I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
41
,
No
.
2
,
Feb
r
u
ar
y
20
26
,
p
p
.
666
~
679
I
SS
N:
2
502
-
4
7
52
,
DOI
: 1
0
.
1
1
5
9
1
/ijee
cs
.v
41.
i
2
.
p
p
666
-
6
7
9
666
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs
.
ia
esco
r
e.
co
m
The
B
ender
’
s de
c
o
mpo
sitio
n mo
del t
o
optimiz
e t
e
mp
o
ra
ry
wa
ste dispo
sa
l sit
es ba
sed o
n gener
a
l alg
ebra
ic mo
deling
sy
stem
Sis
ca
O
ct
a
rina
1
,
F
it
ri
M
a
y
a
P
us
pita
1
,
E
n
dro
Set
y
o
Ca
hy
o
no
1
,
E
v
i Y
uli
za
1
,
P
ebriy
a
nti
Sim
a
njunt
a
k
1
,
Si
t
i Suzlin
S
up
a
di
2
1
D
e
p
a
r
t
me
n
t
o
f
M
a
t
h
e
m
a
t
i
c
s
,
F
a
c
u
l
t
y
o
f
M
a
t
h
e
mat
i
c
s
a
n
d
N
a
t
u
r
a
l
S
c
i
e
n
c
e
s,
U
n
i
v
e
r
s
i
t
a
s Sr
i
w
i
j
a
y
a
,
I
n
d
r
a
l
a
y
a
,
I
n
d
o
n
e
si
a
2
I
n
st
i
t
u
t
e
o
f
M
a
t
h
e
mat
i
c
a
l
S
c
i
e
n
c
e
s
,
U
n
i
v
e
r
si
t
y
o
f
M
a
l
a
y
a
,
K
u
a
l
a
Lu
mp
u
r
,
M
a
l
a
y
s
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Feb
9
,
2
0
2
5
R
ev
is
ed
Dec
2
,
2
0
2
5
Acc
ep
ted
J
an
11
,
2
0
2
6
Was
te
c
o
n
stit
u
tes
a
su
b
sta
n
ti
a
l
p
ro
b
lem
i
n
u
rb
a
n
a
n
d
re
si
d
e
n
ti
a
l
l
o
c
a
les
,
a
s
th
e
v
o
l
u
m
e
o
f
re
fu
se
e
sc
a
late
s
in
tan
d
e
m
with
p
o
p
u
latio
n
in
c
re
a
se
,
d
e
terio
ra
ti
n
g
c
o
m
m
u
n
it
y
q
u
a
li
ty
o
f
li
fe
.
On
e
so
lu
t
io
n
to
t
h
is
p
ro
b
lem
is
to
p
ro
v
id
e
tem
p
o
ra
ry
wa
ste
d
isp
o
sa
l
sites
(TW
DS).
Th
is
re
se
a
rc
h
d
isc
u
ss
e
d
o
p
ti
m
izi
n
g
TW
DS
i
n
th
e
S
u
k
a
ra
m
i
S
u
b
d
istri
c
t
,
P
a
lem
b
a
n
g
Ci
ty
,
w
h
ich
c
o
n
sists
o
f
se
v
e
n
v
il
lag
e
s.
T
h
e
c
u
rre
n
t
TW
DS
in
th
e
S
u
k
a
ra
m
i
S
u
b
d
istri
c
t
is
irreg
u
lar,
with
so
m
e
sites
lo
c
a
ted
c
lo
se
to
g
e
th
e
r
a
n
d
o
t
h
e
rs
fa
r
a
p
a
rt.
Th
e
o
p
ti
m
iza
ti
o
n
p
r
o
b
lem
is
so
lv
e
d
b
y
fo
rm
u
lati
n
g
th
e
se
t
c
o
v
e
rin
g
p
r
o
b
lem
(S
CP
)
m
o
d
e
l,
n
a
m
e
ly
t
h
e
se
t
c
o
v
e
ri
n
g
lo
c
a
ti
o
n
p
ro
b
lem
(S
CLP
),
t
h
e
p
-
M
e
d
ian
p
r
o
b
lem
,
a
n
d
th
e
Be
n
d
e
r
’
s
d
e
c
o
m
p
o
siti
o
n
m
o
d
e
l.
All
m
o
d
e
ls
we
re
so
lv
e
d
u
sin
g
t
h
e
g
e
n
e
ra
l
a
lg
e
b
ra
ic
m
o
d
e
li
n
g
s
y
ste
m
(G
AMS
)
so
ftwa
re
.
Th
e
re
se
a
rc
h
in
tro
d
u
c
e
s
a
Be
n
d
e
r
’
s
d
e
c
o
m
p
o
si
ti
o
n
m
o
d
e
l
b
a
s
e
d
o
n
th
e
S
CLP
m
o
d
e
l.
T
h
e
S
u
k
a
ra
m
i
S
u
b
d
istri
c
t
h
a
s
2
9
TW
DS
l
o
c
a
ted
i
n
o
n
ly
fi
v
e
v
il
lag
e
s.
Us
i
n
g
t
h
e
S
CL
P
a
n
d
Be
n
d
e
r
’
s
d
e
c
o
m
p
o
siti
o
n
m
o
d
e
ls,
th
e
stu
d
y
id
e
n
ti
fie
d
1
9
o
p
ti
m
a
l
TW
DS
in
th
e
S
u
k
a
ra
m
i
S
u
b
d
istri
c
t
.
Ba
se
d
o
n
t
h
e
so
lu
ti
o
n
o
f
th
e
p
-
M
e
d
ian
p
ro
b
lem
,
th
e
re
a
re
se
v
e
n
TW
DS
th
a
t
c
a
n
m
e
e
t
e
a
c
h
v
il
lag
e
’
s
d
e
m
a
n
d
.
T
h
is
st
u
d
y
r
e
c
o
m
m
e
n
d
s
th
e
o
p
ti
m
a
l
TW
DS
o
b
tain
e
d
fro
m
th
e
Be
n
d
e
r
’
s
d
e
c
o
m
p
o
sit
i
o
n
m
o
d
e
l
.
Ad
d
i
ti
o
n
a
ll
y
,
tw
o
T
WDS
a
re
re
c
o
m
m
e
n
d
e
d
to
b
e
a
d
d
e
d
,
e
a
c
h
i
n
S
u
k
o
d
a
d
i
a
n
d
Tala
n
g
Be
tu
t
u
v
i
l
lag
e
s.
K
ey
w
o
r
d
s
:
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
GAM
S
L
o
ca
tio
n
o
p
tim
izatio
n
Set c
o
v
er
in
g
p
r
o
b
lem
T
em
p
o
r
ar
y
waste
d
is
p
o
s
al
s
ite
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
:
Sis
ca
Octa
r
in
a
Dep
ar
tm
en
t o
f
Ma
th
em
atics,
Facu
lty
o
f
Ma
th
e
m
atics a
n
d
Na
tu
r
al
Scien
ce
s
,
Un
iv
er
s
itas
Sriwijay
a
I
n
d
r
alay
a
,
I
n
d
o
n
esia
E
m
ail:
s
is
ca
_
o
ctar
in
a@
u
n
s
r
i.a
c.
id
1.
I
NT
RO
D
UCT
I
O
N
W
aste
d
en
o
tes
wasted
o
b
jects
o
r
item
s
th
at
a
r
e
n
o
l
o
n
g
e
r
f
u
n
ctio
n
al
o
r
s
o
u
g
h
t
af
ter
.
T
h
e
v
o
lu
m
e
o
f
waste
is
escalatin
g
alo
n
g
s
id
e
p
o
p
u
latio
n
g
r
o
wth
,
p
o
ten
tially
d
im
in
is
h
in
g
th
e
q
u
ality
o
f
life
f
o
r
r
esid
en
ts
in
th
e
v
icin
ity
[
1
]
.
I
n
ad
eq
u
ate
waste
m
an
ag
em
e
n
t
ca
n
lead
to
h
ea
lth
is
s
u
es
ca
u
s
ed
b
y
t
h
e
c
o
n
tam
in
atio
n
o
f
air
,
wate
r
,
an
d
s
o
il
b
y
d
is
ea
s
e
v
ec
to
r
s
.
W
aste
m
an
ag
em
en
t
n
ec
ess
itate
s
ca
r
ef
u
l
co
n
s
id
er
atio
n
,
as
it
ca
n
ad
v
er
s
ely
af
f
ec
t
th
e
en
v
ir
o
n
m
en
t
if
n
eg
lecte
d
[
2
]
.
A
v
iab
le
s
o
lu
tio
n
to
th
is
is
s
u
e
in
u
r
b
an
o
r
r
esid
en
tial
ar
ea
s
is
th
e
estab
lis
h
m
en
t
o
f
tem
p
o
r
ar
y
waste
d
is
p
o
s
al
s
ites
(
T
W
D
S).
T
W
DS
f
u
n
ctio
n
s
as
a
lo
ca
tio
n
wh
er
e
clea
n
er
s
tr
an
s
f
er
g
a
r
b
ag
e
to
r
ec
y
clin
g
,
waste
s
o
r
tin
g
,
waste
p
r
o
ce
s
s
in
g
,
o
r
f
in
al
d
is
p
o
s
al
s
ites
(
FDS).
E
v
er
y
r
e
g
io
n
m
u
s
t
estab
lis
h
it
s
tr
ash
d
is
p
o
s
al
s
ite
s
.
A
s
tr
ateg
ically
p
o
s
it
io
n
ed
T
W
DS
is
th
e
f
ir
s
t
s
tep
in
co
n
tr
o
llin
g
an
d
m
ain
tain
in
g
a
clea
n
en
v
ir
o
n
m
en
t.
B
an
g
u
n
et
a
l.
[
3
]
s
tates
th
at
Pa
lem
b
an
g
C
ity
is
a
m
etr
o
p
o
lis
th
at
co
n
tin
u
o
u
s
ly
p
r
o
d
u
ce
s
in
cr
ea
s
in
g
v
o
lu
m
es
o
f
waste
d
u
e
t
o
p
o
p
u
latio
n
g
r
o
wth
.
T
h
e
p
o
p
u
latio
n
d
en
s
ity
in
Palem
b
an
g
C
ity
is
th
e
lead
in
g
ca
u
s
e
o
f
th
is
in
cr
ea
s
e.
E
ac
h
p
er
s
o
n
in
Palem
b
a
n
g
C
ity
co
n
tr
ib
u
tes
0
.
8
%
o
f
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:
2
5
0
2
-
4
7
52
Th
e
B
en
d
er
’
s
d
ec
o
mp
o
s
itio
n
mo
d
el
to
o
p
timiz
e
temp
o
r
a
r
y
w
a
s
te
d
is
p
o
s
a
l sit
e
s
b
a
s
ed
o
n
…
(
S
is
ca
Octa
r
in
a
)
667
d
aily
waste,
r
esu
ltin
g
in
a
we
ek
ly
v
o
l
u
m
e
o
f
ar
o
u
n
d
8
0
0
-
9
0
0
m
etr
ic
to
n
s
.
On
wee
k
en
d
s
an
d
h
o
lid
ay
s
,
th
e
v
o
lu
m
e
o
f
waste
ca
n
in
cr
ea
s
e
to
1
,
0
0
0
m
etr
ic
to
n
s
.
T
h
is
s
tu
d
y
e
x
am
in
es
th
e
p
o
s
i
tio
n
in
g
o
f
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
.
I
n
2
0
2
0
,
t
h
e
ce
n
tr
al
b
u
r
ea
u
o
f
s
tatis
tic
s
(
C
B
S)
r
ep
o
r
ted
th
at
th
e
Su
k
ar
am
i
Su
b
d
i
s
tr
ict
h
as
th
e
h
ig
h
est
p
o
p
u
latio
n
an
d
th
e
s
ec
o
n
d
lar
g
est
ar
ea
am
o
n
g
th
e
1
8
Su
b
d
is
tr
ict
in
Palem
b
an
g
C
ity
,
So
u
th
Su
m
atr
a
Pro
v
in
ce
.
T
h
e
p
o
p
u
latio
n
is
1
5
8
,
2
4
6
,
co
v
er
in
g
an
ar
ea
o
f
5
,
1
4
5
.
9
h
ec
tar
es,
f
ea
t
u
r
in
g
m
u
ltip
le
r
esid
en
tial
c
o
m
p
lex
es,
o
f
f
ices,
a
n
d
an
in
d
u
s
tr
ial
s
ec
to
r
in
v
o
lv
e
d
in
d
iv
er
s
e
ac
tiv
ities
.
T
h
e
d
ep
ar
tm
en
t
o
f
en
v
ir
o
n
m
en
t
an
d
h
y
g
ie
n
e
(
DE
H)
o
v
e
r
s
ee
s
tr
ash
m
an
ag
em
e
n
t,
tr
a
n
s
p
o
r
tat
io
n
,
an
d
s
an
itatio
n
m
atter
s
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
.
Up
d
atin
g
th
e
p
o
s
itio
n
p
o
in
ts
o
f
th
e
2
9
g
o
v
er
n
m
en
t
-
p
r
o
v
id
e
d
T
W
DS
ac
r
o
s
s
v
ar
io
u
s
u
r
b
an
v
illag
es
is
ess
en
tial
f
o
r
ef
f
ec
tiv
e
waste
d
is
p
o
s
al
an
d
e
n
v
ir
o
n
m
en
tal
clea
n
lin
ess
.
Dete
r
m
in
in
g
th
e
p
o
s
itio
n
o
f
T
W
DS
p
r
esen
ts
ch
allen
g
es,
as
tw
o
v
illag
es
in
th
e
Su
k
ar
am
i
S
u
b
d
is
tr
ict
lack
waste
s
tatio
n
s
,
an
d
th
e
d
is
tan
ce
b
etwe
e
n
T
W
DS
r
eq
u
ir
es
ad
ju
s
tm
en
t.
T
h
is
p
r
o
b
lem
le
ad
s
to
litt
er
in
g
an
d
th
e
ac
c
u
m
u
latio
n
o
f
ex
ce
s
s
iv
e
r
u
b
b
is
h
at
th
e
cu
r
r
en
t
d
is
p
o
s
al
s
ites
.
Op
tim
izin
g
T
W
DS
co
n
s
titu
te
s
an
o
p
tim
izatio
n
ch
allen
g
e.
T
h
is
is
s
u
e
en
tails
id
en
tify
in
g
an
o
p
tim
al
s
o
lu
tio
n
th
at
s
atis
f
ies
p
ar
ticu
l
ar
co
n
s
tr
ain
ts
wh
ile
m
in
im
izin
g
o
r
m
a
x
im
izin
g
th
e
o
b
jectiv
e
f
u
n
ctio
n
[
4
]
−
[
7
]
.
T
h
e
s
et
co
v
er
in
g
p
r
o
b
lem
(
S
C
P)
is
a
p
r
o
g
r
am
m
in
g
ap
p
r
o
ac
h
d
esig
n
ed
t
o
m
in
im
ize
th
e
n
u
m
b
e
r
o
f
s
er
v
ice
f
ac
ilit
y
s
ites
wh
ile
en
s
u
r
in
g
co
v
er
ag
e
o
f
all
d
em
a
n
d
p
o
in
ts
[
8
]
−
[
1
0
]
.
SC
P
ap
p
licatio
n
s
in
d
a
ily
life
en
c
o
m
p
ass
task
allo
ca
tio
n
to
m
ac
h
in
es,
wo
r
k
f
o
r
ce
ass
ig
n
m
en
t,
a
n
d
o
p
tim
izin
g
waste
co
llectio
n
r
o
u
tes
to
r
e
d
u
ce
ex
p
en
s
es
an
d
co
m
p
letio
n
d
u
r
atio
n
[
1
1
]
−
[
1
6
]
.
T
h
e
SC
P
m
o
d
el
co
m
p
r
is
es
s
ev
er
al
in
t
er
co
n
n
ec
ted
m
o
d
els,
in
clu
d
in
g
th
e
s
et
co
v
e
r
in
g
lo
ca
tio
n
p
r
o
b
lem
(
SC
L
P)
an
d
th
e
p
-
M
ed
ian
p
r
o
b
le
m
[
1
7
]
.
T
h
e
SC
L
P
aim
s
to
d
eter
m
in
e
th
e
o
p
tim
al
n
u
m
b
er
o
f
f
ac
ilit
ies
av
ailab
le
f
o
r
p
lac
em
en
t
[
1
8
]
,
wh
ile
th
e
p
-
M
ed
ia
n
p
r
o
b
lem
s
ee
k
s
to
m
in
im
ize
th
e
to
tal
d
is
tan
ce
,
tr
av
el
tim
e,
o
r
co
s
t
b
etwe
en
ea
c
h
r
e
q
u
est
an
d
th
e
n
ea
r
est
f
ac
il
ity
b
y
d
eter
m
in
in
g
th
e
lo
ca
tio
n
o
f
f
ac
ilit
ies,
en
ab
lin
g
o
p
tim
al
ch
o
ices
[
1
9
]
.
T
h
e
SC
P
m
o
d
el
h
as
led
to
th
e
d
ev
elo
p
m
en
t
o
f
th
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el,
wh
ich
is
f
am
o
u
s
f
o
r
s
o
l
v
in
g
c
o
m
p
lex
p
r
o
b
lem
s
s
u
c
h
as
s
to
ch
asti
c
an
d
n
o
n
lin
ea
r
p
r
o
g
r
am
m
in
g
p
r
o
b
l
em
s
[
2
0
]
.
I
t
is
o
n
e
o
f
th
e
m
o
s
t
in
f
lu
en
tial
an
d
s
tan
d
ar
d
m
o
d
els
f
o
r
h
a
n
d
lin
g
s
izab
le
m
ix
ed
in
teg
e
r
p
r
o
b
le
m
s
(
MI
P).
T
h
e
o
r
ig
i
n
al
p
r
o
b
l
em
is
r
ef
o
r
m
u
lated
in
t
o
two
p
r
o
b
lem
s
with
f
ewe
r
v
ar
iab
les:
th
e
m
aster
p
r
o
b
lem
(
MP)
an
d
th
e
s
u
b
p
r
o
b
lem
(
SP
)
[
2
1
]
.
T
h
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
is
u
s
ed
to
f
in
d
b
o
th
t
h
e
f
ea
s
ib
le
s
o
lu
tio
n
an
d
th
e
lo
wer
b
o
u
n
d
o
f
th
e
p
r
o
b
lem
.
T
h
e
lo
wer
b
o
u
n
d
is
th
en
u
s
ed
to
f
in
d
a
f
ea
s
ib
le
s
o
lu
tio
n
[
2
2
]
.
Sev
er
al
p
r
e
v
io
u
s
s
tu
d
ies
h
av
e
b
ee
n
co
n
d
u
cted
o
n
lo
ca
tio
n
d
eter
m
i
n
atio
n
u
s
in
g
SC
P
[
1
1
]
,
[
1
5
]
,
[
2
3
]
−
[
2
9
]
.
Octa
r
in
a
et
a
l.
[
2
5
]
d
eter
m
in
ed
th
e
lo
ca
tio
n
o
f
T
W
DS
in
B
u
k
it
Kec
il
Su
b
d
is
tr
i
ct
b
y
m
o
d
ellin
g
th
e
R
o
b
u
s
t
-
SC
P
an
d
an
aly
ze
d
th
e
o
p
tim
al
s
o
lu
tio
n
s
b
y
u
s
in
g
s
en
s
itiv
ity
an
alis
is
.
T
h
e
r
es
u
lt
s
h
o
wed
th
at
th
e
s
o
lu
tio
n
r
em
ain
s
o
p
tim
al
if
t
h
e
co
ef
f
icien
t
c
h
an
g
e
is
with
in
th
e
co
ef
f
icien
t
in
ter
v
al
v
alu
e.
R
esear
ch
h
as
alr
ea
d
y
b
ee
n
c
o
n
d
u
cted
t
o
d
et
er
m
in
e
th
e
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
[
2
6
]
.
Octa
r
i
n
a
et
a
l.
[
2
6
]
f
o
u
n
d
o
n
ly
s
ix
o
p
tim
al
T
W
DS
in
t
h
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
b
y
u
s
in
g
g
r
ee
d
y
r
e
d
u
ctio
n
alg
o
r
it
h
m
.
T
h
e
n
u
m
b
er
o
f
T
W
DS
o
b
tain
ed
is
m
in
im
al,
with
ea
ch
v
illag
e
p
o
s
s
ess
in
g
o
n
ly
a
s
in
g
le
o
p
tim
al
T
W
DS.
T
h
e
n
o
v
elty
o
f
th
is
r
esear
ch
lies
in
th
e
u
p
d
ate
d
n
u
m
b
er
o
f
T
W
DS
an
d
th
e
d
ev
elo
p
m
en
t
o
f
th
e
SC
P
m
o
d
el,
s
p
ec
if
ically
th
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
e
l.
DE
H
ca
n
co
n
s
id
er
th
is
s
o
lu
t
io
n
to
d
eter
m
in
e
th
e
lo
ca
tio
n
o
f
s
tr
ateg
ic
T
W
DS.
B
ased
o
n
th
e
s
tu
d
ies
m
en
tio
n
ed
ab
o
v
e,
r
esear
ch
er
s
d
eter
m
in
ed
th
e
s
tr
ateg
ic
lo
ca
tio
n
f
o
r
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
u
s
in
g
th
e
SC
P
m
o
d
el
f
o
r
m
u
latio
n
,
n
am
ely
SC
L
P
an
d
p
-
Me
d
ian
p
r
o
b
lem
,
a
n
d
f
o
r
m
u
lated
t
h
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el.
All
m
o
d
els
wer
e
s
o
lv
ed
u
s
in
g
th
e
g
e
n
er
al
alg
eb
r
aic
m
o
d
elin
g
s
y
s
tem
(
GAM
S)
s
o
f
twar
e.
2.
M
E
T
H
O
DS
T
h
e
r
esear
ch
p
r
o
ce
s
s
in
v
o
lv
es
s
o
m
e
s
tep
s
.
F
ir
s
tly
,
th
e
n
am
es
o
f
T
W
DS
in
th
e
Su
k
ar
am
i
S
u
b
d
is
tr
ict
f
r
o
m
DE
H
Palem
b
an
g
C
ity
will
b
e
co
llected
an
d
p
r
esen
t
ed
as
d
ata
tab
les.
T
h
en
,
d
ete
r
m
in
e
v
ar
iab
les
an
d
p
ar
am
eter
s
f
o
r
th
e
SC
L
P,
p
-
Me
d
ian
p
r
o
b
lem
,
an
d
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
s
in
th
e
Su
k
ar
a
m
i
Su
b
d
is
tr
ict
.
Me
asu
r
e
th
e
d
is
tan
ce
b
etwe
en
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
u
s
in
g
Go
o
g
le
Ma
p
s
.
T
h
e
d
ata,
v
ar
iab
les,
an
d
p
ar
am
eter
s
wer
e
u
s
ed
to
f
o
r
m
u
late
th
e
SC
P
m
o
d
el,
n
am
ely
SC
L
P.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
o
f
SC
L
P
wa
s
f
o
r
m
ed
b
ased
o
n
th
e
n
u
m
b
e
r
o
f
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
,
an
d
th
e
co
n
s
tr
ain
ts
wer
e
d
eter
m
in
ed
b
y
th
e
d
is
tan
ce
b
e
twee
n
T
W
DS,
wh
ich
was
lim
i
ted
to
5
0
0
m
etr
es.
T
h
e
p
-
M
ed
ian
p
r
o
b
lem
m
o
d
el
was
f
o
r
m
u
lated
b
ased
o
n
th
e
o
p
tim
al
s
o
lu
tio
n
s
o
f
th
e
SC
L
P
m
o
d
el.
T
h
e
o
b
jectiv
e
f
u
n
cti
o
n
o
f
th
e
p
-
M
ed
ian
p
r
o
b
lem
m
o
d
el
was
b
ased
o
n
th
e
d
is
tan
ce
b
etwe
en
v
illa
g
es
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
,
an
d
th
e
T
W
DS
f
ac
ilit
ies
wer
e
o
b
tain
ed
f
r
o
m
th
e
SC
L
P
r
esu
lts
.
T
h
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
is
also
f
o
r
m
u
lated
to
s
o
lv
e
th
e
SC
P.
T
h
e
s
tep
s
tak
en
in
th
e
B
en
d
e
r
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
f
o
r
m
u
latio
n
is
as f
o
l
lo
ws:
−
C
o
n
s
id
er
a
p
r
im
al
p
r
o
b
lem
w
h
er
e
v
ar
iab
le
is
th
e
p
r
o
b
lem
v
a
r
iab
le
(
MP)
.
Min
im
ize
=
+
(
1
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
2
,
Feb
r
u
a
r
y
20
26
:
6
6
6
-
6
7
9
668
s
u
b
ject
to
:
+
≤
(
2
)
≤
(
3
)
,
∈
{
0
,
1
}
(
4
)
ass
u
m
e
th
e
v
ar
iab
le
is
f
ix
ed
(
=
̅
)
,
with
:
: o
b
jectiv
e
f
u
n
ctio
n
: r
o
w
v
ec
to
r
with
elem
en
t
: r
o
w
v
ec
to
r
with
elem
en
t
: m
atr
ix
o
f
s
ize
×
: m
atr
ix
o
f
s
ize
×
: r
ig
h
t h
an
d
s
id
e
o
f
th
e
co
n
s
tr
ain
t (
co
lu
m
n
v
ec
to
r
o
f
co
n
s
tan
t)
: c
o
lu
m
n
v
ec
to
r
o
f
co
n
tin
u
e
v
ar
iab
le
: c
o
lu
m
n
v
ec
to
r
o
f
in
teg
er
v
ar
i
ab
le
: n
u
m
b
er
o
f
i
n
teg
er
v
a
r
iab
les
: r
ig
h
t h
an
d
s
id
e
o
f
co
n
s
tr
ain
ts
: m
atr
ix
o
f
v
ar
iab
les th
at
will b
e
f
ix
ed
−
T
h
e
p
r
im
al
p
r
o
b
lem
ca
n
b
e
tr
a
n
s
f
o
r
m
ed
t
o
SP
as f
o
llo
ws
:
Min
im
ize
=
+
̅
(
5
)
s
u
b
ject
to
:
≤
−
̅
(
6
)
∈
ℝ
(
7
)
−
T
h
e
dua
l
SP
f
o
r
m
is
s
o
lv
ed
b
ec
au
s
e
its
s
o
lu
tio
n
d
o
es
n
o
t
d
ep
en
d
o
n
th
e
v
ar
iab
le
an
d
is
eq
u
al
to
SP
.
T
h
e
f
o
r
m
o
f
th
e
d
u
al
SP
is
as f
o
llo
ws:
Ma
x
im
ize
(
−
̅
)
(
8
)
s
u
b
ject
to
:
≤
(
9
)
∈
ℝ
(1
0
)
with
is
a
s
o
lu
tio
n
o
f
d
u
al
SP
.
−
T
h
e
o
p
tim
al
v
alu
e
o
f
th
e
d
u
al
SP
is
f
in
ite
if
th
e
v
alu
e
o
f
o
b
tain
ed
f
r
o
m
th
e
p
r
ev
io
u
s
MP
is
f
lex
ib
le
f
o
r
SP
.
T
h
is
s
o
lu
tio
n
lead
s
to
an
e
x
tr
em
e
p
o
in
t
in
t
h
e
s
o
lu
tio
n
o
f
th
e
d
u
al
SP
wh
ich
is
eq
u
al
t
o
th
e
o
p
tim
ality
cu
t.
T
h
e
o
p
tim
ality
cu
t is th
en
ad
d
ed
to
th
e
MP.
̅
(
−
)
+
−
≤
0
∀
=
1
,
…
.
,
(
11
)
−
C
o
n
v
er
s
ely
,
s
u
p
p
o
s
e
is
in
f
ea
s
ib
le,
an
d
th
e
d
u
al
SP
d
o
es
n
o
t
r
ea
ch
a
f
ea
s
ib
le
s
o
lu
tio
n
th
r
o
u
g
h
t
h
e
g
i
v
en
v
ar
iab
le
.
I
n
t
h
at
ca
s
e,
th
e
d
u
a
l
SP
s
h
o
u
ld
b
e
r
estricte
d
b
y
th
e
f
ea
s
ib
ilit
y
cu
t
an
d
s
h
o
u
ld
b
e
ad
d
ed
to
MP
as f
o
llo
ws:
̅
(
−
)
≤
0
∀
=
1
,
…
.
,
(
12
)
w
h
er
e
̅
is
ex
tr
im
v
ec
to
r
o
f
d
u
al
SP
.
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:
2
5
0
2
-
4
7
52
Th
e
B
en
d
er
’
s
d
ec
o
mp
o
s
itio
n
mo
d
el
to
o
p
timiz
e
temp
o
r
a
r
y
w
a
s
te
d
is
p
o
s
a
l sit
e
s
b
a
s
ed
o
n
…
(
S
is
ca
Octa
r
in
a
)
669
−
I
n
th
e
co
n
tex
t
o
f
th
is
s
tu
d
y
,
it
is
im
p
o
r
tan
t
to
n
o
te
th
at,
in
e
ac
h
iter
atio
n
,
o
n
ly
o
n
e
o
p
tim
a
lity
cu
t
an
d
o
n
e
f
ea
s
ib
ilit
y
cu
t
b
ec
o
m
e
ac
tiv
e.
Giv
en
th
is
,
th
e
f
o
llo
win
g
f
o
r
m
u
latio
n
is
u
s
ed
to
d
e
f
in
e
th
e
M
P:
Min
im
ize
(
13
)
s
u
b
ject
to
:
≤
(
14
)
̅
(
−
)
+
−
≤
0
,
∀
=
1
,
…
,
(1
5
)
̅
(
−
)
≤
0
,
∀
=
1
,
…
,
(
1
6
)
∈
ℝ
,
∈
ℤ
(
1
7
)
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
ch
ap
ter
d
is
cu
s
s
es
th
e
d
ata
u
s
ed
in
th
e
s
tu
d
y
,
th
e
d
eter
m
in
atio
n
o
f
th
e
n
u
m
b
er
an
d
lo
ca
tio
n
o
f
T
W
DS
in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
,
Palem
b
an
g
C
ity
,
th
e
f
o
r
m
u
latio
n
o
f
th
e
SC
P
m
o
d
el
,
n
am
ely
th
e
SC
L
P
m
o
d
el,
t
h
e
p
-
m
ed
ian
p
r
o
b
lem
m
o
d
el,
an
d
th
e
f
o
r
m
u
latio
n
o
f
th
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
in
s
o
lv
in
g
SC
P.
T
h
er
e
ar
e
2
9
T
W
D
S
i
n
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
s
p
r
ea
d
ac
r
o
s
s
5
v
illag
es:
Su
k
ab
an
g
u
n
,
Su
k
ar
am
i,
Keb
u
n
B
u
n
g
a,
T
alan
g
Kela
p
a,
an
d
Su
k
ajay
a.
Villag
es
an
d
T
W
DS
in
th
e
Su
k
a
r
am
i
Su
b
d
is
tr
ict
ar
e
f
u
r
th
er
d
ef
in
ed
u
s
in
g
v
ar
ia
b
les,
as sh
o
wn
in
T
ab
le
1
an
d
T
ab
le
2
.
T
ab
le
1
.
Var
iab
les d
e
f
in
itio
n
o
f
v
illag
es in
th
e
Su
k
a
r
am
i
Su
b
d
is
tr
ict
V
a
r
i
a
b
l
e
D
e
f
i
n
i
t
i
o
n
o
f
v
a
r
i
a
b
l
e
1
S
u
k
a
b
a
n
g
u
n
V
i
l
l
a
g
e
2
S
u
k
a
r
a
mi
V
i
l
l
a
g
e
3
K
e
b
u
n
B
u
n
g
a
V
i
l
l
a
g
e
4
Ta
l
a
n
g
J
a
mb
e
V
i
l
l
a
g
e
5
S
u
k
a
j
a
y
a
V
i
l
l
a
g
e
6
S
u
k
o
d
a
d
i
V
i
l
l
a
g
e
7
Ta
l
a
n
g
B
e
t
u
t
u
V
i
l
l
a
g
e
T
ab
le
2
.
Var
iab
les d
e
f
in
itio
n
o
f
T
W
DS in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
V
a
r
i
a
b
l
e
D
e
f
i
n
i
t
i
o
n
o
f
v
a
r
i
a
b
l
e
V
a
r
i
a
b
l
e
D
e
f
i
n
i
t
i
o
n
o
f
v
a
r
i
a
b
l
e
1
TWD
S
K
M
5
M
a
r
k
e
t
(
P
a
l
i
m
o
)
B
a
s
e
m
e
n
t
15
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
K
e
b
u
n
B
u
n
g
a
R
o
a
d
I
n
t
e
r
sec
t
i
o
n
2
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
i
n
f
r
o
n
t
o
f
K
M
5
m
o
t
o
r
b
i
k
e
w
o
r
k
s
h
o
p
16
TWD
S
Lu
b
u
k
K
a
w
a
h
S
t
r
e
e
t
b
e
h
i
n
d
A
u
t
o
2
0
0
0
TA
A
3
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
i
n
f
r
o
n
t
o
f
EX
I
n
d
a
h
S
a
r
i
17
TWD
S
I
l
l
e
g
a
l
P
e
r
j
u
a
n
g
a
n
S
t
r
e
e
t
4
TWD
S
S
u
k
a
b
a
n
g
u
n
1
S
t
r
e
e
t
(
C
h
i
n
e
se
G
r
a
v
e
)
18
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
N
e
w
H
a
j
j
D
o
r
mi
t
o
r
y
5
TWD
S
S
u
k
a
b
a
n
g
u
n
2
S
t
r
e
e
t
(
C
h
i
n
e
se
G
r
a
v
e
)
19
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
i
n
f
r
o
n
t
o
f
M
o
s
q
u
e
6
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
S
u
k
a
maj
u
R
o
a
d
I
n
t
e
r
se
c
t
i
o
n
20
TWD
S
o
p
p
o
s
i
t
e
S
e
d
e
r
h
a
n
a
8
8
TA
A
R
e
st
a
u
r
a
n
t
7
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
b
e
s
i
d
e
D
E
P
r
e
mi
u
m H
o
t
e
l
21
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
Ta
l
a
n
g
K
e
d
o
n
d
o
n
g
8
TWD
S
N
a
sk
a
h
S
t
r
e
e
t
22
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
H
o
n
d
a
D
e
a
l
e
r
9
TWD
S
B
a
t
u
Ja
j
a
r
S
t
r
e
e
t
23
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
A
u
t
o
2
0
0
0
TA
A
10
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
b
e
s
i
d
e
D
h
a
r
ma
A
g
u
n
g
H
o
t
e
l
La
n
e
24
TWD
S
B
a
mb
u
K
u
n
i
n
g
S
t
r
e
e
t
11
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
S
M
P
N
4
0
P
a
l
e
m
b
a
n
g
I
n
t
e
r
s
e
c
t
i
o
n
25
TWD
S
Ta
l
a
n
g
Jam
b
e
S
t
r
e
e
t
12
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
i
n
f
r
o
n
t
o
f
M
i
t
r
a
B
a
n
g
u
n
a
n
b
u
s st
o
p
26
TWD
S
S
u
k
a
w
i
n
a
t
a
n
M
a
r
k
e
t
13
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
b
e
s
i
d
e
Tr
a
k
i
n
d
o
L
a
n
e
27
TWD
S
B
i
ma
La
n
e
14
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
P
e
r
i
n
d
u
s
t
r
i
a
n
R
o
a
d
I
n
t
e
r
sec
t
i
o
n
(
K
e
b
u
n
B
u
n
g
a
A
b
u
s s
t
o
p
)
28
TWD
S
G
o
t
o
n
g
R
o
y
o
n
g
I
V
S
t
r
e
e
t
29
TWD
S
Ta
l
a
n
g
K
e
r
i
k
i
l
G
r
a
v
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
2
,
Feb
r
u
a
r
y
20
26
:
6
6
6
-
6
7
9
670
3
.
1
.
F
o
rm
ula
t
i
o
n o
f
t
he
SCL
P
m
o
del
B
y
u
s
in
g
th
e
d
is
tan
ce
d
ata
b
e
twee
n
ea
ch
T
W
DS,
v
ar
iab
les
in
T
ab
le
1
an
d
T
a
b
le
2
,
th
e
n
ex
t
s
tep
is
f
o
r
m
u
latin
g
th
e
SC
L
P m
o
d
el.
T
h
e
f
o
r
m
u
latio
n
o
f
th
e
SC
L
P m
o
d
el
is
as f
o
llo
ws:
Min
im
ize
=
∑
29
=
1
(
18
)
s
u
b
ject
to
:
1
+
2
≥
1
(
19
)
3
+
6
≥
1
(
20
)
4
≥
1
(
21
)
5
≥
1
(
22
)
3
+
6
+
7
≥
1
(
23
)
6
+
7
≥
1
(
24
)
8
+
10
≥
1
(
25
)
9
≥
1
(
26
)
8
+
10
+
11
≥
1
(
27
)
10
+
11
+
12
≥
1
(
28
)
11
+
12
≥
1
(
29
)
13
≥
1
(
30
)
14
+
15
+
17
≥
1
(
31
)
16
≥
1
(
32
)
18
+
19
≥
1
(
33
)
18
+
19
+
20
≥
1
(
34
)
19
+
20
≥
1
(
35
)
21
≥
1
(
36
)
22
+
23
≥
1
(
37
)
24
≥
1
(
38
)
25
≥
1
(
39
)
26
≥
1
(
40
)
27
≥
1
(
41
)
28
≥
1
(
42
)
29
≥
1
(
43
)
∈
{
0
,
1
}
,
=
1
,
2
,
…
,
29
(
44
)
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:
2
5
0
2
-
4
7
52
Th
e
B
en
d
er
’
s
d
ec
o
mp
o
s
itio
n
mo
d
el
to
o
p
timiz
e
temp
o
r
a
r
y
w
a
s
te
d
is
p
o
s
a
l sit
e
s
b
a
s
ed
o
n
…
(
S
is
ca
Octa
r
in
a
)
671
T
h
e
o
p
tim
al
s
o
lu
tio
n
an
d
v
ar
i
ab
les f
o
r
th
e
SC
L
P m
o
d
el
o
f
Su
k
ar
am
i
Su
b
d
is
tr
ict
u
s
in
g
GAM
S c
an
b
e
s
ee
n
in
T
ab
le
3.
Fro
m
T
ab
le
3
,
it
ca
n
b
e
s
ee
n
in
m
o
d
el
s
tat
is
tics
th
at
b
lo
ck
r
ef
er
s
to
th
e
G
AM
S
eq
u
atio
n
s
an
d
v
ar
iab
les,
n
am
ely
b
lo
c
k
o
f
eq
u
atio
n
s
o
f
2
6
an
d
b
lo
ck
o
f
v
a
r
iab
les
o
f
3
0
.
T
h
e
n
u
m
b
e
r
o
f
s
in
g
les
r
ef
er
s
to
th
e
r
o
ws
an
d
co
lu
m
n
s
in
th
e
g
en
er
ated
p
r
o
b
lem
,
n
am
ely
2
6
a
n
d
3
0
.
No
n
-
ze
r
o
elem
e
n
ts
r
ef
er
to
th
e
n
u
m
b
er
o
f
non
-
ze
r
o
co
ef
f
icien
ts
in
th
e
m
atr
ix
.
Gen
er
atio
n
tim
e
is
th
e
tim
e
tak
en
s
in
ce
th
e
s
y
n
tax
ch
e
ck
was
co
m
p
leted
,
wh
ich
is
0
.
0
3
1
s
ec
o
n
d
s
.
T
a
b
l
e
3
d
escr
ib
es
th
e
o
p
tim
al
s
o
l
u
tio
n
o
f
1
9
,
wh
ich
ca
n
b
e
s
e
en
in
th
e
o
b
jectiv
e
v
alu
e
with
th
e
tim
e
r
eq
u
ir
ed
b
y
th
e
s
o
f
twar
e,
wh
ich
is
0
.
0
1
5
s
ec
o
n
d
s
,
an
d
th
e
n
u
m
b
e
r
o
f
iter
atio
n
s
u
s
ed
b
y
th
e
s
o
lv
er
,
wh
ich
is
7
,
with
a
l
im
it
o
f
2
,
0
0
0
,
0
0
0
,
0
0
0
.
B
ased
o
n
T
a
b
le
3
,
th
e
o
p
tim
al
T
W
DS
s
h
o
u
ld
b
e
lo
ca
ted
at
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
in
f
r
o
n
t
o
f
KM
5
m
o
to
r
b
ik
e
wo
r
k
s
h
o
p
,
T
W
DS
Su
k
ab
an
g
u
n
1
Stre
et
(
C
h
in
ese
Gr
av
e)
,
T
W
DS
Su
k
ab
an
g
u
n
2
Stre
et
(
C
h
in
ese
Gr
av
e)
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
Su
k
am
aju
R
o
ad
I
n
ter
s
ec
tio
n
,
T
W
DS
Nask
ah
Stre
et,
T
W
DS
B
atu
J
ajar
Stre
et,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
in
f
r
o
n
t
o
f
Mitr
a
B
an
g
u
n
a
n
b
u
s
s
to
p
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Str
ee
t
b
esid
e
T
r
ak
in
d
o
L
an
e,
T
W
DS
L
u
b
u
k
Kaw
ah
B
elak
an
g
Stre
et
b
e
h
in
d
A
u
to
2
0
0
0
T
AA,
T
W
DS
I
lleg
al
Per
ju
an
g
an
Stre
et,
T
W
DS
L
etjen
Har
u
n
So
h
ar
Stre
et
in
f
r
o
n
t
o
f
Mo
s
q
u
e,
T
W
DS
L
etjen
Har
u
n
So
h
ar
Stre
et
T
ala
n
g
Ked
o
n
d
o
n
g
,
T
W
DS
L
etjen
Har
u
n
So
h
ar
Au
to
2
0
0
0
T
AA,
T
W
DS
B
am
b
u
K
u
n
in
g
Stre
et,
T
W
DS
T
alan
g
J
am
b
e
Stre
et,
T
W
DS
Su
k
awin
atan
Ma
r
k
et,
T
W
DS
B
im
a
L
an
e,
T
W
DS G
o
to
n
g
R
o
y
o
n
g
I
V
Stre
et,
an
d
T
W
DS T
alan
g
Ker
ik
il Gr
av
e.
T
ab
le
3.
Op
tim
al
s
o
lu
tio
n
o
f
t
h
e
SC
L
P
m
o
d
el
u
s
in
g
GAM
S
M
o
d
e
l
s
t
a
t
i
s
t
i
c
s
B
l
o
c
k
o
f
e
q
u
a
t
i
o
n
s
26
B
l
o
c
k
o
f
v
a
r
i
a
b
l
e
s
30
N
o
n
z
e
r
o
e
l
e
me
n
t
s
73
S
i
n
g
l
e
e
q
u
a
t
i
o
n
s
26
S
i
n
g
l
e
v
a
r
i
a
b
l
e
s
30
G
e
n
e
r
a
t
i
o
n
t
i
m
e
0
.
0
3
1
S
e
c
o
n
d
s
Ex
e
c
u
t
i
o
n
t
i
m
e
0
.
0
3
1
S
e
c
o
n
d
s
S
o
l
v
e
su
mm
a
r
y
S
o
l
v
e
r
s
t
a
t
u
s
1
n
o
r
m
a
l
c
o
mp
l
e
t
i
o
n
M
o
d
e
l
s
t
a
t
u
s
1
o
p
t
i
m
a
l
O
b
j
e
c
t
i
v
e
v
a
l
u
e
1
9
.
0
0
0
0
R
e
s
o
u
r
c
e
u
sa
g
e
,
l
i
m
i
t
0
.
0
1
5
1
0
0
0
.
0
0
0
I
t
e
r
a
t
i
o
n
c
o
u
n
t
,
l
i
m
i
t
7
2
0
0
0
0
0
0
0
0
0
3
.
2
.
F
o
rm
ula
t
i
o
n o
f
t
he
p
-
media
n pro
blem
T
h
e
p
-
m
e
d
ian
p
r
o
b
lem
m
o
d
el
u
s
ed
d
ata
f
r
o
m
th
e
lo
ca
tio
n
o
f
T
W
DS
an
d
d
em
a
n
d
in
t
h
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
.
T
h
e
lo
ca
tio
n
o
f
th
e
f
ac
ilit
ies
u
s
ed
was
o
b
tain
ed
f
r
o
m
s
o
lv
i
n
g
t
h
e
SC
L
P
m
o
d
el
an
d
d
en
o
te
d
b
y
,
wh
ile
r
ep
r
esen
ts
th
e
lo
ca
tio
n
o
f
th
e
v
illag
e
d
e
m
an
d
.
T
a
b
le
4
s
h
o
ws
th
e
d
is
tan
ce
b
et
wee
n
v
illag
es
an
d
o
p
tim
al
T
W
DS
o
b
tain
ed
f
r
o
m
th
e
r
esu
lts
o
f
s
o
lv
in
g
SC
L
P
u
s
in
g
GAM
S.
B
y
u
s
in
g
th
e
d
ata
in
T
ab
le
4
,
t
h
e
f
o
r
m
u
latio
n
o
f
t
h
e
p
-
m
ed
ian
p
r
o
b
lem
is
T
ab
le
4
.
Dis
tan
ce
b
etwe
en
v
illag
es a
n
d
T
W
DS in
th
e
Su
k
ar
a
m
i
Su
b
d
is
tr
ict
ac
co
r
d
in
g
to
S
C
L
P c
o
m
p
letio
n
2
4
5
6
8
9
12
13
16
17
19
1
1
0
0
0
5
0
0
2
7
0
0
2
0
0
0
2
8
0
0
5
2
0
0
4
1
0
0
4
7
0
0
4
6
0
0
5
9
0
0
6
3
0
0
2
3
1
0
0
3
2
0
0
4
9
0
0
1
9
0
0
1
6
0
0
1
6
0
0
5
0
0
1
1
0
0
5
3
0
0
2
3
0
0
2
8
0
0
3
4
8
0
0
4
9
0
0
7
3
0
0
3
6
0
0
3
1
0
0
2
0
0
0
2
2
0
0
1
5
0
0
1
4
0
0
2
1
0
0
1
8
0
0
4
1
0
0
0
0
1
0
0
0
0
7
3
0
0
8
8
0
0
1
0
0
0
0
7
3
0
0
7
4
0
0
6
7
0
0
3
7
0
0
6
1
0
0
5
8
0
0
5
1
8
0
0
9
0
0
2
0
0
0
9
5
0
2
0
0
0
3
7
0
0
2
6
0
0
3
2
0
0
3
2
0
0
4
4
0
0
4
8
0
0
6
7
1
0
0
7
1
0
0
8
8
0
0
5
8
0
0
7
0
0
0
4
3
0
0
4
4
0
0
3
8
0
0
5
9
0
0
3
1
0
0
3
4
0
0
7
1
2
0
0
0
1
3
0
0
0
9
9
0
0
1
1
0
0
0
1
2
0
0
0
9
7
0
0
9
9
0
0
9
2
0
0
6
2
0
0
8
5
0
0
8
8
0
0
21
23
24
25
26
27
28
29
1
7
2
0
0
5
5
0
0
7
4
0
0
8
0
0
0
3
6
0
0
3
3
0
0
3
8
0
0
4
1
0
0
2
3
6
0
0
4
8
0
0
6
2
0
0
6
8
0
0
5
8
0
0
5
5
0
0
6
0
0
0
6
3
0
0
3
1
5
0
0
2
0
0
0
3
4
0
0
4
0
0
0
6
7
0
0
7
1
0
0
7
1
0
0
8
0
0
0
4
4
3
0
0
3
2
0
0
2
8
0
0
1
5
0
0
6
7
0
0
7
1
0
0
7
2
0
0
8
0
0
0
5
5
7
0
0
4
1
0
0
6
0
0
0
6
6
0
0
2
8
0
0
2
6
0
0
3
1
0
0
3
3
0
0
6
4
3
0
0
5
5
0
0
6
9
0
0
7
4
0
0
1
0
0
0
0
1
1
0
0
0
1
1
0
0
0
1
1
0
0
0
7
6
8
0
0
5
8
0
0
5
3
0
0
4
1
0
0
9
3
0
0
9
7
0
0
9
7
0
0
1
1
0
0
0
Min
im
ize
−
=
1000
1
,
2
+
500
1
,
4
+
2700
1
,
5
+
2000
1
,
6
+
2800
1
,
8
+
5200
1
,
9
+
4100
1
,
12
+
4700
1
,
13
+
4600
1
,
16
+
5900
1
,
17
+
6300
1
,
19
+
7200
1
,
21
+
5500
1
,
23
+
7400
1
,
24
+
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
2
,
Feb
r
u
a
r
y
20
26
:
6
6
6
-
6
7
9
672
8000
1
,
25
+
3600
1
,
26
+
3300
1
,
27
+
3800
1
,
28
+
4100
1
,
29
+
3100
2
,
2
+
3200
2
,
4
+
4900
2
,
5
+
1900
2
,
6
+
1600
2
,
8
+
1600
2
,
9
+
500
2
,
12
+
1100
2
,
13
+
5300
2
,
16
+
2300
2
,
17
+
2800
2
,
19
+
3600
2
,
21
+
4800
2
,
23
+
6200
2
,
24
+
6800
2
,
25
+
5800
2
,
26
+
5500
2
,
27
+
6000
2
,
28
+
6300
2
,
29
+
4800
3
,
2
+
4900
3
,
4
+
7300
3
,
5
+
3600
3
,
6
+
3100
3
,
8
+
2000
3
,
9
+
2200
3
,
12
+
1500
3
,
13
+
1400
3
,
16
+
2100
3
,
17
+
1800
3
,
19
+
1500
3
,
21
+
2000
3
,
23
+
3400
3
,
24
+
4000
3
,
25
+
6700
3
,
26
+
7100
3
,
27
+
7100
3
,
28
+
8000
3
,
29
+
10000
4
,
2
+
10000
4
,
4
+
7300
4
,
5
+
8800
4
,
6
+
10000
4
,
8
+
7300
4
,
9
+
7400
4
,
12
+
6700
4
,
13
+
3700
4
,
16
+
6100
4
,
17
+
5800
4
,
19
+
4300
4
,
21
+
3200
4
,
23
+
2800
4
,
24
+
1500
4
,
25
+
6700
4
,
26
+
100
4
,
27
+
7200
4
,
28
+
8000
4
,
29
+
1800
5
,
2
+
900
5
,
4
+
2000
5
,
5
+
950
5
,
6
+
2000
5
,
8
+
3700
5
,
9
+
2600
5
,
12
+
3200
5
,
13
+
3200
5
,
16
+
4400
5
,
17
+
4800
5
,
19
+
5700
5
,
21
+
4100
5
,
23
+
6000
5
,
24
+
800
5
,
26
+
2600
5
,
27
+
3100
5
,
28
+
3300
5
,
29
+
7100
6
,
2
+
7100
6
,
4
+
8800
6
,
5
+
5800
6
,
6
+
7000
6
,
8
+
4300
6
,
9
+
4400
6
,
12
+
3800
6
,
13
+
5900
6
,
16
+
3100
6
,
17
+
3400
6
,
19
+
4300
6
,
21
+
5500
6
,
23
+
6900
6
,
24
+
7400
6
,
25
+
1000
6
,
26
+
11000
6
,
27
+
11000
6
,
28
+
11000
6
,
29
+
12000
7
,
2
+
13000
7
,
4
+
9900
7
,
5
+
11000
7
,
6
+
12000
7
,
8
+
9700
7
,
9
+
9900
7
,
12
+
9200
7
,
13
+
6200
7
,
16
+
8500
7
,
17
+
8800
7
,
19
+
6800
7
,
21
+
5800
7
,
23
+
5300
7
,
24
+
4100
7
,
25
+
9300
7
,
26
+
9700
7
,
27
+
9700
7
,
28
+
11000
7
,
29
(
45
)
s
u
b
ject
to
:
1
,
2
+
1
,
4
+
1
,
5
+
1
,
6
+
1
,
8
+
1
,
9
+
1
,
12
+
1
,
13
+
1
,
16
+
1
,
17
+
1
,
19
+
1
,
21
+
1
,
23
+
1
,
24
+
1
,
25
+
1
,
26
+
1
,
27
+
1
,
28
+
1
,
29
=
1
(
46
)
2
,
2
+
2
,
4
+
2
,
5
+
2
,
6
+
2
,
8
+
2
,
9
+
2
,
12
+
2
,
13
+
2
,
16
+
2
,
17
+
2
,
19
+
2
,
21
+
2
,
23
+
2
,
24
+
2
,
25
+
2
,
26
+
2
,
27
+
2
,
28
+
2
,
29
=
1
(
47
)
3
,
2
+
3
,
4
+
3
,
5
+
3
,
6
+
3
,
8
+
3
,
9
+
3
,
12
+
3
,
13
+
3
,
16
+
3
,
17
+
3
,
19
+
3
,
21
+
3
,
23
+
3
,
24
+
3
,
25
+
3
,
26
+
3
,
27
+
3
,
28
+
3
,
29
=
1
(
48
)
4
,
2
+
4
,
4
+
4
,
5
+
4
,
6
+
4
,
8
+
4
,
9
+
4
,
12
+
4
,
13
+
4
,
16
+
4
,
17
+
4
,
19
+
4
,
21
+
4
,
23
+
4
,
24
+
4
,
25
+
4
,
26
+
4
,
27
+
4
,
28
+
4
,
29
=
1
(
49
)
5
,
2
+
5
,
4
+
5
,
5
+
5
,
6
+
5
,
8
+
5
,
9
+
5
,
12
+
5
,
13
+
5
,
16
+
5
,
17
+
5
,
19
+
5
,
21
+
5
,
23
+
5
,
24
+
5
,
25
+
5
,
26
+
5
,
27
+
5
,
28
+
5
,
29
=
1
(
50
)
6
,
2
+
6
,
4
+
6
,
5
+
6
,
6
+
6
,
8
+
6
,
9
+
6
,
12
+
6
,
13
+
6
,
16
+
6
,
17
+
6
,
19
+
6
,
21
+
6
,
23
+
6
,
24
+
6
,
19
+
6
,
21
+
6
,
23
+
6
,
24
+
6
,
25
+
6
,
26
+
6
,
27
+
6
,
28
+
6
,
29
=
1
(
51
)
7
,
2
+
7
,
4
+
7
,
5
+
7
,
6
+
7
,
8
+
7
,
9
+
7
,
12
+
7
,
13
+
7
,
16
+
7
,
17
+
7
,
19
+
7
,
21
+
7
,
23
+
7
,
24
+
7
,
25
+
7
,
26
+
7
,
27
+
7
,
28
+
7
,
29
=
1
(
52
)
2
+
4
+
5
+
6
+
8
+
9
+
12
+
13
+
16
+
17
+
19
+
21
+
23
+
24
+
25
+
26
+
27
+
28
+
29
=
19
(
53
)
1
,
2
+
2
,
2
+
3
,
2
+
4
,
2
+
5
,
2
+
6
,
2
+
7
,
2
≤
2
(
54
)
1
,
4
+
2
,
4
+
3
,
4
+
4
,
4
+
5
,
4
+
6
,
4
+
7
,
4
≤
4
(
55
)
1
,
5
+
2
,
5
+
3
,
5
+
4
,
5
+
5
,
5
+
6
,
5
+
7
,
5
≤
5
(
56
)
1
,
6
+
2
,
6
+
3
,
6
+
4
,
6
+
5
,
6
+
6
,
6
+
7
,
6
≤
6
(
57
)
1
,
8
+
2
,
8
+
3
,
8
+
4
,
8
+
5
,
8
+
6
,
8
+
7
,
8
≤
8
(
58
)
1
,
9
+
2
,
9
+
3
,
9
+
4
,
9
+
5
,
9
+
6
,
9
+
7
,
9
≤
9
(
59
)
1
,
12
+
2
,
12
+
3
,
12
+
4
,
12
+
5
,
12
+
6
,
12
+
7
,
12
≤
12
(
60
)
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:
2
5
0
2
-
4
7
52
Th
e
B
en
d
er
’
s
d
ec
o
mp
o
s
itio
n
mo
d
el
to
o
p
timiz
e
temp
o
r
a
r
y
w
a
s
te
d
is
p
o
s
a
l sit
e
s
b
a
s
ed
o
n
…
(
S
is
ca
Octa
r
in
a
)
673
1
,
13
+
2
,
13
+
3
,
13
+
4
,
13
+
5
,
13
+
6
,
13
+
7
,
13
≤
13
(
61
)
1
,
16
+
2
,
16
+
3
,
16
+
4
,
16
+
5
,
16
+
6
,
16
+
7
,
16
≤
16
(
62
)
1
,
17
+
2
,
17
+
3
,
17
+
4
,
17
+
5
,
17
+
6
,
17
+
7
,
17
≤
17
(
63
)
1
,
19
+
2
,
19
+
3
,
19
+
4
,
19
+
5
,
19
+
6
,
19
+
7
,
19
≤
19
(
64
)
1
,
21
+
2
,
21
+
3
,
21
+
4
,
21
+
5
,
21
+
6
,
21
+
7
,
21
≤
21
(
65
)
1
,
23
+
2
,
23
+
3
,
23
+
4
,
23
+
5
,
23
+
6
,
23
+
7
,
23
≤
23
(
66
)
1
,
24
+
2
,
24
+
3
,
24
+
4
,
24
+
5
,
24
+
6
,
24
+
7
,
24
≤
24
(
67
)
1
,
25
+
2
,
25
+
3
,
25
+
4
,
25
+
5
,
25
+
6
,
25
+
7
,
25
≤
25
(
68
)
1
,
26
+
2
,
26
+
3
,
26
+
4
,
26
+
5
,
26
+
6
,
26
+
7
,
26
≤
26
(
69
)
1
,
27
+
2
,
27
+
3
,
27
+
4
,
27
+
5
,
27
+
6
,
27
+
7
,
27
≤
27
(
70
)
1
,
28
+
2
,
28
+
3
,
28
+
4
,
28
+
5
,
28
+
6
,
28
+
7
,
28
≤
28
(
71
)
1
,
29
+
2
,
29
+
3
,
29
+
4
,
29
+
5
,
29
+
6
,
29
+
7
,
29
≤
29
(
72
)
,
∈
{
0
,
1
}
,
=
1
,
2
,
…
,
7
a
n
d
=
2
,
4
,
5
,
6
,
8
,
9
,
12
,
13
,
16
,
17
,
19
,
21
,
23
,
24
,
25
,
26
,
27
,
28
,
29
(
73
)
∈
{
0
,
1
}
,
=
2
,
4
,
5
,
6
,
8
,
9
,
12
,
13
,
16
,
17
,
19
,
21
,
23
,
24
,
25
,
26
,
27
,
28
,
29
(
74
)
B
y
u
s
in
g
GAM
S,
t
h
e
o
p
tim
a
l
s
o
lu
tio
n
s
o
f
th
e
p
-
m
e
d
ian
p
r
o
b
lem
m
o
d
el
ar
e
:
t
h
e
d
em
an
d
in
t
h
e
Su
k
ab
an
g
u
n
v
illag
e
will
b
e
l
o
ca
ted
at
T
W
DS
Su
k
ab
an
g
u
n
1
Stre
et
(
C
h
in
ese
Gr
av
e
)
,
t
h
e
d
em
an
d
in
th
e
Su
k
ar
am
i
v
illag
e
will
b
e
lo
ca
t
ed
at
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
in
f
r
o
n
t
o
f
Mitr
a
B
an
g
u
n
an
b
u
s
s
to
p
,
t
h
e
d
em
an
d
in
th
e
Keb
u
n
B
u
n
g
a
v
illag
e
will
b
e
lo
ca
ted
at
T
W
DS
B
am
b
u
Ku
n
in
g
Stre
et
,
t
h
e
d
em
an
d
in
th
e
T
alan
g
J
am
b
e
v
illag
e
(
4
)
will
b
e
lo
ca
ted
at
T
W
DS
Go
to
n
g
R
o
y
o
n
g
I
V
Stre
et
,
t
h
e
d
em
a
n
d
i
n
th
e
Su
k
ajay
a
v
illag
e
will
b
e
lo
ca
ted
at
T
W
DS
Su
k
ab
an
g
u
n
1
Stre
et
(
C
h
in
ese
Gr
av
e)
,
t
h
e
d
em
an
d
in
t
h
e
Su
k
o
d
ad
i
v
illag
e
will
b
e
lo
ca
ted
at
T
W
DS
I
lleg
al
Per
ju
an
g
a
n
Stre
et
,
an
d
t
h
e
d
em
a
n
d
in
th
e
T
alan
g
B
e
tu
tu
v
illag
e
will
b
e
lo
ca
ted
at
T
W
DS Su
k
ab
an
g
u
n
2
Stre
et
(
C
h
in
ese
Gr
av
e)
.
3
.
3
.
B
ender
’
s
deco
m
po
s
it
io
n m
o
del in so
lv
ing
SCP
T
h
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el
u
s
es
d
ata
f
r
o
m
th
e
lo
ca
tio
n
o
f
T
W
DS
an
d
d
em
a
n
d
lo
ca
tio
n
s
in
Su
k
ar
am
i
Su
b
d
is
tr
ict
.
T
h
e
lo
c
atio
n
o
f
th
e
f
ac
ilit
ies
u
s
ed
is
th
e
lo
ca
tio
n
o
b
tain
e
d
f
r
o
m
s
o
lv
in
g
th
e
p
r
e
v
io
u
s
SC
L
P m
o
d
el.
Prim
al
SP
̂
=
∑
29
=
24
(
75
)
Min
im
ize
∑
+
̂
23
=
1
(
76
)
s
u
b
ject
to
:
co
n
s
tr
ain
ts
(
19
)
t
o
(
43
)
∈
{
0
,
1
}
,
=
1
,
2
,
…
,
23
(
77
)
∈
{
0
,
1
}
,
=
24
,
25
,
…
,
29
(
78
)
Du
al
SP
Ma
x
im
ize
∑
+
̂
23
=
1
(
79
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
2
,
Feb
r
u
a
r
y
20
26
:
6
6
6
-
6
7
9
674
s
u
b
ject
to
:
1
+
2
≤
1
(
80
)
3
+
6
≤
1
(
81
)
4
≤
1
(
82
)
5
≤
1
(
83
)
3
+
6
+
7
≤
1
(
84
)
6
+
7
≤
1
(
85
)
8
+
10
≤
1
(
86
)
9
≤
1
(
87
)
8
+
10
+
11
≤
1
(
88
)
10
+
11
+
12
≤
1
(
89
)
11
+
12
≤
1
(
90
)
13
≤
1
13
≤
1
(
91
)
14
+
15
+
17
≤
1
(
92
)
16
≤
1
(
93
)
18
+
19
≤
1
(
94
)
18
+
19
+
20
≤
1
(
95
)
19
+
20
≤
1
(
96
)
21
≤
1
(
97
)
22
+
23
≤
1
(
98
)
24
≤
1
(
99
)
25
≤
1
(
100
)
26
≤
1
(
101
)
27
≤
1
(
102
)
28
≤
1
(
103
)
29
≤
1
(
104
)
∈
{
0
,
1
}
,
=
1
,
2
,
…
,
23
(
105
)
∈
{
0
,
1
}
,
=
24
,
25
,
…
,
29
(
106
)
B
en
d
er
’
s
r
ef
o
r
m
u
latio
n
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:
2
5
0
2
-
4
7
52
Th
e
B
en
d
er
’
s
d
ec
o
mp
o
s
itio
n
mo
d
el
to
o
p
timiz
e
temp
o
r
a
r
y
w
a
s
te
d
is
p
o
s
a
l sit
e
s
b
a
s
ed
o
n
…
(
S
is
ca
Octa
r
in
a
)
675
Ma
x
im
ize
(
107
)
s
u
b
ject
to
:
≥
2
+
3
+
4
+
5
+
8
+
9
+
12
+
13
+
16
+
17
+
18
+
21
+
23
(
108
)
co
n
s
tr
ain
ts
(
80
)
t
o
(
1
0
6
)
.
T
h
e
o
p
tim
al
s
o
lu
tio
n
s
an
d
v
ar
iab
les
o
f
B
en
d
er
’
s
r
ef
o
r
m
u
latio
n
m
o
d
el
u
s
in
g
GAM
S
ar
e
T
W
DS
K
M
5
Ma
r
k
et
(
Palim
o
)
B
asem
en
t
,
T
W
DS
Su
k
ab
an
g
u
n
1
Stre
et
(
C
h
in
ese
Gr
av
e
)
,
T
W
DS
Su
k
ab
an
g
u
n
2
Stre
et
(
C
h
in
ese
Gr
av
e)
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
Su
k
am
aju
R
o
ad
I
n
ter
s
ec
tio
n
,
T
W
D
S
B
atu
J
ajar
Stre
et
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
b
esid
e
Dh
a
r
m
a
A
g
u
n
g
Ho
t
el
L
an
e
.
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Stre
et
SMPN
4
0
Palem
b
an
g
I
n
ter
s
ec
tio
n
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
b
esid
e
T
r
ak
in
d
o
L
an
e
,
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Per
in
d
u
s
tr
ian
R
o
ad
I
n
ter
s
ec
tio
n
(
Keb
u
n
B
u
n
g
a
A
b
u
s
s
to
p
)
,
T
W
DS
L
u
b
u
k
Kaw
ah
Stre
e
t
b
eh
in
d
Au
to
2
0
0
0
T
AA
,
T
W
DS
L
etjen
Har
u
n
So
h
ar
Stre
et
i
n
f
r
o
n
t
o
f
Mo
s
q
u
e
,
T
W
DS
L
etjen
Har
u
n
S
o
h
ar
Stre
et
T
alan
g
Ked
o
n
d
o
n
g
,
T
W
DS
L
etjen
H
ar
u
n
So
h
ar
Stre
et
Ho
n
d
a
Dea
l
er
,
T
W
DS
B
am
b
u
Ku
n
in
g
Stre
et
,
T
W
DS
T
alan
g
J
am
b
e
Stre
et
,
T
W
DS
Su
k
aw
in
atan
Ma
r
k
et
,
T
W
DS
B
im
a
L
an
e
,
T
W
DS
Go
to
n
g
R
o
y
o
n
g
I
V
,
an
d
T
W
DS
T
alan
g
Ker
ik
il
Gr
a
v
e.
T
h
e
f
in
al
r
esu
lts
o
f
th
e
SC
L
P,
p
-
Me
d
i
an
p
r
o
b
lem
,
a
n
d
B
en
d
e
r
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
els
u
s
in
g
GAM
S
y
ield
ed
a
v
ar
iet
y
o
f
o
p
tim
al
T
W
DS.
T
h
e
SC
L
P
an
d
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
els
y
ield
e
d
1
9
o
p
tim
al
lo
ca
tio
n
s
,
wh
ile
th
e
p
-
m
ed
ian
p
r
o
b
lem
m
o
d
el
y
ield
ed
7
o
p
tim
al
T
W
DS.
T
h
is
s
tu
d
y
’
s
f
in
d
in
g
s
ad
v
o
ca
te
f
o
r
im
p
lem
en
tin
g
th
e
s
o
lu
tio
n
d
er
iv
ed
f
r
o
m
th
e
B
en
d
er
’
s
d
ec
o
m
p
o
s
itio
n
m
o
d
el,
as
it c
an
ad
d
r
ess
th
e
co
m
p
r
eh
e
n
s
iv
e
ar
r
ay
o
f
d
em
an
d
s
p
r
esen
t
with
in
th
e
ad
m
in
is
tr
ativ
e
r
eg
io
n
o
f
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
.
T
h
e
o
p
tim
al
s
o
lu
tio
n
id
en
tifie
d
in
th
is
r
esear
ch
is
d
elin
ea
ted
in
T
ab
le
5
a
n
d
Fig
u
r
e
1
.
T
ab
le
5
.
Op
tim
al
T
W
DS in
th
e
Su
k
ar
am
i
Su
b
d
is
tr
ict
N
a
me
o
f
V
i
l
l
a
g
e
s
N
a
me
o
f
TWD
S
C
o
o
r
d
i
n
a
t
e
p
o
i
n
t
S
u
k
a
b
a
n
g
u
n
TWD
S
K
M
5
M
a
r
k
e
t
(
P
a
l
i
m
o
)
B
a
s
e
m
e
n
t
-
2
.
9
5
3
3
1
0
8
0
5
3
0
5
5
0
8
,
1
0
4
.
7
3
5
3
3
8
2
5
2
4
4
3
9
5
TWD
S
S
u
k
a
b
a
n
g
u
n
1
S
t
r
e
e
t
(
C
h
i
n
e
se
G
r
a
v
e
)
-
2
.
9
4
2
2
6
8
,
1
0
4
.
7
3
8
0
2
0
TWD
S
S
u
k
a
b
a
n
g
u
n
2
S
t
r
e
e
t
(
C
h
i
n
e
se
G
r
a
v
e
)
-
2
.
9
3
8
7
2
0
4
8
4
7
1
7
2
3
1
2
,
1
0
4
.
7
3
0
6
8
3
9
7
9
4
3
0
6
7
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
S
u
k
a
maj
u
R
o
a
d
I
n
t
e
r
sec
t
i
o
n
-
2
.
9
4
2
9
9
6
8
0
6
2
3
9
4
6
5
,
1
0
4
.
7
2
8
8
3
2
6
8
3
2
7
4
8
9
S
u
k
a
r
a
mi
TWD
S
B
a
t
u
Ja
j
a
r
S
t
r
e
e
t
-
2
.
9
2
7
0
1
2
,
1
0
4
.
7
3
2
4
1
5
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
b
e
s
i
d
e
D
h
a
r
m
a
A
g
u
n
g
H
o
t
e
l
L
a
n
e
-
2
.
9
3
8
2
0
9
0
1
3
5
8
1
9
8
6
,
1
0
4
.
7
2
0
9
4
4
7
4
2
1
5
6
3
9
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
S
t
r
e
e
t
S
M
P
N
4
0
P
a
l
e
m
b
a
n
g
I
n
t
e
r
sec
t
i
o
n
-
2
.
9
3
7
6
3
1
4
3
5
5
7
7
8
9
7
,
1
0
4
.
7
2
0
3
5
5
5
6
9
7
8
8
2
5
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
b
e
si
d
e
Tr
a
k
i
n
d
o
La
n
e
-
2
.
9
3
1
2
3
9
,
1
0
4
.
7
1
7
4
3
1
K
e
b
u
n
B
u
n
g
a
TWD
S
K
o
l
o
n
e
l
H
B
u
r
l
i
a
n
P
e
r
i
n
d
u
s
t
r
i
a
n
R
o
a
d
I
n
t
e
r
s
e
c
t
i
o
n
(
K
e
b
u
n
B
u
n
g
a
A
b
u
s
st
o
p
)
-
2
.
9
2
5
7
3
6
5
7
0
5
9
7
7
6
2
5
,
1
0
4
.
7
1
4
0
2
0
4
0
1
8
0
8
9
1
TWD
S
Lu
b
u
k
K
a
w
a
h
S
t
r
e
e
t
b
e
h
i
n
d
A
u
t
o
2
0
0
0
TA
A
-
2
.
9
0
8
0
3
2
,
1
0
4
.
7
2
4
5
3
8
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
i
n
f
r
o
n
t
o
f
M
o
s
q
u
e
-
2
.
9
1
7
5
9
9
,
1
0
4
.
7
1
1
9
0
9
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
Ta
l
a
n
g
K
e
d
o
n
d
o
n
g
-
2
.
9
0
9
7
6
0
7
2
2
0
0
2
0
0
8
7
,
1
0
4
.
7
1
4
9
1
2
3
9
4
7
7
2
5
7
TWD
S
Le
t
j
e
n
H
a
r
u
n
S
o
h
a
r
S
t
r
e
e
t
H
o
n
d
a
D
e
a
l
e
r
-
2
.
9
0
8
4
3
6
5
4
5
9
8
3
4
3
9
4
,
1
0
4
.
7
2
2
6
3
6
1
5
3
0
2
2
8
6
TWD
S
B
a
mb
u
K
u
n
i
n
g
S
t
r
e
e
t
-
2
.
8
9
8
7
1
4
4
4
2
2
3
3
9
9
3
4
,
1
0
4
.
7
2
5
8
4
5
1
6
4
7
1
1
6
9
Ta
l
a
n
g
J
a
mb
e
TWD
S
Ta
l
a
n
g
Jam
b
e
S
t
r
e
e
t
-
2
.
8
9
6
0
0
5
,
1
0
4
.
7
2
2
8
9
5
S
u
k
a
j
a
y
a
TWD
S
S
u
k
a
w
i
n
a
t
a
n
M
a
r
k
e
t
-
2
.
9
2
3
8
4
4
4
3
4
1
0
0
5
3
,
1
0
4
.
7
5
1
2
9
5
4
3
9
2
8
9
2
7
TWD
S
B
i
ma
La
n
e
-
2
.
9
2
9
1
2
2
9
1
9
3
9
4
1
2
2
6
,
1
0
4
.
7
5
0
8
3
6
2
3
2
7
7
7
5
4
TWD
S
G
o
t
o
n
g
R
o
y
o
n
g
I
V
-
2
.
9
1
4
4
6
2
6
5
5
3
5
2
1
7
9
5
,
1
0
4
.
7
3
8
1
8
6
4
2
6
4
2
6
2
5
TWD
S
Ta
l
a
n
g
K
e
r
i
k
i
l
G
r
a
v
e
-
2
.
9
3
4
1
0
0
6
4
9
6
6
8
7
8
8
,
1
0
4
.
7
5
4
5
8
3
3
3
6
3
3
8
8
Fig
u
r
e
1
s
h
o
ws
th
e
d
is
tr
ib
u
ti
o
n
o
f
o
p
tim
al
T
W
DS
in
f
iv
e
v
illag
es
in
th
e
Su
k
ar
a
m
i
Su
b
d
is
tr
ict
.
As
s
h
o
wn
in
Fig
u
r
e
1
,
Su
k
ab
an
g
u
n
v
illag
e
,
Su
k
ar
am
i
v
illa
g
e,
an
d
Su
k
ajay
a
v
illag
e
h
a
v
e
4
o
p
tim
al
T
W
D
S
ea
ch
.
Keb
u
n
B
u
n
g
a
n
v
illag
e
h
as
th
e
m
o
s
t
o
p
tim
al
T
W
D
S.
T
h
er
e
ar
e
6
T
W
DS
in
th
is
v
illag
e,
wh
ich
ar
e
T
W
DS
Ko
lo
n
el
H
B
u
r
lian
Per
in
d
u
s
tr
ian
R
o
ad
I
n
ter
s
ec
tio
n
(
Keb
u
n
B
u
n
g
a
A
b
u
s
s
to
p
)
,
T
W
DS
L
u
b
u
k
Kaw
ah
Stre
et
b
eh
in
d
A
u
to
2
0
0
0
T
A
A,
T
W
DS
L
etjen
Har
u
n
So
h
a
r
Stre
et
in
f
r
o
n
t
o
f
M
o
s
q
u
e,
T
W
DS
L
etjen
Har
u
n
So
h
ar
Stre
et
T
alan
g
Ked
o
n
d
o
n
g
,
T
W
DS
L
etjen
Har
in
So
h
ar
Stre
et
Ho
n
d
a
Dea
ler
,
a
n
d
.
T
W
DS
B
am
b
u
Ku
n
in
g
Stre
et.
T
alan
g
J
am
b
e
v
illag
e
h
as
o
n
ly
o
n
e
T
W
DS
n
am
ely
T
W
D
S
T
al
an
g
J
am
b
e
Stre
et.
T
h
e
d
is
tr
ib
u
tio
n
o
f
th
e
n
u
m
b
e
r
o
f
T
W
DS
r
em
ain
s
im
b
alan
c
ed
ac
r
o
s
s
all
v
illag
es.
T
h
is
r
e
s
ea
r
ch
s
u
g
g
ests
th
e
im
p
lem
en
tatio
n
o
f
a
d
d
itio
n
al
T
W
DS,
p
ar
ticu
lar
ly
i
n
T
ala
n
g
J
am
b
e
Villag
e,
wh
ich
cu
r
r
en
tly
h
as
o
n
ly
o
n
e
T
W
DS.
T
h
is
r
ec
o
m
m
en
d
atio
n
is
b
ased
o
n
th
e
o
b
s
er
v
atio
n
th
at
T
alan
g
J
am
b
e
Villag
e
is
co
m
p
ar
ativ
ely
lar
g
e
in
r
elatio
n
to
o
th
er
v
illag
es with
in
th
e
Su
k
ar
a
m
i
Su
b
d
is
tr
ict
.
Evaluation Warning : The document was created with Spire.PDF for Python.