
y
Ho
llan
d
in
1
9
9
2
,
s
im
u
late
d
Dar
win
'
s
ev
o
lu
tio
n
th
eo
r
y
th
r
o
u
g
h
n
atu
r
al
s
elec
tio
n
by
a
p
ar
ticu
la
r
ty
p
e
o
f
b
i
o
-
in
s
p
ir
ed
a
p
p
r
o
ac
h
.
Acc
o
r
d
in
g
to
t
h
is
th
eo
r
y
th
er
e
is
m
ax
im
u
m
ch
an
ce
s
f
o
r
t
h
e
s
u
r
v
iv
al
o
f
th
e
f
ittes
t
o
r
g
a
n
is
m
.
I
n
th
e
s
ea
r
ch
s
p
ac
e,
g
en
etic
alg
o
r
ith
m
wil
l
ex
p
lo
r
e
all
th
e
s
o
lu
tio
n
s
an
d
th
e
o
p
tim
al
s
o
lu
tio
n
will
b
e
r
etain
ed
.
All
in
d
iv
id
u
als
o
f
a
p
ar
ticu
la
r
s
o
lu
tio
n
ar
e
en
co
d
e
d
in
th
e
f
o
r
m
o
f
ch
r
o
m
o
s
o
m
es.
T
h
e
im
p
o
r
ta
n
t
g
en
etic
o
p
er
ato
r
s
s
u
ch
as
cr
o
s
s
o
v
er
a
n
d
m
u
tatio
n
ar
e
ap
p
lied
to
th
e
p
ar
e
n
t
c
h
r
o
m
o
s
o
m
e
to
ac
h
iev
e
b
etter
s
o
lu
tio
n
s
with
m
o
r
e
p
o
ten
tial.
C
r
o
s
s
o
v
er
o
p
e
r
ato
r
r
ec
o
m
b
in
es
th
e
o
f
f
s
p
r
i
n
g
’
s
a
n
d
p
r
o
d
u
ce
s
n
ew
c
h
r
o
m
o
s
o
m
es
wh
ich
ar
e
m
o
r
e
en
h
an
ce
d
t
h
an
th
e
p
a
r
en
t c
h
r
o
m
o
s
o
m
es.
T
o
d
is
co
v
er
n
ew
s
tates,
m
u
tatio
n
is
o
f
ten
alwa
y
s
n
ee
d
ed
,
a
n
d
it h
elp
s
th
e
g
en
etic
alg
o
r
ith
m
to
escap
e
lo
ca
l
o
p
tim
a.
T
h
ese
p
r
ac
tis
es
ty
p
ically
r
esu
lt
in
f
in
d
in
g
an
o
p
tim
al
o
r
n
ea
r
-
o
p
tim
al
g
lo
b
al
s
o
lu
tio
n
t
o
a
g
i
v
en
p
r
o
b
lem
[
1
]
,
[
2
].
T
h
e
r
e
ar
e
v
ar
io
u
s
ty
p
es
o
f
c
r
o
s
s
o
v
er
o
p
er
ato
r
s
wh
ich
ar
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t 2
0
2
1
:
1
0
1
1
-
1
0
1
7
1012
ap
p
licatio
n
d
ep
e
n
d
en
t a
s
well
as a
p
p
licatio
n
in
d
ep
e
n
d
en
t.
A
g
en
etic
alg
o
r
ith
m
'
s
ef
f
icien
cy
d
ep
en
d
s
as to
wh
at
ki
n
d
o
f
c
r
o
s
s
o
v
er
o
p
er
ato
r
u
s
ed
[
3
]
-
[
5
]
.
I
n
t
h
is
r
ev
iew,
th
e
m
ain
em
p
h
asis
is
o
n
an
im
p
o
r
tan
t
ty
p
e
o
f
p
r
o
b
lem
s
with
co
m
b
i
n
ato
r
ial
o
p
tim
izatio
n
w
h
o
s
e
s
o
lu
tio
n
s
ca
n
b
e
ex
p
r
ess
ed
with
p
er
m
u
t
atio
n
.
I
n
th
is
ty
p
e
o
f
p
r
o
b
lem
,
th
e
jo
b
is
to
ar
r
an
g
e
s
o
m
e
o
b
jects
in
o
r
d
er
to
o
b
ta
in
th
e
o
b
jectiv
e
f
u
n
ctio
n
wh
er
e
n
o
d
u
p
licates
ar
e
allo
wed
.
So
m
e
ex
am
p
les
o
f
t
h
ese
ty
p
es
o
f
p
r
o
b
lem
s
ar
e
L
in
ea
r
o
r
d
e
r
in
g
p
r
o
b
lem
,
s
h
o
r
te
s
t
p
ath
p
r
o
b
lem
an
d
tr
av
ellin
g
s
alesp
er
s
o
n
p
r
o
b
le
m
[
6
]
.
Per
m
u
tatio
n
-
b
ased
Gas a
r
e
g
en
etic
alg
o
r
ith
m
s
th
at
u
s
e
p
ath
r
ep
r
esen
tatio
n
f
o
r
ch
r
o
m
o
s
o
m
es.
Gen
er
ally
,
f
o
r
a
s
et
o
f
in
teg
er
’
s
p
er
m
u
tatio
n
s
is
p
er
f
o
r
m
ed
in
o
r
d
er
to
en
co
d
e
a
p
ath
.
Fo
r
p
er
m
u
tatio
n
p
r
o
b
lem
s
,
th
is
is
th
e
m
o
s
t
g
en
er
al
r
ep
r
esen
tati
o
n
o
f
c
h
r
o
m
o
s
o
m
es
[
7
].
T
h
e
p
ath
r
ep
r
esen
tatio
n
an
d
s
u
g
g
ested
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
o
p
er
ato
r
s
u
n
iq
u
e
to
th
is
r
ep
r
esen
tatio
n
h
av
e
b
e
en
u
s
ed
in
a
r
an
g
e
o
f
r
elev
an
t
s
tu
d
ies
o
n
th
e
a
p
p
li
ca
tio
n
o
f
GAs
to
p
er
m
u
tatio
n
p
r
o
b
lem
s
.
I
n
th
is
an
aly
s
is
,
we
s
u
g
g
est
a
GA
f
o
cu
s
ed
o
n
p
er
m
u
tatio
n
to
a
n
s
wer
p
r
o
b
lem
s
o
f
c
o
m
b
in
ato
r
ial
o
p
tim
izatio
n
.
T
h
e
m
ai
n
attr
ib
u
te
o
f
th
is
GA
co
n
tain
s
an
im
p
r
o
v
ed
c
r
o
s
s
o
v
er
o
p
er
ato
r
wh
ich
im
p
r
o
v
es
t
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
GA.
I
n
o
r
d
er
to
ass
ess
o
u
r
cr
o
s
s
o
v
er
o
p
er
ato
r
'
s
p
er
f
o
r
m
a
n
ce
an
d
f
ea
s
ib
ilit
y
,
we
c
o
m
p
ar
e
it
with
two
well
-
k
n
o
wn
c
r
o
s
s
o
v
er
o
p
er
ato
r
s
Po
in
t
B
ased
C
r
o
s
s
o
v
er
an
d
Or
d
er
C
r
o
s
s
o
v
er
.
T
h
e
r
em
ai
n
in
g
p
a
r
t
o
f
th
e
p
ap
e
r
is
ar
r
an
g
ed
as
f
o
llo
ws:
s
ec
tio
n
2
,
co
n
s
is
ts
o
f
a
s
h
o
r
t
d
escr
ip
tio
n
o
f
GAs
f
o
r
p
r
o
b
lem
s
o
f
p
er
m
u
tatio
n
-
b
ased
co
m
b
in
ato
r
ial
o
p
tim
izatio
n
.
Sectio
n
3
d
escr
ib
es
th
e
p
r
o
b
lem
.
Sectio
n
4
,
ex
p
lain
s
th
e
m
eth
o
d
o
lo
g
y
u
s
ed
in
o
u
r
p
r
o
p
o
s
ed
o
p
er
ato
r
.
Sectio
n
5
,
ev
alu
ates
an
d
d
is
cu
s
s
es
th
e
r
esu
lt
s
b
ased
o
n
th
e
r
esu
lts
.
Fin
ally
,
c
o
n
cl
u
s
io
n
s
ar
e
g
iv
en
in
s
ec
tio
n
6
.
2.
B
ACK
G
RO
UND
C
o
m
b
in
ato
r
ial
o
p
tim
izatio
n
is
a
tech
n
iq
u
e
f
o
cu
s
ed
o
n
f
in
d
i
n
g
an
o
b
ject
(
e.
g
.
a
g
r
ap
h
)
f
r
o
m
a
f
i
n
ite
s
et
o
f
m
ath
em
atica
l
o
b
jects
th
at
s
ig
n
if
ican
tly
r
ed
u
ce
s
o
r
e
n
h
an
ce
s
a
ce
r
ta
in
f
u
n
ctio
n
.
V
ar
iab
les
ar
e
u
s
u
ally
d
is
cr
ete
in
co
m
b
in
ato
r
ial
o
p
tim
izatio
n
tech
n
iq
u
es.
Pe
r
m
u
tatio
n
-
b
ased
p
r
o
b
lem
s
with
co
m
b
in
ato
r
ial
o
p
tim
izatio
n
a
r
e
a
m
ajo
r
class
o
f
p
r
o
b
lem
s
with
co
m
b
in
at
o
r
ial
o
p
tim
izatio
n
wh
o
s
e
s
o
lu
tio
n
s
ar
e
d
ef
in
ed
as
p
er
m
u
tatio
n
s
.
Fin
d
in
g
th
e
Sh
o
r
test
p
ath
is
o
n
e
o
f
th
e
co
m
b
in
ato
r
ial
o
p
tim
izatio
n
p
r
o
b
le
m
s
wh
er
e
we
tr
y
t
o
m
in
im
ize
th
e
to
tal
d
is
tan
ce
tr
a
v
elled
as we
ll a
s
th
e
tim
e
tak
en
.
I
n
s
p
ir
ed
b
y
Dar
win
'
s
th
eo
r
y
o
f
ev
o
l
u
tio
n
an
d
n
atu
r
al
s
e
lectio
n
,
GAs
ar
e
h
ig
h
ly
p
ar
a
llel
s
ea
r
ch
alg
o
r
ith
m
s
th
at
d
e
v
elo
p
a
p
o
p
u
latio
n
o
f
en
co
d
ed
ca
n
d
id
ate
s
o
lu
tio
n
s
(
also
ca
lled
ch
r
o
m
o
s
o
m
es)
wh
er
e
ea
ch
ch
r
o
m
o
s
o
m
e
h
av
e
a
r
elate
d
f
itn
ess
v
alu
e
an
d
th
ey
u
n
d
er
g
o
a
s
et
o
f
g
en
etic
o
p
er
atio
n
s
an
d
f
in
ally
n
ew
p
o
p
u
latio
n
is
g
en
er
ated
.
T
h
er
e
ar
e
v
ar
io
u
s
m
eth
o
d
s
to
r
ep
r
esen
t
ch
r
o
m
o
s
o
m
e
f
o
r
co
m
b
i
n
ato
r
ial
o
p
tim
is
atio
n
p
r
o
b
lem
s
[
8
]
-
[
1
2
]
.
I
n
o
r
d
er
to
m
ee
t
t
h
e
r
e
q
u
ir
em
e
n
t
o
f
th
e
d
iv
er
s
e
n
ee
d
a
v
ar
iety
o
f
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
o
p
er
ato
r
s
h
a
v
e
b
ee
n
d
ev
el
o
p
e
d
.
I
n
o
r
d
er
t
o
f
in
d
an
o
p
tim
al
s
o
lu
tio
n
f
o
r
s
h
o
r
test
p
ath
a
lo
t
o
f
m
o
d
if
icatio
n
h
av
e
b
ee
n
d
o
n
e
o
n
th
e
cr
o
s
s
o
v
er
o
p
er
ato
r
o
f
th
e
g
en
etic
alg
o
r
ith
m
t
o
im
p
r
o
v
e
its
ef
f
icien
cy
.
A
cr
o
s
s
o
v
er
o
p
er
ato
r
is
r
ep
r
esen
te
d
in
[
1
3
]
,
[
1
4
]
,
wh
ich
g
en
er
ates
a
s
in
g
le
cr
o
s
s
o
v
er
p
o
i
n
t,
o
n
t
h
e
b
asis
o
f
co
s
t
co
m
p
ar
is
o
n
.
T
h
is
is
a
v
er
y
s
im
p
le
ap
p
r
o
a
c
h
with
less
d
if
f
icu
lty
b
u
t
it
is
h
ar
d
to
ac
h
iev
e
th
e
o
p
tim
u
m
m
in
im
u
m
c
o
s
t
o
f
tr
av
el.
Par
tially
m
ap
p
ed
cr
o
s
s
o
v
er
(
PMX)
was
s
u
g
g
ested
in
[
1
5
]
,
[
1
6
]
.
T
h
is
p
r
o
ce
d
u
r
e
s
elec
ts
a
two
-
p
o
in
t
cr
o
s
s
o
v
er
o
p
er
ato
r
th
at
s
am
p
les
th
e
p
ar
en
t
ch
r
o
m
o
s
o
m
e
in
to
th
r
ee
s
u
b
s
tr
in
g
s
an
d
s
wap
s
th
e
m
id
d
le
s
u
b
s
tr
in
g
.
Seq
u
en
tial
C
o
n
s
tr
u
ctiv
e
C
r
o
s
s
o
v
er
Op
er
a
to
r
(
SC
X)
[
1
7
]
,
[
1
8
]
p
r
o
d
u
ce
s
an
o
f
f
s
p
r
in
g
f
r
o
m
f
ew
p
ar
e
n
t
s
u
s
in
g
g
o
o
d
e
d
g
es
b
ased
o
n
t
h
eir
f
ea
tu
r
es
th
at
m
ig
h
t
b
e
p
r
esen
t
in
th
e
ar
r
an
g
e
m
en
t
o
f
t
h
e
p
ar
e
n
ts
to
p
r
eser
v
e
th
e
s
u
cc
ess
io
n
o
f
n
o
d
es
in
th
e
p
a
r
en
t
ch
r
o
m
o
s
o
m
es.
T
h
e
o
r
d
e
r
cr
o
s
s
o
v
er
(
O
X)
s
u
g
g
ested
in
[
1
9
]
-
[
2
2
]
g
en
er
ates
o
f
f
s
p
r
in
g
b
y
ch
o
o
s
in
g
a
s
u
b
-
to
u
r
f
r
o
m
o
n
e
p
ar
en
t
an
d
r
etain
in
g
th
e
g
en
er
al
o
r
d
er
o
f
b
its
o
f
th
e
o
th
er
p
a
r
en
t,
wh
ich
is
also
f
o
cu
s
ed
o
n
th
e
cr
o
s
s
o
v
er
o
p
er
ato
r
wi
th
two
p
o
in
ts
.
I
n
c
ase
o
f
C
y
cle
cr
o
s
s
o
v
er
o
p
er
ato
r
(
C
X)
p
r
o
p
o
s
ed
in
[
2
2
]
-
[
2
4
]
b
its
ar
e
tak
e
n
f
r
o
m
b
o
th
p
ar
en
ts
in
a
cir
c
u
lar
o
r
d
er
alo
n
g
with
th
eir
p
o
s
itio
n
.
T
h
is
o
p
er
ato
r
g
iv
es
a
g
o
o
d
r
esu
lt b
u
t t
h
e
d
r
awb
ac
k
is
th
at
it g
iv
es th
e
s
am
e
o
f
f
s
p
r
in
g
’
s
with
th
e
s
am
e
p
ar
en
ts
[
2
5
]
,
[
2
6
]
.
Ho
wev
er
,
it
h
as
b
ee
n
f
o
u
n
d
in
th
e
d
escr
ib
ed
a
p
p
r
o
ac
h
es
ce
r
tain
n
o
d
es
ar
e
r
eu
s
ed
o
v
e
r
an
d
o
v
er
ag
ain
s
o
it is
n
o
t f
ea
s
ib
le
to
att
ain
d
iv
er
s
ity
.
T
h
e
o
f
f
s
p
r
i
n
g
ac
q
u
ir
ed
b
y
cr
o
s
s
o
v
er
o
p
e
r
ato
r
s
is
id
en
tical
to
th
eir
p
ar
en
t
allele
an
d
c
a
n
th
u
s
d
o
e
s
n
o
t
ac
h
iev
e
ev
o
lu
tio
n
.
B
y
m
in
im
is
in
g
th
e
r
ep
licatio
n
o
f
n
o
d
es,
th
e
s
u
g
g
este
d
n
ew
cr
o
s
s
o
v
er
s
tr
ateg
y
p
r
o
p
o
s
ed
in
th
is
p
ap
er
will
o
v
er
co
m
e
th
ese
lim
itatio
n
s
.
I
n
th
is
p
ap
er
we
co
n
s
id
er
th
e
“Ne
w
Yo
r
k
C
ity
T
ax
i
an
d
L
i
m
o
u
s
in
e
C
o
m
m
is
s
io
n
”
d
ata
s
e
t.
T
h
e
s
o
u
r
ce
an
d
d
esti
n
atio
n
p
o
in
t
o
f
th
e
tax
i
tr
ip
ar
e
co
n
s
id
er
ed
as n
o
d
es a
n
d
th
e
s
h
o
r
test
d
is
tan
ce
b
etwe
en
ea
ch
p
air
o
f
n
o
d
es is
ca
lcu
lated
.
3.
M
E
T
H
O
DO
L
O
G
Y
E
ac
h
f
ea
s
ib
le
r
o
u
te
f
o
r
th
e
p
ath
is
r
ep
r
esen
ted
b
y
a
ch
r
o
m
o
s
o
m
e.
R
an
d
o
m
ly
we
cr
ea
t
e
th
e
in
itial
p
o
p
u
latio
n
an
d
t
h
e
f
itn
ess
f
u
n
ctio
n
is
t
h
e
to
tal
d
is
tan
ce
o
f
th
e
r
o
u
te.
Fo
r
th
is
Gen
etic
alg
o
r
ith
m
we
u
s
e
T
o
u
r
n
a
m
en
t
Selectio
n
as
th
e
s
elec
tio
n
o
p
er
ato
r
an
d
Swa
p
m
u
tatio
n
as
th
e
m
u
tatio
n
o
p
e
r
ato
r
.
W
e
iter
ate
it
m
ax
im
u
m
n
u
m
b
er
o
f
tim
es
to
r
ea
ch
th
e
ter
m
in
atio
n
co
n
d
itio
n
.
W
e
p
r
o
p
o
s
e
a
cr
o
s
s
o
v
e
r
o
p
er
ato
r
clo
s
est
-
n
o
d
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
s
elf
a
d
a
p
tive
n
ew cro
s
s
o
ve
r
o
p
era
to
r
to
imp
r
o
ve
th
e
efficie
n
cy
o
f th
e
…
(
Mr
in
mo
ye
e
C
h
a
tto
r
a
j
)
1013
p
air
in
g
cr
o
s
s
o
v
er
(
C
NPC
)
an
d
co
m
p
a
r
e
it
with
ex
is
tin
g
cr
o
s
s
o
v
er
o
p
er
at
o
r
s
lik
e
Po
in
t
B
ased
C
r
o
s
s
o
v
er
an
d
Or
d
er
C
r
o
s
s
o
v
er
.
Ps
eu
d
o
co
d
e
o
f
clo
s
est n
o
d
e
p
a
ir
in
g
cr
o
s
s
o
v
er
o
p
er
at
o
r
:
T
h
e
s
tep
s
in
v
o
lv
e
d
in
th
e
cr
o
s
s
o
v
er
o
p
e
r
ato
r
t
o
o
b
tain
a
c
h
ild
i
f
r
o
m
a
p
ar
en
t
i
co
n
s
id
er
s
t
h
e
d
is
tan
ce
b
etwe
en
two
g
en
es.
a.
I
n
itially
we
s
elec
t
g
en
es
in
a
r
an
d
o
m
m
an
n
er
f
r
o
m
th
e
p
ar
en
t
ch
r
o
m
o
s
o
m
e
an
d
p
u
t
it
d
i
r
ec
tly
in
th
e
s
am
e
lo
ca
tio
n
o
f
t
h
e
ch
ild
c
h
r
o
m
o
s
o
m
e.
b.
I
n
ca
s
e
th
e
f
ir
s
t
g
en
e
o
f
th
e
ch
ild
ch
r
o
m
o
s
o
m
e
i
is
n
o
t
ass
ig
n
ed
th
en
we
s
elec
t
r
an
d
o
m
ly
f
r
o
m
th
e
r
em
ain
in
g
c
h
r
o
m
o
s
o
m
e
o
f
th
e
u
n
ass
ig
n
ed
g
en
es f
r
o
m
t
h
e
p
ar
en
t i
an
d
allo
ca
te
it to
t
h
e
ch
il
d
.
c.
Fo
r
th
e
r
em
ain
i
n
g
u
n
ass
ig
n
ed
g
en
es o
f
th
e
ch
ild
ch
r
o
m
o
s
o
m
e
x
we
f
o
llo
w
th
e
s
tep
s
:
−
Star
tin
g
f
r
o
m
lef
t
we
f
in
d
o
u
t
th
e
g
en
e
th
at
is
n
ea
r
est
to
th
e
ass
ig
n
ed
g
en
e
an
d
ass
ig
n
it
t
o
th
e
ch
ild
i
lo
ca
tio
n
.
−
Similar
ly
,
we
s
elec
t
th
e
r
em
ai
n
in
g
u
n
ass
ig
n
ed
g
en
e
f
r
o
m
p
a
r
en
t
i
wh
ich
is
clo
s
e
to
th
e
ass
ig
n
ed
g
e
n
e
in
s
tep
a.
−
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
till
all
th
e
g
en
es f
r
o
m
p
a
r
en
t x
h
av
e
b
ee
n
ass
ig
n
ed
in
c
h
ild
i.
d.
W
e
r
ep
ea
t th
e
s
am
e
p
r
o
ce
s
s
to
cr
ea
te
C
h
ild
2
f
r
o
m
Par
en
t
2
s
in
ce
th
e
in
itial r
an
d
o
m
s
elec
tio
n
cr
ea
tes a
p
air
o
f
p
ar
e
n
ts
at
a
tim
e.
Fig
u
r
e
1
(
a)
illu
s
tr
ates
th
e
wo
r
k
in
g
p
r
o
ce
s
s
o
f
th
e
cr
o
s
s
o
v
er
o
p
er
ato
r
f
o
r
a
n
etwo
r
k
o
f
eig
h
t
n
o
d
es
A,
B
,
C
,
D,
E
,
F,
G
an
d
H
wh
ic
h
is
s
h
o
wn
in
Fig
u
r
e
1
(
b
)
.
O
n
th
e
ar
c
we
r
ep
r
esen
t
th
e
d
is
tan
ce
b
etwe
en
th
e
n
o
d
es.
T
h
e
p
r
o
ce
s
s
b
eg
i
n
s
b
y
r
an
d
o
m
ly
s
elec
tin
g
g
en
es
E
,
C
,
H
an
d
F
f
r
o
m
th
e
Par
en
t
to
t
h
e
ch
ild
an
d
ass
ig
n
in
g
it
in
th
e
s
am
e
ch
r
o
m
o
s
o
m
al
p
o
s
itio
n
.
Sin
ce
th
e
f
ir
s
t
p
o
s
itio
n
o
f
th
e
ch
ild
ch
r
o
m
o
s
o
m
e
is
n
o
t
ass
ig
n
ed
s
o
we
r
an
d
o
m
ly
s
ele
ct
an
y
g
en
e
f
r
o
m
th
e
u
n
ass
ig
n
ed
g
en
es
o
f
th
e
p
ar
e
n
t.
I
n
t
h
is
ex
am
p
le
A,
B
,
D
an
d
G
ar
e
th
e
u
n
ass
ig
n
ed
g
en
e
s
s
o
we
h
ad
s
elec
ted
G.
Fo
r
all
o
th
er
g
en
es
we
s
elec
t
th
at
g
en
e
wh
ich
is
clo
s
est
to
th
e
g
e
n
e
o
n
th
e
lef
t.
I
n
p
la
ce
o
f
th
e
th
ir
d
g
en
e
o
f
t
h
e
ch
i
ld
ch
r
o
m
o
s
o
m
e
we
p
lace
D
s
in
ce
it
is
n
ea
r
est
to
g
en
e
E
.
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
f
o
r
all
th
e
u
n
ass
ig
n
ed
g
e
n
es
in
th
e
p
ar
e
n
t
ch
r
o
m
o
s
o
m
e
.
T
h
u
s
,
we
o
b
tain
a
ch
ild
ch
r
o
m
o
s
o
m
e
f
r
o
m
a
p
ar
e
n
t c
h
r
o
m
o
s
o
m
e.
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
to
o
b
tain
ch
ild
2
f
o
r
th
e
p
ar
en
t.
I
n
ca
s
e
o
f
o
r
d
e
r
c
r
o
s
s
o
v
er
(
O
X)
to
g
en
er
ate
a
f
ea
s
ib
le
o
f
f
s
p
r
in
g
b
o
th
th
e
p
ar
en
ts
ar
e
r
eq
u
i
r
ed
.
I
n
th
e
b
eg
in
n
in
g
we
s
elec
t
a
s
u
b
s
tr
in
g
f
r
o
m
Par
en
t
1
in
a
r
an
d
o
m
o
r
d
er
.
T
h
en
th
o
s
e
g
en
es
s
elec
ted
f
r
o
m
th
e
f
ir
s
t
p
ar
en
t
ar
e
d
elete
d
in
th
e
s
ec
o
n
d
p
ar
e
n
t
an
d
th
e
r
em
ain
i
n
g
g
en
es
f
r
o
m
th
e
s
ec
o
n
d
p
ar
en
t
ar
e
p
u
t
in
th
e
ch
il
d
ch
r
o
m
o
s
o
m
e.
Similar
ly
,
t
h
e
s
ec
o
n
d
ch
ild
is
cr
ea
ted
b
y
c
o
n
s
id
er
in
g
th
e
f
ir
s
t
s
et
o
f
g
e
n
es
f
r
o
m
Par
en
t
2
.
Po
s
itio
n
b
ased
cr
o
s
s
o
v
er
(
PB
X)
also
r
eq
u
ir
es
b
o
th
th
e
p
ar
en
ts
to
g
en
er
ate
two
o
f
f
s
p
r
in
g
.
I
n
th
is
ca
s
e
we
r
an
d
o
m
l
y
s
elec
t
a
s
et
o
f
g
en
es
f
r
o
m
th
e
Par
en
t1
an
d
tr
an
s
f
er
it
to
its
ch
ild
r
e
n
.
I
t
m
ay
o
r
m
ay
n
o
t
b
e
a
s
u
b
s
tr
in
g
.
T
h
e
s
elec
ted
g
en
es
f
r
o
m
Par
en
t1
ar
e
d
elete
d
f
r
o
m
Par
en
t2
an
d
th
e
n
th
e
r
e
m
ain
in
g
g
en
es
f
r
o
m
Par
en
t2
ar
e
tr
an
s
f
er
r
e
d
to
th
e
ch
ild
.
Fig
u
r
e
2
(
a)
illu
s
tr
ates
o
r
d
er
cr
o
s
s
o
v
e
r
wh
er
ea
s
Fig
u
r
e
2
(
b
)
illu
s
tr
ates
p
o
s
itio
n
-
b
ased
cr
o
s
s
o
v
er
f
o
r
t
h
e
s
am
e
n
etwo
r
k
s
h
o
wn
in
Fig
u
r
e
1
.
(
a)
(
b
)
Fig
u
r
e
1
.
T
h
ese
f
ig
u
r
es a
r
e;
(
a
)
clo
s
estn
o
d
e
p
air
in
g
cr
o
d
d
o
v
er
o
p
er
at
o
r
;
(
b
)
n
etwo
r
k
d
iag
r
am
o
f
8
n
o
d
es
(
a)
(
b
)
Fig
u
r
e
2
.
T
h
ese
f
ig
u
r
es a
r
e;
(
a
)
o
r
d
e
r
cr
o
s
s
o
v
er
v
is
u
al
illu
s
tr
atio
n
;
(
b
)
p
o
s
itio
n
b
ased
c
r
o
s
s
o
v
er
v
is
u
al
illu
s
tr
atio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
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Sci,
Vo
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g
u
s
t 2
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1
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1
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7
1014
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
Gen
etic
alg
o
r
ith
m
was
u
s
ed
with
th
e
to
u
r
n
am
e
n
t
s
ize
o
f
2
,
m
u
tatio
n
r
ate
5
%
an
d
ter
m
in
atio
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n
d
itio
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f
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0
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atio
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cr
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ted
3
5
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s
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s
p
er
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o
s
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er
wh
e
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e
th
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in
itial
p
o
p
u
latio
n
ar
e
p
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ed
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m
in
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at
all
th
e
c
r
o
s
s
o
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er
ato
r
s
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av
e
th
e
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am
e
s
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o
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t.
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h
e
f
o
llo
wi
n
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e
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p
er
im
e
n
t
was
p
er
f
o
r
m
ed
to
c
o
m
p
ar
e
o
u
r
cr
o
s
s
o
v
er
o
p
e
r
ato
r
with
k
n
o
wn
c
r
o
s
s
o
v
er
o
p
er
ato
r
s
lik
e
OX
an
d
PB
X.
W
e
ch
an
g
e
th
e
p
o
p
u
latio
n
s
ize
an
d
o
b
s
er
v
e
its
ef
f
ec
t
o
n
t
h
e
d
is
tan
ce
o
f
th
e
r
o
u
te
a
n
d
its
c
o
m
p
u
tatio
n
tim
e.
W
e
also
d
o
a
co
m
p
ar
ativ
e
s
tu
d
y
o
f
th
e
co
n
v
er
g
en
ce
r
ates
o
f
th
e
th
r
ee
cr
o
s
s
o
v
er
o
p
er
at
o
r
s
.
I
n
o
u
r
ex
p
e
r
i
m
en
t
we
ad
ju
s
t
o
u
r
p
o
p
u
latio
n
s
ize
to
1
0
,
2
5
,
5
0
,
1
0
0
an
d
2
0
0
.
Hen
ce
a
to
t
al
o
f
5
(
p
o
p
u
latio
n
s
ize)
*
3
(
c
r
o
s
s
o
v
er
o
p
er
ato
r
s
)
*
3
0
(
in
s
tan
ce
s
)
=4
5
0
test
r
u
n
s
wer
e
co
n
d
u
cte
d
.
W
e
ch
ec
k
th
e
r
o
u
te
d
is
tan
ce
an
d
tim
e
tak
en
f
o
r
all
th
e
th
r
ee
cr
o
s
s
o
v
er
o
p
e
r
ato
r
s
.
T
ab
le
1
s
h
o
ws
th
e
b
est
,
w
o
r
s
t
an
d
av
e
r
ag
e
r
o
u
te
d
is
tan
ce
o
b
tain
ed
f
r
o
m
th
e
th
r
ee
cr
o
s
s
o
v
er
o
p
er
ato
r
s
.
I
t
h
as
b
ee
n
o
b
s
er
v
e
d
th
at
f
r
o
m
all
th
e
cr
o
s
s
o
v
er
o
p
er
ato
r
s
th
e
b
est
r
o
u
te
d
is
tan
ce
is
1
9
0
8
6
m
etr
es.
T
h
e
wo
r
s
t
an
d
av
er
a
g
e
r
o
u
te
d
is
tan
ce
s
v
ar
ies
with
th
e
p
o
p
u
latio
n
s
ize.
I
n
ca
s
e
o
f
O
X
an
d
PB
X
as
th
e
p
o
p
u
latio
n
s
ize
in
c
r
ea
s
es
th
e
av
er
ag
e
r
o
u
te
d
is
tan
ce
d
ec
r
ea
s
es
b
u
t
in
ca
s
e
o
f
th
e
n
ew
cr
o
s
s
o
v
er
o
p
e
r
ato
r
th
e
d
is
tan
ce
v
ar
ies
with
in
a
s
m
all
r
an
g
e.
He
n
ce
th
e
p
o
p
u
latio
n
s
ize
d
o
es
n
o
t
m
a
k
e
a
m
ajo
r
ef
f
ec
t
in
th
e
r
o
u
te
d
is
tan
ce
.
T
ab
le
1
.
B
est,
wo
r
s
t a
n
d
av
e
r
a
g
e
r
o
u
te
d
is
tan
ce
o
b
tain
e
d
f
r
o
m
th
e
th
r
ee
c
r
o
s
s
o
v
er
,
o
r
d
er
cr
o
s
s
o
v
er
(
OX)
,
p
o
s
itio
n
-
b
ased
cr
o
s
s
o
v
er
(
PB
X)
an
d
th
e
p
r
o
p
o
s
ed
cr
o
s
s
o
v
er
(
C
NPC
)
P
O
P
U
LA
TI
O
N
S
I
ZE
10
25
50
1
0
0
2
0
0
OX
B
e
st
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
W
o
r
st
2
1
9
5
6
2
2
3
6
7
2
2
9
6
8
2
1
5
3
9
2
0
1
4
0
A
v
e
r
a
g
e
2
1
5
3
0
2
0
4
7
6
2
0
4
9
8
1
9
8
4
3
1
9
3
3
7
P
B
X
B
e
st
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
1
9
0
8
6
W
o
r
st
2
2
1
0
0
2
2
0
5
0
2
2
0
5
0
2
2
6
8
0
2
1
0
4
5
A
v
e
r
a
g
e
2
0
7
7
5
2
0
6
3
4
2
0
1
7
3
1
9
9
9
6
1
9
5
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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esian
J
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n
g
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m
p
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N:
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ize
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ak
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u
r
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5
.
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if
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t c
r
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r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
5
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2
I
n
d
o
n
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J
E
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n
g
&
C
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m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t 2
0
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1
:
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1
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1
7
1016
5.
CO
NCLU
SI
O
N
I
n
o
r
d
e
r
to
f
in
d
th
e
s
h
o
r
test
r
o
u
te
u
s
in
g
g
e
n
etic
alg
o
r
ith
m
we
p
r
o
p
o
s
e
a
n
ew
cr
o
s
s
o
v
e
r
o
p
er
ato
r
clo
s
est
n
o
d
e
p
air
in
g
cr
o
s
s
o
v
er
(
C
NPC
)
wh
o
s
e
o
v
er
all
p
er
f
o
r
m
an
ce
is
b
etter
th
an
OX
an
d
PB
X
wh
ich
ar
e
th
e
cr
o
s
s
o
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s
wh
ich
is
v
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y
co
m
m
o
n
.
I
t
h
as
b
ee
n
o
b
s
e
r
v
ed
th
at
th
e
p
e
r
f
o
r
m
an
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o
f
c
r
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s
s
o
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p
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s
m
ain
ly
OX
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d
PB
X
d
ep
en
d
s
m
o
s
tly
o
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th
e
p
o
p
u
l
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n
s
ize
wh
ile
th
e
C
NP
C
o
p
er
ato
r
is
n
o
t
m
u
ch
d
e
p
en
d
e
d
o
n
th
e
p
o
p
u
latio
n
s
ize.
T
h
e
c
o
n
v
er
g
en
ce
r
ate
o
f
t
h
e
C
NPC
o
p
er
ato
r
is
also
f
aster
as
co
m
p
ar
ed
t
o
th
e
o
th
er
cr
o
s
s
o
v
er
o
p
e
r
ato
r
s
.
RE
F
E
R
E
NC
E
S
[1
]
A.
E.
Ei
b
e
n
a
n
d
J.
E.
S
m
it
h
,
In
tro
d
u
c
ti
o
n
t
o
e
v
o
l
u
ti
o
n
a
ry
c
o
mp
u
ti
n
g
,
Be
rli
n
,
He
id
e
l
b
e
rg
:
S
p
ri
n
g
e
r
,
2
0
1
5
.
[2
]
M.
Ch
a
tt
o
ra
j
a
n
d
V.
U.
Ra
n
i,
“
Ro
a
d
traffic
n
e
two
rk
so
l
u
ti
o
n
i
n
M
a
tl
a
b
u
si
n
g
s
o
ft
c
o
m
p
u
ti
n
g
,
”
2
0
1
7
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
S
ma
rt
T
e
c
h
n
o
l
o
g
ies
f
o
r
S
ma
rt
N
a
ti
o
n
(S
ma
rtT
e
c
h
C
o
n
)
,
2
0
1
7
,
p
p
.
1
4
3
4
-
1
4
3
7
,
d
o
i:
1
0
.
1
1
0
9
/S
m
a
rtT
e
c
h
Co
n
.
2
0
1
7
.
8
3
5
8
6
0
1
.
[3
]
A.
El
Be
q
a
l,
B.
Be
n
h
a
la
,
a
n
d
I.
Zo
rk
a
n
i,
“
A
g
e
n
e
ti
c
a
lg
o
r
it
h
m
fo
r
th
e
o
p
ti
m
a
l
d
e
sig
n
o
f
a
m
u
lt
ist
a
g
e
a
m
p
li
fier
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
E
n
g
i
n
e
e
rin
g
,
v
o
l.
10
,
n
o
.
1
,
p
p
.
1
2
9
-
1
3
8
,
2
0
2
0
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
e
c
e
.
v
1
0
i1
.
p
p
1
2
9
-
138
.
[4
]
A.
J.
Um
b
a
rk
a
r
a
n
d
P
.
D.
S
h
e
th
,
“
Cro
ss
o
v
e
r
o
p
e
ra
to
rs
i
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
s:
A
re
v
iew
,
”
ICT
ACT
jo
u
rn
a
l
o
n
so
f
t
c
o
mp
u
ti
n
g
,
v
o
l.
6
,
n
o
.
1
,
2
0
1
5
,
d
o
i:
1
0
.
2
1
9
1
7
/
ij
sc
.
2
0
1
5
.
0
1
5
0
.
[5
]
R.
P
in
h
o
a
n
d
F.
S
a
ra
iv
a
,
“
A
c
o
m
p
a
riso
n
o
f
c
ro
ss
o
v
e
r
o
p
e
ra
to
rs
in
g
e
n
e
ti
c
a
lg
o
ri
th
m
s
fo
r
sw
it
c
h
a
ll
o
c
a
ti
o
n
p
r
o
b
lem
in
p
o
we
r
d
istri
b
u
ti
o
n
sy
ste
m
s
,”
2
0
2
0
IEE
E
Co
n
g
re
ss
o
n
Ev
o
l
u
ti
o
n
a
ry
C
o
mp
u
ta
t
io
n
(CEC)
,
2
0
2
0
,
p
p
.
1
-
8
,
d
o
i:
1
0
.
1
1
0
9
/CE
C
4
8
6
0
6
.
2
0
2
0
.
9
1
8
5
7
9
5
.
[6
]
C.
H.
P
a
p
a
d
imitr
io
u
a
n
d
K.
S
tei
g
li
tz,
C
o
mb
i
n
a
t
o
ria
l
o
p
ti
miza
ti
o
n
:
Al
g
o
rit
h
ms
a
n
d
c
o
m
p
lex
it
y
,
Ha
wa
ii
:
Co
u
rier
Co
rp
o
ra
ti
o
n
,
1
9
9
8
.
[7
]
K.
L.
D
u
a
n
d
M
.
N.
S
.
S
wa
m
y
,
“
S
e
a
rc
h
a
n
d
o
p
ti
m
iza
ti
o
n
b
y
m
e
tah
e
u
risti
c
s
,
”
T
e
c
h
n
iq
u
e
s
a
n
d
Al
g
o
rith
ms
In
sp
ire
d
b
y
Na
t
u
re
;
Birk
h
a
u
se
r:
Ba
se
l,
S
w
it
z
e
rlan
d
,
2
0
1
6
.
[8
]
G.
P
a
v
a
i
a
n
d
T.
V.
G
e
e
th
a
,
“
A
su
rv
e
y
o
n
c
r
o
ss
o
v
e
r
o
p
e
ra
to
rs
,
”
A
CM
Co
mp
u
ti
n
g
S
u
rv
e
y
s
(CS
UR)
,
v
o
l
.
49
,
n
o
.
4
,
p
p
.
1
-
43
,
2
0
1
6
,
d
o
i:
1
0
.
1
1
4
5
/3
0
0
9
9
6
6
.
[9
]
L.
M
a
n
z
o
n
i,
L.
M
a
rio
t,
a
n
d
E.
Tu
b
a
,
“
Ba
lan
c
e
d
c
ro
ss
o
v
e
r
o
p
e
ra
to
rs
in
g
e
n
e
ti
c
a
lg
o
rit
h
m
s
,
”
S
wa
rm
a
n
d
Evo
lu
ti
o
n
a
ry
Co
mp
u
t
a
ti
o
n
,
v
o
l.
5
4
,
2
0
2
0
,
d
o
i:
1
0
.
1
0
1
6
/
j.
sw
e
v
o
.
2
0
2
0
.
1
0
0
6
4
6
.
[1
0
]
P.
Larra
n
a
g
a
,
C.
M
.
H.
Ku
ij
p
e
rs,
R.
H
.
M
u
rg
a
,
I.
In
z
a
,
a
n
d
S
.
Di
z
d
a
re
v
ic
,
“
G
e
n
e
ti
c
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R.
S
a
b
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S.
Du
n
s
tall,
a
n
d
A.
S
o
n
g
,
“
Hy
p
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ti
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lo
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,
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2
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S.
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,
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.
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m
a
d
,
S
.
M
.
Ha
ti
m
,
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Ba
h
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ru
n
,
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Om
a
r,
a
n
d
A.
S
.
A.
Ra
h
m
a
n
,
“
Diffe
re
n
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m
u
tatio
n
a
n
d
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ro
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t
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ra
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a
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m
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ted
m
a
c
h
in
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lea
rn
in
g
,
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S
I
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ter
n
a
ti
o
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a
l
J
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ter,
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o
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in
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n
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n
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C
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fer
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4
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R.
B.
Ab
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jab
b
a
r,
O.
K.
Ha
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id
,
a
n
d
N.
J.
Alh
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a
n
i,
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F
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A.
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,
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Un
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.
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Attarm
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d
d
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m
,
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F
.
Li
,
a
n
d
A.
Ka
n
a
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,
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P
G
A
imp
lem
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tatio
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d
,
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n
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ter
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8
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M
ru
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.
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,”
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telli
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Al
g
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ms
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r
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lys
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9
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A.
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m
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d
M.
Ay
o
b
,
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n
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m
fo
r
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in
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to
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i
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l
o
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ti
m
iza
ti
o
n
p
ro
b
lem
s
,
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mp
u
ter
s &
In
d
u
stria
l
E
n
g
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,
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0
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z
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A.
A.
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E
.
-
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leh
,
a
n
d
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Ra
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n
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lg
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h
m
s
,”
2
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te
rn
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ti
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Co
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1
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.
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Oro
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,
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M
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S
iso
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n
d
R
.
P
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2
0
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8
5
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In
ter
n
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2
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A
.
Ca
n
o
,
P.
C
.
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h
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,
E
.
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.
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m
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n
d
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A.
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.
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a
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m
,
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n
ter
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ti
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a
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J
o
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El
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trica
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g
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IJ
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),
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l.
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p
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.
[2
3
]
V.
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in
g
h
,
L
.
G
a
n
a
p
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th
y
,
a
n
d
A.
K.
P
u
n
d
ir
,
“
An
imp
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ter
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f
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.
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,
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.
4
,
p
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[2
4
]
M
.
H.
Ha
ss
a
n
,
M
.
A.
Ju
b
a
ir
,
S
.
A.
M
o
sta
fa
,
H.
Ka
m
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lu
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i
n
,
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M
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.
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In
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In
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ig
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5
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.
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V.
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Ra
n
i
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De
tec
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