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ng h
a
v
e
us
e
d t
h
e
m
e
t
a
h
e
u
r
i
s
t
i
c
a
l
g
or
i
t
hm
s
i
n t
h
e
i
r
opt
i
m
i
z
a
t
i
o
n
pr
oc
e
du
r
e
[
8]
.
A
l
t
h
ough
t
h
e
m
et
a
h
eu
r
i
s
t
i
c al
g
o
r
i
t
h
m
s
h
av
e
t
h
e
s
a
m
e co
n
cep
t
o
f
t
ak
i
n
g
t
h
ei
r
i
d
ea f
r
o
m
n
a
tu
r
e
,
t
h
e
s
e
a
l
g
o
r
ith
m
s
c
o
m
e
w
it
h
d
i
f
f
er
e
n
t
s
ear
ch
m
ec
h
an
i
s
m
s
[
9
]
,
an
d
v
ar
i
o
u
s
i
n
s
p
i
r
ed
s
o
u
r
ces
[
7
]
.
F
o
r
i
n
s
t
an
ce,
al
g
o
r
i
t
h
m
s
s
u
c
h
as
g
e
n
et
i
c
a
lg
o
r
ith
m
s
(
G
A
)
,
a
n
d
d
if
f
e
r
e
n
tia
l
e
v
o
l
u
tio
n
(
D
E
)
a
r
e
b
io
-
i
n
s
p
i
r
ed
b
as
ed
al
g
o
r
i
t
h
m
w
h
i
l
e p
ar
t
i
cl
e s
w
ar
m
o
p
tim
iz
at
i
o
n
(
P
S
O
)
,
A
n
t
C
o
l
o
n
y
O
p
t
i
m
i
za
t
i
o
n
(
A
C
O
)
,
an
d
cu
ck
o
o
s
ear
ch
(
C
S
)
ar
e s
w
ar
m
i
n
t
el
l
i
g
e
n
ce
-
b
as
ed
a
l
go
r
i
t
h
m
[
1
0
]
.
I
n
t
hi
s
s
t
ud
y,
w
e
ha
ve
c
ho
s
e
n
s
w
a
r
m
i
nt
e
l
l
i
ge
nc
e
a
l
go
r
i
t
h
m
s
t
o
d
e
a
l
w
i
t
h
hi
g
h d
i
m
e
n
s
i
o
na
l
opt
i
m
i
z
a
t
i
on
pr
obl
e
m
.
T
h
e
r
e
a
r
e
m
or
e
t
h
a
n
on
e
hu
n
dr
e
d
he
ur
i
s
t
i
c
a
l
go
r
i
t
h
m
s
a
nd
m
a
n
y o
f
t
he
m
c
o
ul
d
s
o
l
ve
di
f
f
e
r
e
n
t
t
y
pe
of
opt
i
m
i
z
a
t
i
on
pr
obl
e
m
s
e
f
f
e
c
t
i
v
e
l
y
[
5]
.
W
i
t
h
i
n t
h
e
h
ug
e
n
um
be
r
of
a
l
g
or
i
t
hm
s
s
e
l
e
c
t
i
ng
on
e
a
l
g
or
i
t
hm
a
m
o
n
g ot
h
e
r
s
t
o a
ppl
y
i
t
i
n
a
s
pe
c
i
f
i
c
do
m
a
i
n
t
o
s
ol
v
e
t
h
e
h
i
gh
di
m
e
n
s
i
on
a
l
pr
obl
e
m
i
s
n
ot
a
n
eas
i
l
y
acco
m
p
l
i
s
h
ed
t
as
k
.
F
o
r
t
h
at
,
t
h
e p
ap
er
ai
m
s
t
o
d
et
er
m
i
n
e t
h
e al
g
o
r
i
t
h
m
t
h
at
co
u
l
d
r
es
o
l
v
e t
h
e h
i
g
h
d
i
m
en
s
i
o
n
al
p
r
o
b
l
e
m
p
r
o
p
er
l
y
.
T
h
i
s
ar
t
i
cl
e i
s
f
o
cu
s
i
n
g
o
n
an
al
y
zi
n
g
,
an
d
co
m
p
ar
i
n
g
i
n
d
et
ai
l
s
p
ar
t
i
cl
e s
w
ar
m
opt
i
m
i
z
a
t
i
on (
P
S
O
)
a
n
d c
u
c
koo s
e
a
r
ch
(
C
S
)
i
n
r
es
p
ect
o
f
s
o
l
u
t
i
o
n
acc
u
r
ac
y
a
n
d
r
u
n
t
i
m
e p
er
f
o
r
m
an
ce
o
n
s
t
a
n
da
r
d
be
n
c
hm
a
r
k
f
un
c
t
i
ons
.
T
h
e
or
g
a
n
i
z
a
t
i
on
o
f
t
h
i
s
p
a
pe
r
i
s
s
h
o
w
n
a
s
f
ol
l
o
w
:
S
e
c
t
i
on
I
I
pr
ov
i
de
s
t
h
e
opt
i
m
i
z
a
t
i
on pr
obl
e
m
de
s
c
r
i
pt
i
on
.
S
e
c
t
i
o
n
I
I
I
s
h
o
w
s
a
r
e
vi
e
w
of
(
P
S
O
)
,
a
n
d (
C
S
)
.
T
h
e
s
t
a
n
da
r
d f
un
c
t
i
o
n
us
i
n
g i
n e
xp
e
r
i
m
e
nt
s
a
r
e
i
n
s
e
c
t
i
o
n I
V
,
w
hi
l
e
t
he
r
e
s
ul
t
s
a
nd
c
o
nc
l
u
s
i
o
n a
r
e
p
r
e
s
e
nt
e
d
i
n s
e
c
t
i
o
n V
a
nd
V
I
r
es
p
ect
i
v
el
y
.
2.
HI
G
H
DI
M
E
NS
I
O
NAL
O
P
TIM
I
Z
A
T
I
O
N
P
R
O
B
LEM
H
i
g
h
d
i
m
e
n
s
i
o
na
l
o
p
t
i
m
i
z
a
t
i
o
n
ha
s
t
w
o
m
a
i
n
i
s
s
ue
s
o
ne
i
s
t
ha
t
w
i
t
hi
n
t
he
i
nc
r
e
a
s
e
o
f
d
i
m
e
ns
i
o
ns
n
um
be
r
,
t
h
e
num
be
r
of
pos
s
i
b
l
e
s
ol
u
t
i
ons
i
s
g
r
o
w
n
e
x
t
e
n
s
i
ve
l
y
[
1,
3]
.
A
n
d t
h
e
ot
h
e
r
i
s
t
ha
t
t
h
e
s
e
a
r
c
h
s
pa
c
e
ex
t
en
d
ed
ex
p
o
n
e
n
t
i
al
l
y
[
1
,
3
]
.
T
h
es
e t
w
o
i
s
s
u
es
m
ak
e t
h
e a
l
g
o
r
i
t
h
m
f
ace a d
i
f
f
i
c
u
l
t
y
t
o
ach
i
ev
e a
n
o
p
t
i
m
al
s
o
lu
tio
n
a
t th
e
a
p
p
r
o
p
r
ia
te
tim
e
[
1
1
]
.
A
lth
o
u
g
h
o
p
ti
m
iz
a
tio
n
m
e
th
o
d
s
h
a
v
e
b
e
e
n
u
t
iliz
e
d
in
th
e
v
a
r
io
u
s
la
r
g
e
-
s
cal
e s
p
ace p
r
o
b
l
e
m
s
i
n
cl
u
d
i
n
g
el
ect
r
o
n
i
c s
y
s
t
e
m
s
d
es
i
g
n
i
n
g
,
e
n
o
r
m
o
u
s
r
es
o
u
r
ce
s
s
c
h
ed
u
l
i
n
g
,
an
ef
f
e
ct
i
v
e
s
ol
u
t
i
o
n
f
or
pr
obl
e
m
s
i
nv
ol
vi
n
g
h
i
gh
di
m
e
n
s
i
o
n
s
i
s
h
i
gh
l
y
r
e
qu
i
r
e
d [
11]
.
W
ith
th
e
r
a
p
id
e
v
o
lu
tio
n
a
n
d
i
nc
r
eas
es
o
f
d
at
a a
m
o
n
g
v
ar
i
o
u
s
f
i
el
d
s
,
t
h
e n
eed
t
o
t
es
t
an
e
x
i
s
t
i
n
g
al
g
o
r
i
t
h
m
t
o
f
i
n
d
th
e
s
u
ita
b
le
m
e
th
o
d
th
a
t
c
ope
th
e
h
ig
h
d
i
m
e
n
s
io
n
a
l o
p
t
i
m
iz
a
tio
n
p
r
o
b
le
m
s
is
c
r
u
c
ia
l.
2.
1
P
r
ob
l
e
m
F
or
m
u
l
at
i
on
M
an
y
cr
u
ci
al
f
i
el
d
s
i
n
cl
u
d
i
n
g
e
n
g
i
n
eer
i
n
g
,
m
ed
i
ci
n
e,
an
d
eco
n
o
m
ic
s
r
e
l
y
o
n
o
p
ti
m
iz
a
t
io
n
m
ech
a
n
i
s
m
t
o
ach
i
e
v
e t
h
ei
r
r
eq
u
i
r
e
m
e
n
t
s
.
T
h
e o
p
t
i
m
i
za
t
i
o
n
o
f
t
h
e p
r
o
b
l
e
m
s
f
i
e
l
d
s
co
u
l
d
b
e r
ep
r
es
en
t
ed
u
s
i
n
g
m
a
t
h
e
m
a
tic
a
l f
u
n
c
tio
n
s
to
b
e
s
o
lv
e
d
b
y
c
o
m
p
u
ta
tio
n
a
l
m
e
th
o
d
s
[
1
2
]
.
O
p
tim
iz
a
tio
n
p
r
o
b
le
m
e
x
p
r
e
s
s
e
d
b
y
:
1
)
T
he
c
o
s
t
f
unc
t
i
o
n
o
b
j
ect
i
v
e f
u
n
ct
i
o
n
o
r
r
ep
r
es
en
t
s
t
h
e
g
o
a
ls
o
f
o
p
tim
iz
a
tio
n
e
it
h
e
r
m
i
n
i
m
iz
e
o
r
m
a
x
i
m
i
ze.
Y
X
f
a
:
(1
)
W
h
e
r
e
Y
s
h
o
u
l
d be
l
ong
t
o t
he
r
e
a
l
num
be
r
R
Y
⊆
,
X
r
ep
r
es
en
t
ed
t
h
e
p
ar
a
m
et
er
s
o
r
d
i
m
e
n
s
i
o
n
s
o
f
t
h
e p
r
o
b
l
em
,
a
n
d
R
i
s
r
ep
r
es
en
t
ed
t
h
e s
ear
ch
s
co
p
e
2)
T
h
e
di
m
e
n
s
i
on
s
or
v
a
r
i
a
bl
e
s
of
t
h
e
pr
obl
e
m
)
,...,
,
(
2
1
n
x
x
x
.
3)
T
h
e
c
on
s
t
r
a
i
n
t
s
,
w
h
i
c
h
de
t
e
r
m
i
n
e
t
h
e
boun
da
r
y
di
m
e
n
s
i
o
ns
of
a
pa
r
t
i
c
u
l
a
r
pr
obl
e
m
.
I
n
th
i
s
s
tu
d
y
,
th
e
c
o
s
t
f
u
n
c
tio
n
is
i
n
d
ic
a
te
d
b
y
th
e
f
it
n
e
s
s
o
r
q
u
a
lit
y
o
f
v
a
r
i
a
b
le
s
f
o
r
a
m
i
n
i
m
iz
a
tio
n
p
r
o
b
le
m
.
M
in
i
m
iz
e
)
(
x
f
,
)
,...,
,
(
2
1
n
i
x
x
x
x
=
(2
)
i
x
is
c
o
n
s
id
e
r
e
d
a
s
a
g
lo
b
a
l
s
o
lu
tio
n
to
a
g
iv
e
n
p
r
o
b
le
m
if
th
e
s
o
l
u
tio
n
i
s
b
e
tte
r
th
a
n
a
n
y
o
th
e
r
s
o
lu
tio
n
s
.
3.
IN
T
EL
LI
G
EN
C
E
M
ETH
O
D
S
S
w
a
r
m
m
e
a
n
s
a
g
r
ou
p o
f
bi
r
ds
,
a
n
t
s
or
be
e
s
l
i
v
e
i
n
c
ol
on
i
e
s
[
13,
14
]
i
n
w
hi
c
h t
h
e
pa
r
t
s
of
t
h
e
g
r
ou
p
co
m
m
u
n
i
cat
e f
o
r
v
ar
i
e
s
t
as
k
s
s
uc
h a
s
b
ui
l
d
i
n
g a
ne
w
n
e
s
t
o
r
s
e
a
r
c
hi
n
g f
o
r
f
o
o
d
.
S
w
a
r
m
i
nt
e
l
l
i
ge
nc
e
a
lg
o
r
ith
m
s
a
r
e
w
id
e
l
y
u
s
e
d
f
o
r
o
p
tim
iz
a
tio
n
p
r
o
b
le
m
a
m
o
n
g
o
t
h
e
r
a
lg
o
r
ith
m
s
; f
o
r
in
s
ta
n
c
e
,
p
a
r
tic
le
s
w
a
r
m
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
25
02
-
4752
I
nd
o
ne
s
i
a
n J
E
l
e
c
E
ng
&
C
o
m
p
S
c
i
,
V
o
l.
11
, N
o
.
1
,
J
u
l
y
2018
:
30
0
–
307
302
o
p
t
i
m
i
zat
i
o
n
a
n
d
cu
ck
o
o
s
ear
ch
ar
e ap
p
l
i
ed
i
n
s
ci
en
ce an
d
en
g
i
n
eer
i
n
g
,
a
n
d
t
h
es
e
a
l
g
o
r
ith
m
s
h
a
v
e
th
e
a
b
ilit
y
t
o t
a
c
k
l
e
t
h
e
v
a
r
i
e
s
t
y
pe
s
of
opt
i
m
i
z
a
t
i
on
pr
obl
e
m
s
[
6]
.
3.
1.
P
a
r
t
ic
le
S
w
a
r
m
O
p
t
i
m
iz
a
t
io
n
E
b
e
r
ha
r
t
a
nd
K
e
nne
d
y i
n 1
9
9
5
pr
opos
e
d
a
s
w
ar
m
b
as
ed
i
n
t
el
l
i
g
e
n
ce al
g
o
r
i
t
h
m
n
a
m
e
d
P
a
r
tic
le
s
w
a
r
m
o
p
ti
m
iz
a
tio
n
(P
S
O
) [1
5
]
.
P
ar
t
i
cl
e s
w
ar
m
o
p
t
i
m
iz
a
tio
n
f
u
n
c
tio
n
a
lit
y
r
e
l
a
y o
n
t
he
p
a
r
tic
le
s
.T
wo
c
h
a
r
a
c
te
r
is
tic
s
: p
o
s
itio
n
a
n
d
v
e
lo
c
it
y
be
l
ong
t
o
ev
er
y
s
in
g
le
p
a
r
tic
le
.
T
h
e
p
a
r
tic
le
s
h
a
v
e
th
e
t
ow
b
e
st
p
o
s
itio
n
:
p
er
s
o
n
al
(
P
b
e
s
t
)
a
nd
g
l
oba
l
(G
b
e
s
t
)
r
es
p
ect
t
o
t
he
w
ho
l
e
gr
o
up
ma
k
i
ng
th
e
p
a
r
tic
le
le
a
r
n
f
r
o
m
its
e
x
p
e
r
ie
n
c
e
as
w
el
l
as
f
r
o
m
t
h
e
w
h
o
l
e g
r
o
u
p
f
o
r
s
ear
ch
i
n
g
an
o
p
ti
m
iz
e
d
s
o
lu
tio
n
.
T
h
es
e p
o
i
s
o
n
s
ar
e u
p
d
at
i
n
g
b
as
ed
o
n
t
he
f
i
t
ne
s
s
va
l
ue
co
m
p
ar
i
s
o
n
b
et
w
een
t
he
c
ur
r
e
nt
a
nd
t
h
e
n
e
w
p
o
s
itio
n
.
U
n
til
t
h
e s
w
ar
m
fi
n
d
s
t
he
d
es
i
r
ed
s
o
lu
ti
on
t
h
i
s
p
r
o
ces
s
h
a
s
b
een
r
ep
l
i
cat
ed
ma
n
y
t
i
m
e
s
.
T
h
r
ee
v
ect
o
r
s
a
r
e
u
s
i
n
g
f
o
r
i
d
e
nt
i
f
yi
ng
p
a
r
tic
le
i
n
t
h
e
s
ear
c
h
s
co
p
e:
p
o
s
itio
n
)
(
t
X
i
,
v
e
lo
c
it
y
,
)
(
t
V
i
,
an
d
p
er
s
o
n
al
b
es
t
p
o
s
itio
n
b
es
t
P
.
I
n
a
d
d
itio
n
,
its
m
o
v
e
m
e
n
t d
e
te
r
m
in
e
d
by
b
es
t
P
a
nd
b
es
t
G
.
P
S
O
v
el
o
ci
t
y
a
n
d
p
o
s
i
t
i
o
n
f
o
r
m
u
l
a ar
e p
r
es
en
t
ed
i
n
e
q
u
at
i
o
n
3
,
4
r
ecep
t
i
v
el
y
.
)
1
(
+
t
V
i
=
)
(
t
V
i
+
*
*
1
1
r
c
(
b
es
t
P
-
)
(
t
X
i
)+
*
*
2
2
r
c
(
b
es
t
G
-
)
(
t
X
i
(3
)
)
1
(
+
t
X
i
=
)
(
t
X
i
+
)
1
(
+
t
V
i
(4
)
W
h
er
e,
1
r
,
2
r
r
a
n
do
m
num
be
r
s
w
i
t
h
v
a
l
u
e
s
be
t
w
e
e
n
(
0,
1)
wh
i
l
e
1
c
,
a
nd
2
c
ar
e l
ear
n
i
n
g
f
act
o
r
s
.
P
S
O
u
tiliz
e
s
t
he
s
e
f
a
c
to
r
s
to
c
o
n
tr
o
l t
he
u
pda
t
i
n
g pr
oc
e
s
s
of
pa
r
t
i
c
l
e
v
e
l
oc
i
t
y
a
n
d p
os
i
t
i
on
.
T
h
es
e t
w
o
p
ar
am
et
er
s
ar
e u
s
ed
t
o
co
n
t
r
o
l
t
h
e
v
e
lo
c
it
y
a
n
d
p
o
s
itio
n
o
f
th
e
p
a
r
tic
le
.
P
a
r
tic
le
s
w
a
r
m
o
p
ti
m
iz
a
tio
n
h
a
s
ap
p
eal
ed
ma
n
y
r
es
ear
ch
er
s
o
v
er
o
th
e
r
a
l
g
o
r
ith
m
s
.
T
h
e
a
l
g
o
r
ith
m
i
s
s
i
m
p
le
to
i
mp
l
e
me
n
t
a
n
d h
a
s
l
e
s
s
num
be
r
o
f
pa
r
a
m
e
t
e
r
s
[
16]
.
O
n
t
he
o
t
he
r
ha
nd
,
i
t
ha
s
s
o
me
d
r
a
w
b
ack
s
t
ha
t
p
r
e
ve
nt
i
ng
t
he
a
l
go
r
i
t
h
m
fr
o
m
ef
f
ect
i
v
el
y
w
or
k
i
ng
o
n
s
o
me
o
p
ti
m
iz
a
t
io
n
p
r
o
b
l
e
m
.
T
h
e r
es
ear
ch
er
s
s
o
l
v
ed
t
h
i
s
pr
obl
e
m
b
y
s
o
m
e
m
odi
f
i
c
a
t
i
on
on
t
h
e
ba
s
i
c
v
e
r
s
i
on
.
O
n
e
of
t
h
i
s
m
odi
f
i
c
a
t
i
on
i
s
pr
opos
e
d
by
S
h
i
a
n
d
E
b
e
r
h
a
r
t in
1
9
9
8
,
th
e
y
in
tr
o
d
u
c
e
d
th
e
I
n
e
r
tia
W
e
ig
h
t
eq
u
al
s
to
1
to
c
o
n
tr
o
l e
x
p
lo
r
a
tio
n
a
n
d
e
x
p
lo
ita
tio
n
i
n
s
ear
ch
s
p
ace
[
17]
,
an
d
t
h
e v
el
o
ci
t
y
eq
u
at
i
o
n
i
s
al
t
er
ed
to
(
5
).
)
1
(
+
t
V
i
=
*
w
)
(
t
V
i
+
*
*
1
1
r
c
(
b
es
t
P
-
)
(
t
X
i
)+
*
*
2
2
r
c
(
b
es
t
G
-
)
(
t
X
i
)
(5
)
B
ecau
s
e
o
f
t
he
i
m
p
o
r
t
an
ce
o
f
th
e
in
e
r
tia
w
e
i
g
h
t o
n
th
e
P
S
O
p
er
f
o
r
m
a
n
ce
,
it h
a
s
b
e
e
n
w
e
ll
s
tu
d
ie
d
in
th
e
lite
r
a
t
u
r
e
[1
8
]
.
I
n
th
is
s
tu
d
y
,
t
h
e
i
n
er
t
i
a
w
ei
g
h
t
is
e
qu
a
l
t
o
w
=
0.
7298 [
1
9
].
T
he
P
s
e
u
doc
ode
of
pa
r
t
i
c
l
e
s
w
a
r
m
o
p
ti
m
iz
a
tio
n
i
s
a
s
f
o
l
l
o
w
s
:
F
or
i
ndi
v
i
dual
par
t
i
c
l
e
(
i
)
I
n
itia
liz
e
p
a
r
tic
le
v
e
lo
c
ity
I
n
itia
liz
e
p
a
r
tic
le
p
o
s
itio
n
E
n
d
Do
F
o
r
i
=
1 t
o p
opul
at
i
o
n s
i
z
e
E
v
a
lu
a
te
th
e
fitn
e
s
s
v
a
lu
e
I
f th
e
c
u
r
r
e
n
t fitn
e
s
s
v
a
lu
e
is
b
e
tte
r
th
a
n
th
e
p
a
r
tic
le
b
e
s
t
va
l
u
e (
b
es
t
P
)
as
s
i
gn c
ur
r
e
nt
v
al
ue
t
o p
ar
t
i
c
l
e
be
s
t
v
al
ue
(
b
es
t
P
)
en
d
F
o
r
ea
ch
p
a
r
t
i
cl
e
F
in
d
p
a
r
tic
le
w
ith
th
e
b
e
s
t fit
n
e
s
s
a
m
o
n
g
a
ll p
a
r
tic
le
s
a
s
(
b
es
t
G
)
U
pdat
e
p
ar
t
i
c
l
e
v
e
l
oc
i
t
y
ac
c
o
r
di
ng t
o
e
q
uat
i
on (
3)
U
pdat
e
p
ar
t
i
c
l
e
pos
i
t
i
on ac
c
o
r
di
ng t
o e
q
uat
i
on
(4
)
E
n
d
W
hi
l
e
m
ax
i
m
um
i
t
e
r
at
i
on i
s
not
r
e
ac
he
d
3.
2.
C
u
c
ko
o
S
ea
rch
N
e
w
b
a
s
e
d
s
w
a
r
m
i
nt
e
l
l
i
ge
nc
e
a
l
go
r
i
t
h
m
na
m
e
d
C
uc
ko
o
s
e
a
r
c
h(
C
S
)
ha
s
b
e
e
n
a
nno
unc
e
d
i
n
2
0
09
[
20]
.
c
u
c
k
oo s
e
a
r
c
h
t
a
k
e
s
i
t
s
c
on
c
e
pt
s
f
r
o
m
t
h
e
c
u
c
k
oo bi
r
d
w
h
i
c
h
de
pe
n
d on ot
h
e
r
bi
r
ds
t
o br
ood i
t
s
e
gg
s
.
C
u
c
k
o
o
s
ear
ch
h
as
p
r
es
e
n
t
ed
ad
v
an
t
a
g
e p
er
f
o
r
m
a
n
ce o
v
er
m
an
y
o
p
ti
m
iz
a
tio
n
p
r
o
b
le
m
s
;
a
d
d
itio
n
a
ll
y
,
a
s
tu
d
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nd
o
ne
s
i
a
n J
E
l
e
c
E
ng
&
C
o
m
p
S
c
i
I
SSN
:
2502
-
4752
C
om
par
i
s
on
of
Sw
ar
m
I
nt
e
l
l
i
ge
nc
e
A
l
gor
i
t
hm
s
f
or
H
i
gh
D
i
m
e
ns
i
onal
...
(
Sam
ar
B
as
h
at
h
)
303
ha
s
m
e
nt
i
o
ne
d
t
ha
t
t
hi
s
a
l
go
r
i
t
h
m
ha
s
a
n a
b
i
l
i
t
y t
o
f
i
nd
t
he
gl
o
b
a
l
o
p
t
i
m
a
l
[
2
1
]
.
C
S
ha
s
o
nl
y t
w
o
p
a
r
a
m
e
t
e
r
s
t
o
co
n
t
r
o
l
i
t
s
p
r
o
g
r
es
s
.
T
h
at
m
ean
s
i
t
d
o
es
n
’
t
n
eed
t
o
r
eg
u
l
at
e t
h
e
p
ar
a
m
et
er
v
al
u
es
f
o
r
s
p
e
ci
f
i
c p
r
o
bl
e
m
s
.
F
or
t
h
a
t
,
C
S
s
e
e
m
s
t
o be
m
or
e
g
e
n
e
r
i
c
f
or
v
a
r
i
a
t
i
o
n
num
be
r
of
opt
i
m
i
z
a
t
i
o
n
pr
obl
e
m
s
[
20]
.
C
u
c
k
oo s
e
a
r
c
h
f
ol
l
o
w
s
t
h
e
s
e
s
t
e
ps
m
i
m
i
c
k
i
ng t
h
e
c
u
c
k
oo bi
r
ds
.
F
ir
s
t,
c
u
c
k
o
o
b
ir
d
s
s
e
le
c
t a
r
a
n
d
o
m
n
e
s
t to
p
u
t its
e
g
g
s
o
n
i
t.
S
e
c
o
n
d
,
th
e
n
e
s
t
w
it
h
g
o
o
d
m
e
r
its
w
ill
b
e
t
r
a
ns
f
e
r
r
e
d
t
o
t
he
ne
x
t
p
r
o
d
uc
t
i
o
n.
F
i
na
l
l
y,
t
he
ho
s
t
b
i
r
d
s
ha
ve
t
w
o
c
ho
i
c
e
s
e
i
t
he
r
t
hr
o
w
a
w
a
y t
he
e
g
g
s
o
r
l
eav
e t
h
e
n
es
t
t
o
cr
eat
e a n
e
w
o
n
e
w
i
t
h
t
h
e p
r
o
b
ab
i
l
i
t
y
P
a
∈
(
0
,
1
)
.
T
h
e
a
lg
o
r
ith
m
i
m
p
le
m
e
n
ta
t
io
n
i
s
pe
r
f
or
m
e
d ba
s
e
d on
t
h
e
pr
oba
bi
l
i
t
y
of
us
i
ng
t
h
e
n
e
w
c
u
c
k
o
o s
ol
u
t
i
on
[
i
n
s
t
e
a
d of
t
h
e
ba
d ol
d s
ol
u
t
i
on
.
L
é
v
y
f
l
i
g
ht
i
s
i
nv
ok
e
d
w
he
n
e
v
e
r
t
h
e
r
e
i
s
n
e
w
c
r
e
a
t
i
ng
o
f
t
h
e
s
ol
u
t
i
on
a
s
s
h
o
w
n i
n
e
qu
a
t
i
on (
6)
a
n
d i
t
s
s
t
e
p obt
a
i
n
e
d
by
L
é
vy
[
20]
.
(6
)
W
h
er
e
α
>0
an
d
s
et
t
o
1
i
n
c
u
ck
o
o
s
ear
ch
a
n
d
λ
i
s
a
p
ar
a
m
et
er
w
h
i
c
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23
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
25
02
-
4752
I
nd
o
ne
s
i
a
n J
E
l
e
c
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&
C
o
m
p
S
c
i
,
V
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l.
11
, N
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.
1
,
J
u
l
y
2018
:
30
0
–
307
306
5
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.
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o
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P
SO
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, 2
-
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ch
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C
S
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or
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o
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l
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e
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s
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nv
ol
v
i
ng
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i
g
h
di
m
e
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i
ons
.
W
e
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ve
e
xp
l
a
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ne
d
in
d
e
ta
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ls
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h
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f
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n
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t
i
on
a
l
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t
y
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n
d ps
e
u
doc
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of
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ith
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s
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t
an
d
ar
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o
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d
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m
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nd
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unt
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f
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s
.
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o
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d
en
ce t
h
a
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er
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s
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r
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e (
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346
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a
nd
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t
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R
EF
ER
EN
C
ES
[
1]
N
eu
m
ü
l
l
er
C
,
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g
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er
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n
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zel
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ar
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e N
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n
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d
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r
e N
o
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n
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ci
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n
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N
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te
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in
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in
fo
r
m
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s
)
.
2
01
2;
69
27 L
N
C
S
(
P
A
R
T
1)
:
367
–
74
.
[
2]
B
ag
h
el
M
,
A
g
r
a
w
al
S
,
S
i
l
ak
a
r
i S
,
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S
u
r
v
e
y
o
f
M
e
ta
h
e
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r
is
tic
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l
g
o
r
ith
m
s
f
o
r
C
o
m
b
in
a
to
r
ia
l
O
p
tim
iz
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tio
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”
.
I
nt
e
r
nat
i
o
nal
J
our
n
al
of
C
om
p
ut
e
r
A
ppl
i
c
at
i
ons
.
2
01
2;
58
(
19
)
:
9
75
–
8
88
7.
[
3]
S
i
ng
h A
,
J
a
na
N
D
,
“
A
S
ur
v
e
y
on M
e
t
a
he
ur
i
s
t
i
c
s
f
or
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ol
v
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a
r
g
e
S
c
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l
e
O
pt
i
m
i
z
a
t
i
on
P
r
obl
e
m
s
”,
I
n
t
e
r
n
at
i
on
al
J
our
n
al
o
f
C
om
put
e
r
A
ppl
i
c
at
i
on
s
.
20
17;
1
70(
5)
:
1
–
7.
[
4]
S
i
n
g
h
A
,
Ja
n
a
ND,
“
A
S
ur
v
e
y
on M
e
t
a
he
ur
i
s
t
i
c
s
f
or
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ol
v
i
ng
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a
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g
e
S
c
a
l
e
O
pt
i
m
i
z
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t
i
on
P
r
obl
e
m
s
”,
I
n
t
e
r
n
at
i
on
al
J
our
n
a
l o
f
C
om
put
e
r
A
pp
l
i
c
at
i
ons
.
20
17
;
1
70(
5)
:
1
–
7.
[
5]
N
y
ar
k
o
E
K
,
C
u
p
ec R
,
“
A
C
o
m
pa
r
i
s
on of
S
e
v
e
r
a
l
H
e
u
r
is
tic
A
l
g
o
r
ith
m
s
f
o
r
S
o
lv
in
g
H
i
g
h
D
i
m
e
n
s
io
n
a
l O
p
tim
iz
a
tio
n
P
r
o
b
le
m
s
P
r
e
lim
in
a
r
y
C
o
m
m
u
n
ic
a
tio
n
”
,
I
nt
e
r
na
t
i
o
nal
J
our
nal
of
C
om
put
e
r
A
pp
l
i
c
at
i
ons
.
2
01
4;
5(
1)
:
1
–
8.
[
6]
Y
a
n
g
X
.
A
r
tif
ic
ia
l I
n
te
llig
e
n
c
e
,
“
M
e
ta
h
e
u
r
is
tic
O
p
t
im
iz
a
tio
n
: N
a
tu
r
e
-
I
ns
pi
r
e
d A
l
g
or
i
t
hm
s
a
nd A
ppl
i
c
a
t
i
ons
:
in
th
e
A
r
ti
f
ic
ia
l
I
n
te
llig
e
n
c
e
”
,
E
v
ol
ut
i
o
n
ar
y
C
om
p
ut
i
n
g
an
d M
e
t
ahe
ur
i
s
t
i
c
.
Be
rl
i
n
:
S
pr
i
ng
e
r
.
2
01
3.
[
7]
R
aj
ak
u
m
ar
R
,
D
h
av
a
ch
el
v
an
P
,
V
en
g
at
t
ar
am
an
T
,
“
A
s
ur
v
e
y
on na
t
ur
e
i
ns
pi
r
e
d m
e
t
a
-
h
e
u
r
is
tic
a
lg
o
r
ith
m
s
w
ith
its
dom
a
i
n
s
p
e
c
if
ic
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tio
n
s
”
,
P
r
oc
e
e
di
ngs
of
t
he
I
nt
e
r
nat
i
on
al
C
o
nf
e
r
e
nc
e
on C
om
m
uni
c
a
t
i
o
n a
nd E
l
e
c
t
r
oni
c
s
Sy
s
t
e
m
s
,
I
C
C
E
S
2
01
6.
20
16.
[
8]
Y
a
ng
X
,
C
hi
e
n S
F
,
T
i
ng
T
O
.
“
C
o
m
p
u
ta
tio
n
a
l I
n
te
llig
e
n
c
e
a
n
d
M
e
ta
h
e
u
r
is
tic
w
ith
A
l
g
o
r
ith
m
s
A
p
p
lic
a
tio
n
s
”,
Th
e
S
c
i
e
nt
i
f
i
c
w
or
l
d J
our
na
l
.
20
14
;
201
4
:
1
–
4.
[
9]
Is
m
a
il I
,
H
a
lim
A
H
.
“
C
om
pa
r
a
t
i
v
e
s
t
udy
of
m
e
t
a
-
he
ur
i
s
t
i
c
s
opt
i
m
i
z
a
t
i
on a
l
g
or
i
t
hm
us
i
ng
be
nc
h
m
a
r
k
f
unc
t
i
on
”,
I
nd
one
s
i
a
n
J
o
ur
na
l
o
f
E
l
e
c
t
r
i
c
al
E
ngi
ne
e
r
i
ng
an
d C
om
p
ut
e
r
E
n
gi
n
e
e
r
i
ng
.
2
01
7;
7(
3)
:
16
43
-
1
65
0.
[
1
0]
Y
a
n
g X
,
“
S
w
a
r
m
in
te
llig
e
n
c
e
b
a
s
e
d
a
lg
o
r
ith
m
s
: a
c
r
itic
a
l a
n
a
ly
s
is
”,
Ev
o
lu
t
io
n
a
r
y
I
n
te
llig
e
n
c
e
.
2
01
4;
7(
1)
:
17
-
2
8.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nd
o
ne
s
i
a
n J
E
l
e
c
E
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&
C
o
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p
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I
SSN
:
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-
4752
C
om
par
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s
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nc
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A
l
gor
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t
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s
f
or
H
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m
e
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...
(
Sam
ar
B
as
h
at
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)
307
[
1
1]
Ma
hda
v
i
S
,
S
hi
r
i
M
E
,
R
a
h
na
m
a
y
a
n S
,
“
M
e
ta
h
e
u
r
is
tic
s
in
la
r
g
e
-
s
c
a
le
g
lo
b
a
l c
o
n
tin
u
e
s
o
p
tim
iz
a
ti
o
n
: A
s
u
r
v
e
y
”
.
I
nf
or
m
at
i
o
n
S
ci
en
ce
.
20
15
;
2
95:
4
07
-
42
8.
[
1
2]
L
at
o
r
r
e
A
,
M
u
el
as
S
,
P
e
n
a J
M
,
“
L
ar
g
e s
c
al
e g
l
o
b
al
o
p
t
im
iz
a
tio
n
: E
x
p
e
r
im
e
n
ta
l r
e
s
u
lts
w
ith
M
O
S
-
ba
s
e
d hy
br
i
d
a
lg
o
r
ith
m
s
”
,
2013
I
E
E
E
C
on
gr
e
s
s
on E
v
ol
u
t
i
o
nar
y
C
om
put
at
i
on,
C
E
C
20
13
.
2
01
3;
27
42
–
9
.
[
1
3]
A
h
m
ad
n
i
a S
,
T
af
eh
i
E
,
“
U
s
in
g
P
a
r
tic
le
S
w
a
r
m
O
p
tim
iz
a
tio
n
,
G
e
n
e
tic
A
lg
o
r
ith
m
,
H
o
n
e
y
B
e
e
M
a
tin
g
O
p
tim
iz
a
ti
o
n
a
nd S
huf
f
l
e
F
r
og
L
e
a
pi
ng
A
l
g
or
i
t
hm
f
or
S
ol
v
i
ng
O
P
F
P
r
o
bl
e
m
w
i
t
h t
he
i
r
C
om
pa
r
i
s
on
”,
I
n
do
ne
s
i
an
J
our
nal
o
f
E
l
ect
r
i
ca
l
E
n
g
i
n
eer
i
n
g
a
n
d
C
o
m
p
u
t
er
S
ci
en
ce
.
2
01
5;
15(
3)
:
4
45
–
51
.
[
1
4]
A
l H
a
e
k
M
,
R
ita
h
a
n
i
I
s
m
ai
l
A
,
B
as
al
i
b
A
O
,
M
ak
ar
i
m
N
,
“
E
x
pl
or
i
ng
e
ne
r
gy
c
ha
r
g
i
ng
pr
obl
e
m
i
n s
w
a
r
m
r
obot
i
c
s
y
s
te
m
s
u
s
in
g
f
o
r
a
g
in
g
s
i
m
u
la
tio
n
”,
J
ur
n
al
T
e
k
n
ol
o
gi
.
2
01
5;
1:
23
9
–
4
4.
[
1
5]
K
e
nne
dy
J
,
E
be
r
ha
r
t
R
,
“
P
ar
t
i
cl
e s
w
ar
m
o
p
t
i
m
i
zat
i
o
n
.
N
eu
r
al
N
et
w
o
r
k
s
”
,
P
r
oc
e
e
di
ngs
,
I
E
E
E
I
nt
e
r
n
at
i
on
a
l
C
o
n
f
er
en
ce.
1
9
9
5
;
4:
19
42
–
8 vo
l
.
4.
[
1
6]
A
t
t
i
y
a
A
J
,
W
en
y
u
Y
,
S
h
n
een
S
W
,
“
C
om
pa
r
e
d w
i
t
h P
I
,
F
uz
z
y
-
P
I
a
n
d
PSO
-
P
I
C
o
nt
r
ol
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.
20
13;
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1)
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–
21
.
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