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s
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u
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tes
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s
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o
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a
l
p
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si
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ra
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ly
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K
ey
w
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r
d
s
:
Fru
it
f
l
y
o
p
ti
m
izatio
n
R
ea
cti
v
e
po
w
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Statu
s
o
f
m
ate
r
ial
T
r
an
s
m
is
s
io
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lo
s
s
T
h
is i
s
a
n
o
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c
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ss
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rticle
u
n
d
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e
CC B
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SA
li
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se
.
C
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r
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s
p
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A
uth
o
r
:
Kan
a
g
asab
ai
L
e
n
i
n
,
Dep
ar
t
m
en
t o
f
E
lectr
ical
an
d
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lectr
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ics E
n
g
i
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ee
r
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g
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P
r
asad
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P
o
tlu
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d
h
ar
th
a
I
n
s
ti
tu
te
o
f
T
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h
n
o
lo
g
y
,
Kan
u
r
u
,
Vij
a
y
a
w
ad
a,
An
d
h
r
a
P
r
ad
esh
-
520007
,
I
n
d
ia.
E
m
ail:
g
k
len
i
n
@
g
m
ai
l.c
o
m
1.
I
NT
RO
D
UCT
I
O
N
R
ea
cti
v
e
p
o
w
er
p
r
o
b
lem
p
la
y
s
an
i
m
p
o
r
tan
t
r
o
le
in
s
ec
u
r
e
an
d
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n
o
m
ic
o
p
er
atio
n
s
o
f
p
o
w
er
s
y
s
te
m
.
Nu
m
er
o
u
s
t
y
p
e
s
o
f
m
et
h
o
d
s
[
1
-
6
]
h
av
e
b
ee
n
u
tili
ze
d
to
s
o
lv
e
th
e
o
p
ti
m
al
r
ea
ct
iv
e
p
o
w
er
p
r
o
b
le
m
.
Ho
w
e
v
er
m
an
y
s
cien
tific
d
i
f
f
icu
ltie
s
ar
e
f
o
u
n
d
w
h
ile
s
o
lv
i
n
g
p
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b
lem
d
u
e
to
a
n
a
s
s
o
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t
m
en
t
o
f
co
n
s
tr
ain
t
s
.
E
v
o
lu
tio
n
ar
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tec
h
n
iq
u
e
s
[
7
-
1
5
]
ar
e
ap
p
lied
t
o
s
o
lv
e
th
e
r
ea
ctiv
e
p
o
w
er
p
r
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le
m
.
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h
is
p
ap
er
p
r
o
p
o
s
es
en
h
a
n
ce
d
f
r
u
it
f
l
y
o
p
ti
m
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alg
o
r
it
h
m
,
s
tat
u
s
o
f
m
ater
ia
l
a
lg
o
r
ith
m
to
s
o
l
v
e
t
h
e
o
p
tim
al
r
ea
cti
v
e
p
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w
er
p
r
o
b
lem
.
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it
f
l
y
o
p
ti
m
izat
i
o
n
alg
o
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ith
m
i
s
b
ased
o
n
th
e
f
o
o
d
f
in
d
in
g
b
eh
a
v
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t
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f
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it
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l
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.
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h
e
n
co
m
p
ar
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to
o
th
er
s
p
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f
r
u
it
f
l
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is
b
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to
in
v
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an
d
o
s
p
h
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.
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n
th
e
p
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ec
te
d
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h
a
n
ce
d
f
r
u
it
f
l
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o
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tim
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a
lg
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it
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m
(
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,
lin
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r
g
en
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m
ec
h
a
n
i
s
m
o
f
ca
n
d
id
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o
l
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tio
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is
in
co
r
p
o
r
ated
w
it
h
f
r
u
it
f
l
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al
g
o
r
ith
m
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n
o
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ai
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th
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a
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p
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w
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m
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ap
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ch
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b
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m
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w
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ce
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g
lo
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p
ab
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n
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h
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n
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o
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r
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.
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n
s
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a
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alg
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m
(
SM
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tili
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d
to
s
o
lv
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th
e
o
p
ti
m
al
r
ea
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v
e
p
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b
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.
T
h
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s
tate
o
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m
ater
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s
o
lid
,
liq
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id
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an
d
g
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s
h
ap
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b
u
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f
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t
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to
t
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n
tire
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timiz
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(
K
a
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s
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b
a
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in
)
101
co
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tain
er
in
w
h
ich
it
is
r
estri
cted
.
Dev
elo
p
m
e
n
t
is
test
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h
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m
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ρ
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n
ce
.
C
o
ll
is
i
o
n
o
p
er
ato
r
im
i
tate
s
th
e
co
lli
s
io
n
s
f
ac
to
r
in
w
h
ich
m
o
lec
u
les
ar
e
in
ter
ac
tin
g
to
ea
ch
o
th
er
.
I
n
ar
b
itra
r
y
b
e
h
av
io
u
r
o
f
m
o
lec
u
les
,
ca
p
r
icio
u
s
p
o
s
itio
n
s
ar
e
f
o
r
m
e
d
s
u
b
s
eq
u
e
n
t
to
a
p
r
o
b
ab
ilis
tic
co
n
d
itio
n
w
h
ich
co
n
s
id
er
s
c
ap
r
ici
o
u
s
lo
ca
tio
n
s
w
it
h
i
n
a
r
ea
lis
tic
ex
p
lo
r
atio
n
s
p
ac
e.
P
r
o
p
o
s
ed
en
h
an
ce
d
f
r
u
it
f
l
y
o
p
ti
m
iza
tio
n
alg
o
r
ith
m
(
E
F
F),
s
tatu
s
o
f
m
ater
ial
a
lg
o
r
it
h
m
(
SM
A
)
h
as b
ee
n
test
ed
i
n
s
ta
n
d
ar
d
I
E
E
E
3
0
b
u
s
test
s
y
s
te
m
a
n
d
s
i
m
u
latio
n
r
e
s
u
l
ts
s
h
o
w
th
e
p
r
o
j
ec
ted
alg
o
r
ith
m
s
r
ed
u
c
ed
th
e
r
ea
l p
o
w
er
lo
s
s
co
n
s
id
e
r
ab
ly
.
2.
P
RO
B
L
E
M
F
O
R
M
UL
AT
I
O
N
Ob
j
ec
tiv
e
o
f
th
e
p
r
o
b
lem
i
s
to
r
ed
u
ce
th
e
tr
u
e
p
o
w
er
lo
s
s
:
F
=
P
L
=
∑
g
k
k
∈
Nbr
(
V
i
2
+
V
j
2
−
2
V
i
V
j
c
os
θ
ij
)
(
1
)
Vo
ltag
e
d
ev
iatio
n
g
i
v
e
n
as
f
o
llo
w
s
:
F
=
P
L
+
ω
v
×
Vol
ta
ge
De
via
tion
(
2
)
Vo
ltag
e
d
ev
iatio
n
g
i
v
e
n
b
y
:
Vol
ta
ge
de
via
tion
=
∑
|
V
i
−
1
|
N
p
q
i
=
1
(
3
)
C
o
n
s
tr
ain
t (
e
q
u
ali
t
y
)
:
P
G
=
P
D
+
P
L
(
4
)
Co
n
s
tr
ain
t
s
(
i
n
eq
u
a
lit
y
)
:
P
g
s
l
ack
m
i
n
≤
P
g
s
l
ac
k
≤
P
g
s
l
ack
m
ax
(
5
)
≤
Q
gi
≤
Q
gi
m
ax
,
i
∈
N
g
(
6
)
V
i
m
i
n
≤
V
i
≤
V
i
m
ax
,
i
∈
N
(
7
)
T
i
m
i
n
≤
T
i
≤
T
i
m
ax
,
i
∈
N
T
(
8
)
Q
c
m
i
n
≤
Q
c
≤
Q
C
m
ax
,
i
∈
N
C
(
9
)
3.
E
NH
ANC
E
D
F
RUI
T
F
L
Y
O
P
T
I
M
I
Z
AT
I
O
N
AL
G
O
R
I
T
H
M
Fru
it
f
l
y
o
p
ti
m
izatio
n
al
g
o
r
ith
m
is
b
ased
o
n
t
h
e
f
o
o
d
f
i
n
d
in
g
b
eh
a
v
io
r
o
f
t
h
e
f
r
u
it
f
l
y
.
W
h
e
n
co
m
p
ar
e
to
o
th
er
s
p
ec
ies
f
r
u
it
f
l
y
i
s
b
etter
to
in
v
is
io
n
an
d
o
s
p
h
r
esis
[
1
6
]
.
T
h
er
e
ar
e
t
w
o
s
tep
s
in
f
o
o
d
f
in
d
in
g
p
r
o
ce
d
u
r
e
o
f
f
r
u
it
f
l
y
:
at
f
ir
s
t
it
s
m
ells
t
h
e
f
o
o
d
s
o
u
r
ce
b
y
m
ea
n
s
o
f
o
s
p
h
r
esi
s
o
r
g
an
an
d
it
f
lies
in
t
h
at
d
ir
ec
tio
n
;
af
ter
w
ar
d
s
,
w
h
e
n
it
g
ets
clo
s
er
to
th
e
f
o
o
d
s
ite,
th
r
o
u
g
h
it
s
s
en
s
iti
v
e
v
i
s
io
n
it
w
il
l
f
i
n
d
th
e
f
o
o
d
.
Mo
d
eled
alg
o
r
ith
m
o
f
t
h
e
f
r
u
it
f
l
y
o
p
ti
m
izatio
n
h
a
s
b
ee
n
g
i
v
en
b
elo
w
:
a.
I
n
itializatio
n
o
f
p
ar
a
m
eter
s
b.
C
an
d
id
ate
s
o
l
u
tio
n
s
ar
e
en
g
e
n
d
er
ed
c.
L
o
ca
tio
n
o
f
f
r
u
it f
l
y
s
w
ar
m
at
p
r
eli
m
in
ar
y
lev
e
l
_
=
(
)
;
_
=
(
)
(
1
0
)
d.
C
o
n
f
er
ca
p
r
icio
u
s
d
ir
ec
tio
n
an
d
d
is
tan
ce
f
o
r
f
i
n
d
in
g
t
h
e
f
o
o
d
b
y
a
n
in
d
i
v
id
u
al
f
r
u
it f
l
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8792
I
n
t J
A
p
p
l P
o
w
er
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
u
g
u
s
t 2
0
2
0
:
1
0
0
–
1
0
6
102
=
_
+
(
)
;
=
_
+
(
)
(
1
1
)
e.
Fro
m
th
e
o
r
ig
i
n
co
m
p
u
te
t
h
e
d
is
tan
ce
o
f
f
o
o
d
lo
ca
tio
n
=
√
2
+
2
(
1
2
)
f.
Valu
e
o
f
t
h
e
s
m
ell
co
n
ce
n
tr
ati
o
n
j
u
d
g
m
e
n
t is
f
o
u
n
d
b
y
,
=
1
(
1
3
)
=
1
√
(
_
+
(
)
)
2
+
(
_
+
(
)
)
2
(
1
4
)
g.
I
n
d
iv
id
u
a
l f
r
u
it f
l
y
s
m
e
ll c
o
n
c
en
tr
atio
n
i
s
ca
lcu
la
ted
b
y
,
=
(
)
(
1
5
)
h.
Am
o
n
g
t
h
e
f
r
u
it
f
l
y
s
w
ar
m
d
i
s
co
v
er
o
u
t th
e
f
r
u
it
f
l
y
w
it
h
m
a
x
i
m
u
m
s
m
el
l c
o
n
ce
n
tr
atio
n
,
[
,
]
=
(
)
(
1
6
)
i.
B
y
u
s
i
n
g
v
i
s
io
n
to
w
ar
d
s
t
h
at
l
o
ca
tio
n
f
r
u
i
t f
l
y
s
w
ar
m
f
lies
,
=
(
1
7
)
_
=
(
)
(
1
8
)
_
=
(
)
(
1
9
)
j.
R
ep
licate
t
h
e
i
m
p
le
m
e
n
tatio
n
o
f
s
te
p
s
b
-
i.
W
h
en
th
e
s
m
ell
co
n
ce
n
tr
atio
n
is
n
o
t
s
u
p
er
io
r
to
th
e
p
r
ec
ed
in
g
iter
ati
v
e
s
m
el
l
co
n
ce
n
tr
atio
n
an
y
lo
n
g
er
o
r
w
h
e
n
th
e
i
ter
ativ
e
n
u
m
b
er
r
ea
ch
es
th
e
m
a
x
i
m
u
m
n
u
m
b
er
o
f
iter
at
io
n
s
,
th
e
f
lo
w
w
ill
s
to
p
.
I
n
th
e
p
r
o
j
ec
ted
en
h
an
ce
d
f
r
u
it
f
l
y
o
p
ti
m
izatio
n
al
g
o
r
ith
m
(
E
F
F),
lin
ea
r
g
en
er
atio
n
m
ec
h
a
n
i
s
m
o
f
ca
n
d
id
ate
s
o
lu
tio
n
is
in
co
r
p
o
r
ated
w
it
h
f
r
u
it
f
l
y
al
g
o
r
ith
m
.
I
n
o
r
d
er
to
m
a
in
ta
in
th
e
b
ala
n
ce
b
et
w
ee
n
g
lo
b
al
an
d
lo
ca
l sear
ch
a
n
i
n
er
tia
w
ei
g
h
t
is
ap
p
lied
in
t
h
e
p
r
o
ce
d
u
r
e.
Fo
r
g
lo
b
al
s
ea
r
ch
lar
g
e
in
er
ti
a
w
ei
g
h
t is
u
ti
lized
an
d
s
m
all
i
n
er
tia
w
e
ig
h
t
ap
p
lied
f
o
r
lo
ca
l
s
ea
r
ch
.
A
t
th
e
b
eg
in
n
i
n
g
o
f
t
h
e
r
u
n
b
y
d
i
m
in
is
h
i
n
g
th
e
in
er
tia
w
ei
g
h
t
f
r
o
m
a
lar
g
e
v
al
u
e
to
a
s
m
al
l
v
al
u
e,
w
il
l
lead
to
en
h
an
ce
t
h
e
g
lo
b
al
s
ea
r
ch
ca
p
ab
ilit
y
a
n
d
m
o
r
e
lo
ca
l
s
ea
r
ch
ab
ilit
y
w
ill b
e
in
p
r
o
ce
s
s
th
e
e
n
d
o
f
th
e
r
u
n
.
a.
I
n
itializatio
n
o
f
p
ar
a
m
eter
s
b.
C
an
d
id
ate
s
o
l
u
tio
n
s
ar
e
en
g
e
n
d
er
ed
th
r
o
u
g
h
li
n
ea
r
g
e
n
er
atio
n
m
ec
h
a
n
is
m
c.
L
o
ca
tio
n
o
f
f
r
u
it f
l
y
s
w
ar
m
at
p
r
eli
m
in
ar
y
lev
e
l
_
′
=
∗
(
2
0
)
d.
C
o
n
f
er
ca
p
r
icio
u
s
d
ir
ec
tio
n
an
d
d
is
tan
ce
f
o
r
f
i
n
d
in
g
t
h
e
f
o
o
d
b
y
a
n
in
d
i
v
id
u
al
f
r
u
it f
l
y
′
=
_
′
+
∗
;
=
∗
(
2
1
)
e.
Valu
e
o
f
t
h
e
s
m
ell
co
n
ce
n
tr
ati
o
n
j
u
d
g
m
e
n
t is
f
o
u
n
d
b
y
′
=
′
=
_
′
+
∗
(
2
2
)
k.
I
n
d
iv
id
u
a
l f
r
u
it f
l
y
s
m
e
ll c
o
n
c
en
tr
atio
n
i
s
ca
lcu
la
ted
b
y
,
′
=
(
′
)
(
2
3
)
l.
Am
o
n
g
t
h
e
f
r
u
it
f
l
y
s
w
ar
m
d
i
s
co
v
er
o
u
t th
e
f
r
u
it
f
l
y
w
it
h
m
a
x
i
m
u
m
s
m
el
l c
o
n
ce
n
tr
atio
n
,
[
′
,
′
]
=
(
′
)
(
2
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
p
p
l P
o
w
er
E
n
g
I
SS
N:
2252
-
8792
S
o
lvin
g
o
p
tima
l rea
ctive
p
o
w
e
r
p
r
o
b
lem
b
y
en
h
a
n
ce
d
fr
u
it fl
y
o
p
timiz
a
tio
n
…
(
K
a
n
a
g
a
s
a
b
a
i Len
in
)
103
m.
Ma
in
tai
n
t
h
e
m
ax
i
m
u
m
co
n
ce
n
tr
atio
n
v
al
u
e
an
d
′
co
o
r
d
in
ate.
s
u
b
s
eq
u
en
t
l
y
,
b
y
u
s
in
g
v
is
io
n
th
e
f
r
u
it
f
l
y
s
w
ar
m
f
lie
s
i
n
th
e
d
ir
ec
tio
n
o
f
t
h
at
lo
ca
tio
n
:
′
=
′
(
2
5
)
_
′
=
(
)
′
(
2
6
)
n.
R
ep
licate
t
h
e
i
m
p
le
m
e
n
tatio
n
o
f
S
tep
s
b
-
i.
W
h
e
n
t
h
e
s
m
el
l
co
n
ce
n
tr
atio
n
i
s
n
o
t
s
u
p
er
io
r
to
th
e
p
r
ec
ed
in
g
iter
ati
v
e
s
m
el
l
co
n
ce
n
tr
atio
n
an
y
lo
n
g
er
o
r
w
h
e
n
th
e
i
ter
ativ
e
n
u
m
b
er
r
ea
ch
es
th
e
m
a
x
i
m
u
m
n
u
m
b
er
o
f
iter
at
io
n
s
,
th
e
f
lo
w
w
ill
s
to
p
.
4.
ST
A
T
US O
F
M
AT
E
RIA
L
A
L
G
O
R
I
T
H
M
C
o
n
v
en
t
io
n
all
y
,
th
r
ee
s
ta
te
o
f
m
a
ter
ial
ar
e
s
o
lid
,
liq
u
id
,
an
d
g
as.
I
n
g
as
th
er
e
is
n
o
s
p
ec
if
ic
s
h
ap
e,
b
u
t
f
it
in
to
th
e
w
h
o
le
co
n
tai
n
e
r
in
w
h
ich
it
is
r
estricte
d
.
P
r
o
g
r
ess
io
n
is
test
ed
b
y
th
e
m
o
le
cu
les
s
y
m
b
o
lize
t
h
e
u
t
m
o
s
t
allo
w
ab
le
d
is
p
lace
m
e
n
t
ρ
1
am
o
n
g
s
t
th
e
p
ar
ticles.
I
n
ter
m
o
le
c
u
lar
f
o
r
ce
s
ar
e
ex
tr
a
r
estricte
d
in
liq
u
id
s
tate,
th
a
n
i
n
g
as s
tate.
T
h
er
e
w
il
l b
e
en
o
u
g
h
en
er
g
y
f
o
r
th
e
m
o
lecu
le
s
to
s
h
i
f
t c
o
m
p
ar
ati
v
el
y
to
ea
ch
o
t
h
er
b
u
t
a
m
o
b
ile
s
tr
u
ct
u
r
e
w
ill
p
r
ev
a
il.
T
h
r
o
u
g
h
t
h
e
co
n
tai
n
er
th
e
s
h
ap
e
o
f
t
h
e
liq
u
id
ca
n
b
e
ac
ce
s
s
ed
.
Mo
l
ec
u
le
s
s
y
m
b
o
lize
a
p
ar
ticle
m
o
v
e
m
e
n
t
ρ
2
in
s
id
e
t
h
e
liq
u
id
s
tate.
Mo
lecu
les
ar
e
cr
a
m
m
ed
co
llectiv
el
y
w
it
h
f
o
r
ce
s
a
m
o
n
g
s
t
t
h
e
p
ar
ticles
ar
e
b
ein
g
to
u
g
h
en
o
u
g
h
ca
n
n
o
t
m
o
v
e
lib
er
all
y
o
n
l
y
ca
n
v
ib
r
ate
in
th
e
s
o
lid
s
tate.
So
lid
s
tate
h
a
s
a
s
tead
y
,
u
n
a
m
b
ig
u
o
u
s
s
h
ap
e
an
d
p
o
s
s
ess
e
s
s
p
ec
i
f
i
c
v
o
lu
m
e.
So
lid
s
ca
n
o
n
l
y
m
o
d
if
y
t
h
eir
s
h
ap
e
b
y
ap
p
ly
i
n
g
f
o
r
ce
,
an
d
p
ar
ticles a
r
e
ca
p
ab
le
to
v
ib
r
ate
tak
in
g
i
n
t
o
ac
co
u
n
t o
f
a
m
in
i
m
u
m
ρ
3
d
is
tan
ce
[
1
7
]
.
I
n
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
s
tat
u
s
o
f
m
ater
ial
al
g
o
r
it
h
m
(
S
M
A
)
,
f
o
r
ev
o
lu
t
io
n
p
r
o
ce
d
u
r
e
d
ir
ec
tio
n
v
ec
to
r
o
p
er
ato
r
ass
ig
n
a
d
ir
ec
tio
n
to
ev
er
y
m
o
lec
u
le
co
n
s
ec
u
ti
v
el
y
to
g
u
id
e
th
e
p
ar
ticle
p
r
o
g
r
ess
io
n
.
C
o
llis
io
n
o
p
er
ato
r
im
itates
t
h
e
co
llis
io
n
s
f
ac
to
r
in
w
h
ich
m
o
lec
u
les
ar
e
in
ter
ac
tin
g
to
ea
ch
o
th
er
.
I
n
ar
b
itra
r
y
b
eh
a
v
io
u
r
o
f
m
o
lec
u
les,
ca
p
r
icio
u
s
p
o
s
itio
n
s
ar
e
f
o
r
m
ed
s
u
b
s
eq
u
en
t
to
a
p
r
o
b
ab
ilis
tic
co
n
d
itio
n
w
h
ich
co
n
s
id
er
s
ca
p
r
icio
u
s
lo
ca
tio
n
s
w
it
h
i
n
a
r
ea
lis
tic
ex
p
lo
r
atio
n
s
p
ac
e.
P
r
im
ar
il
y
w
i
th
i
n
t
h
e
r
an
g
e
o
f
[
-
1
,
1
]
,
all
th
e
d
ir
ec
tio
n
v
ec
to
r
s
(
=
{
1
,
2
,
.
.
,
}
)
ar
e
ar
b
itra
r
ily
ch
o
s
en
.
Mo
lecu
le
s
ex
p
er
ien
ce
n
u
m
er
o
u
s
attr
ac
tio
n
f
o
r
ce
s
an
d
n
e
w
-
f
an
g
led
d
ir
ec
tio
n
v
ec
to
r
is
ca
lcu
lated
b
y
:
+
1
=
∙
(
1
−
)
∙
0
.
5
+
(
2
7
)
=
(
−
)
/
‖
−
‖
,
(
2
8
)
Velo
cit
y
o
f
ev
er
y
m
o
lecu
le
i
s
ca
lcu
lated
b
y
,
=
∙
(
2
9
)
I
n
itial
v
elo
cit
y
m
a
g
n
i
tu
d
e
co
m
p
u
ted
b
y
,
=
∑
(
ℎ
ℎ
−
)
=
1
∙
(
3
0
)
Ne
w
-
f
a
n
g
led
lo
ca
tio
n
f
o
r
ev
er
y
m
o
lec
u
le
is
m
o
d
er
n
ized
b
y
,
,
+
1
=
,
+
,
∙
(
0
,
1
)
∙
∙
(
ℎ
ℎ
−
)
(
3
1
)
W
h
en
t
w
o
m
o
lec
u
le
s
w
h
ic
h
is
s
h
o
r
ter
th
an
a
d
eter
m
i
n
ed
p
r
o
x
i
m
it
y
v
al
u
e
th
en
C
o
ll
is
io
n
s
w
il
l
o
cc
u
r
.
C
o
n
s
eq
u
en
tl
y
,
i
f
‖
−
‖
<
,
a
co
llis
io
n
b
et
w
ee
n
m
o
lecu
le
s
i
an
d
q
is
ass
u
m
ed
;
o
r
else,
th
er
e
w
o
n
’
t
b
e
co
llis
io
n
,
i
n
v
ie
w
o
f
,
∈
{
1
,
.
.
,
}
≠
.
W
h
en
c
o
llis
io
n
o
cc
u
r
s
,
ev
er
y
p
ar
ticle
d
ir
ec
tio
n
v
ec
to
r
is
tailo
r
ed
b
y
s
w
ap
p
in
g
t
h
eir
p
ar
ticu
lar
d
ir
ec
tio
n
v
ec
to
r
s
as
f
o
llo
w
s
:
=
=
(
3
2
)
C
o
llis
io
n
r
ad
iu
s
co
m
p
u
ted
b
y
,
=
∑
(
ℎ
ℎ
−
)
=
1
∙
(
3
3
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8792
I
n
t J
A
p
p
l P
o
w
er
E
n
g
,
Vo
l.
9
,
No
.
2
,
A
u
g
u
s
t 2
0
2
0
:
1
0
0
–
1
0
6
104
W
ith
in
t
h
e
r
an
g
e
[
0
,
1
]
an
u
n
i
f
o
r
m
ar
b
itra
r
y
n
u
m
b
er
r
m
is
g
e
n
er
ated
an
d
m
o
d
elled
b
y
,
,
+
1
=
{
+
(
0
,
1
)
∙
(
ℎ
ℎ
−
)
ℎ
,
+
1
ℎ
1
−
(
3
4
)
Mo
s
t
ex
ce
llen
t
f
o
u
n
d
in
d
iv
i
d
u
al
f
r
o
m
th
e
cu
r
r
en
t
k
p
o
p
u
latio
n
Q
b
est,
k
is
co
m
p
ar
e
to
th
e
m
o
s
t
ex
ce
lle
n
t
in
d
i
v
id
u
a
l
Q
b
es
t,
k
-
1
o
f
th
e
p
r
ev
io
u
s
g
en
er
atio
n
.
I
f
Q
b
est,
k
is
en
h
a
n
ce
d
th
a
n
Q
best,
k
-
1
b
y
f
it
n
es
s
v
a
lu
e,
th
en
b
est
Q
i
s
m
o
d
er
n
ized
w
it
h
Q
b
est,
k
,
o
r
else
Q
b
est
r
e
m
ai
n
s
w
it
h
o
u
t
an
y
c
h
an
g
e.
C
o
n
s
eq
u
en
tl
y
,
Q
b
est
s
to
ck
u
p
t
h
e
m
o
s
t
e
x
c
e
l
l
e
n
t
i
n
d
i
v
i
d
u
a
l
f
o
u
n
d
u
p
t
o
n
o
w
.
M
o
d
u
s
o
p
e
r
a
n
d
i
m
a
p
t
h
e
e
x
i
s
t
i
n
g
p
o
p
u
l
a
t
i
o
n
Q
k
t
o
t
h
e
n
e
w
-
f
a
n
g
l
e
d
p
o
p
u
latio
n
Q
k
+1
.
Alg
o
r
it
h
m
o
b
tain
th
e
ex
i
s
ti
n
g
p
o
p
u
latio
n
Q
k
an
d
th
e
co
n
f
ig
u
r
atio
n
p
ar
a
m
eter
s
,
,
an
d
H,
y
ield
th
e
n
e
w
-
f
a
n
g
led
p
o
p
u
lati
o
n
Q
k
+1
.
C
o
m
m
o
n
p
r
o
ce
d
u
r
e:
Step
a:
B
est ele
m
e
n
t o
f
t
h
e
p
o
p
u
latio
n
∈
{
}
h
as b
ee
n
f
o
u
n
d
Step
b
:
v
initial
,
r
ar
e
ca
lcu
lated
Step
c:
B
y
m
ea
n
s
o
f
t
h
e
Dir
ec
t
io
n
v
ec
to
r
o
p
er
ato
r
f
in
d
th
e
n
e
w
-
f
an
g
led
mo
lec
u
le
s
Step
d
: B
y
u
tili
zi
n
g
th
e
C
o
llis
i
o
n
o
p
er
ato
r
r
eso
lv
e
th
e
co
llis
i
o
n
s
Step
e:
B
y
u
tili
z
in
g
t
h
e
ar
b
itra
r
y
p
o
s
itio
n
s
o
p
er
ato
r
f
in
d
th
e
n
e
w
-
f
a
n
g
led
ar
b
itra
r
y
p
o
s
itio
n
s
I
n
th
e
o
p
ti
m
izatio
n
p
r
o
ce
d
u
r
e,
5
0
%
o
f
iter
atio
n
s
f
o
r
th
e
g
a
s
s
tate
(
ex
p
lo
r
atio
n
)
,
4
0
%
o
f
iter
atio
n
s
f
o
r
th
e
liq
u
id
s
tate
(
e
x
p
lo
r
atio
n
-
e
x
p
lo
itatio
n
)
an
d
1
0
%
o
f
iter
atio
n
s
f
o
r
th
e
s
o
lid
s
tate
(
ex
p
lo
itatio
n
)
.
A
l
g
o
r
ith
m
b
e
g
i
n
s
b
y
i
n
itia
liz
in
g
a
s
et
Q
o
f
N
Q
m
o
lec
u
le
(
=
{
1
,
2
,
.
.
,
}
)
ea
ch
m
o
lecu
le
p
o
s
itio
n
Q
i
is
a
n
-
d
i
m
e
n
s
io
n
al
v
ec
to
r
co
n
t
ain
i
n
g
t
h
e
p
ar
a
m
eter
v
alu
es
to
b
e
o
p
tim
ized
.
Valu
es
ar
e
ar
b
itra
r
ily
an
d
u
n
v
ar
y
i
n
g
l
y
d
is
p
er
s
ed
b
etw
ee
n
t
h
e
p
r
e
-
s
p
ec
i
f
ied
lo
w
er
p
r
eli
m
in
ar
y
p
ar
a
m
eter
b
o
u
n
d
an
d
th
e
u
p
p
er
in
itial p
ar
a
m
e
ter
b
o
u
n
d
ℎ
ℎ
as f
o
llo
w
s
,
,
0
=
+
(
0
,
1
)
∙
(
ℎ
ℎ
−
)
(
3
5
)
Gas stat
u
s
Step
a:
P
ar
am
eter
s
∈
[
0
.
8
0
,
1
]
,
=
0
.
8
0
,
=
0
.
8
0
,
an
d
H
=0
.
9
0
ar
e
f
ix
ed
Step
b
:
C
o
m
m
o
n
p
r
o
ce
d
u
r
e
w
i
ll b
e
ap
p
lied
Step
c:
W
h
en
5
0
%
o
f
th
e
en
ti
r
e
iter
atio
n
n
u
m
b
er
is
en
d
ed
(
1
≤
k
≤
0
.
5
≤
g
en
era
tio
n
)
,
af
ter
w
ar
d
s
th
e
p
r
o
ce
d
u
r
e
co
n
tin
u
es to
t
h
e
liq
u
id
s
ta
te
p
r
o
ce
s
s
; o
r
else g
o
b
ac
k
to
s
tep
b
.
L
iq
u
id
s
tatu
s
Step
d
:
P
ar
am
eter
s
∈
[
0
.
3
0
,
0
.
6
0
]
,
=0
.
4
0
,
=
0
.
2
0
,
an
d
H
=0
.
2
0
ar
e
f
ix
ed
Step
e:
C
o
m
m
o
n
p
r
o
ce
d
u
r
e
w
i
ll b
e
ap
p
lied
Step
f
:
W
h
en
9
0
%
(
5
0
%
f
r
o
m
t
h
e
g
as
s
tate
a
n
d
4
0
%
f
r
o
m
t
h
e
liq
u
id
s
tate)
o
f
th
e
en
ti
r
e
iter
atio
n
n
u
m
b
er
i
s
co
n
clu
d
ed
(
0
.
5
∙
g
en
era
tio
n
<
k
≤
0
.
9
∙
g
en
era
tio
n
)
,
af
ter
w
ar
d
s
t
h
e
p
r
o
ce
d
u
r
e
co
n
tin
u
e
to
t
h
e
s
o
li
d
s
tate
p
r
o
ce
s
s
;
if
n
o
t
g
o
b
ac
k
to
s
tep
e.
So
lid
s
tatu
s
Step
g
:
P
ar
a
m
eter
s
∈
[
0
.
0
,
0
.
1
]
a
n
d
=
0
.
1
,
=0
,
an
d
H
=0
ar
e
f
ix
ed
Step
h
:
C
o
m
m
o
n
p
r
o
ce
d
u
r
e
w
i
ll b
e
ap
p
lied
Step
i:
I
f
th
e
1
0
0
%
o
f
th
e
en
tire
iter
atio
n
n
u
m
b
er
is
co
n
clu
d
ed
(
0
.
9
∙
g
en
<
k
≤
g
en
)
,
th
en
th
e
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ter
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[1
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3
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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.
1
,
p
p
.
6
1
-
67,
2006
.
[7
]
A
.
M
u
k
h
e
rjee
a
n
d
V
.
M
u
k
h
e
rjee
,
"
S
o
lu
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o
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o
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im
a
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c
ti
v
e
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isp
a
tch
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y
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h
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Ge
n
e
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ra
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p
p
.
2
3
5
1
-
2
3
6
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,
2
0
1
5
.
[8
]
Z.
Hu
,
X.
W
a
n
g
a
n
d
G
.
T
a
y
lo
r,
"
S
to
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h
a
stic
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p
ti
m
a
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re
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c
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p
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2
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p
.
6
1
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2
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,
2
0
1
0
.
[9
]
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0
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b
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l,
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u
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1
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.
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b
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ra
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o
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p
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2
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o
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ize
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o
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5
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,
p
p
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5
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[1
3
]
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.
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a
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F
.
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ra
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, v
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5
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1
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p
p
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4
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1
7
.
[1
4
]
M.
Ca
ld
e
ra
,
P
.
Un
g
a
ro
,
G
.
Ca
m
m
a
ra
ta
a
n
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.
P
u
g
li
si
,
"
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u
rv
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a
se
d
a
n
a
ly
sis
o
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th
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tri
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a
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d
i
n
Italian
h
o
u
se
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o
ld
s
,"
M
a
t
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ma
ti
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a
l
M
o
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o
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E
n
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g
Pro
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l
e
ms
,
v
o
l.
5
,
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3
,
p
p
.
2
1
7
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4
,
2
0
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8
.
[1
5
]
E.
Ra
sh
e
d
i,
S
.
Ne
z
a
m
a
b
a
d
i
a
n
d
S
.
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a
ry
a
z
d
i,
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S
A
:
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g
ra
v
it
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a
rc
h
a
lg
o
rit
h
m
,
"
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fo
rm
a
ti
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n
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c
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s
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l.
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7
9
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3
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p
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2
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3
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-
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2
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9
.
[1
6
]
W
-
T.
P
a
n
,
"
A
n
e
w
f
r
u
i
t
f
l
y
o
p
t
i
m
i
z
a
t
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o
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a
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g
o
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i
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m
:
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a
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n
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-
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ms
,
v
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l.
2
6
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o
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2
,
p
p
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6
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-
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2
0
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2
.
[1
7
]
Y.
Zh
o
u
,
Y.
Z
h
o
u
,
Q.
L
u
o
,
S.
Qi
a
o
a
n
d
R.
W
a
n
g
,
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A
d
v
a
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c
e
d
in
tel
li
g
e
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t
c
o
m
p
u
ti
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g
th
e
o
ries
a
n
d
a
p
p
li
c
a
ti
o
n
s
:
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t
o
p
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ra
to
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f
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r
sta
tes
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m
a
tt
e
r
se
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h
a
lg
o
r
it
h
m
,"
S
p
rin
g
e
r,
2
0
1
5
.
[1
8
]
IEE
E,
"
T
h
e
IEE
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-
tes
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sy
ste
m
s,"
1
9
9
3
.
[
On
li
n
e
]
A
v
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b
le
at
:
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tt
p
:/
/
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w
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rc
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/p
stc
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/.
[1
9
]
A
.
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ss
a
in
,
A
.
A
.
Ab
d
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h
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ied
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h
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g
y
,
v
o
l
.
15
,
n
o
.
8
,
p
p
.
3
1
6
-
327,
2018.
B
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RAP
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AUTHO
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