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1
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5
[
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Gen
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A
l
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m
m
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g
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ith
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d
o
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o
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eq
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ir
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r
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s
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ch
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o
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a
Glo
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S
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m
a
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f
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t
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I
n
co
r
r
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o
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s
o
m
e
o
f
t
h
e
P
SO a
lg
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r
ith
m
p
ar
a
m
eter
s
[
1
]
.
T
h
e
b
asic
P
SO
alg
o
r
ith
m
e
x
p
er
ien
ce
s
p
r
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r
ap
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o
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p
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g
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f
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iv
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it
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[
2
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.
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itio
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s
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m
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o
n
th
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co
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p
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icate
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p
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o
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[
3
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.
Fo
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th
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s
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n
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s
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al
m
o
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f
icatio
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p
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f
o
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m
a
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ce
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th
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b
asic
P
SO.
I
n
[
2
]
,
a
d
iv
er
s
it
y
e
n
h
a
n
ci
n
g
p
r
o
ce
d
u
r
e
an
d
s
ea
r
ch
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tr
ate
g
ies
in
th
e
n
eig
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b
o
r
h
o
o
d
w
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e
en
g
a
g
ed
.
I
n
[
4
]
,
th
e
i
m
p
r
o
v
e
d
P
SO
w
a
s
f
o
u
n
d
ed
o
n
b
ac
k
-
P
r
o
p
ag
atio
n
n
e
u
r
al
n
et
w
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r
k
.
I
n
[
3
]
,
an
ad
ap
tiv
e
m
u
tati
on
w
as
u
til
ized
.
I
n
[
5
]
,
a
s
eg
m
e
n
tatio
n
P
SO
(
SeP
SO
)
ap
p
r
o
ac
h
w
as
p
r
o
p
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s
ed
,
in
w
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h
th
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s
e
g
m
e
n
tatio
n
is
u
til
ized
t
o
o
b
tain
th
e
g
lo
b
al
an
d
lo
ca
l
o
p
ti
m
al
s
o
l
u
tio
n
.
I
n
[
6
]
,
a
D
y
n
a
m
ic
Ob
j
ec
tiv
e
Fu
n
ctio
n
E
n
v
ir
o
n
m
e
n
t
w
as
p
u
r
p
o
s
ed
b
ased
o
n
im
p
r
o
v
ed
P
SO
to
in
cr
ea
s
e
th
e
ca
p
ab
ilit
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to
a
q
u
ick
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ea
ctio
n
to
th
e
en
v
ir
o
n
m
e
n
t
c
h
an
g
e.
I
n
[
7
]
,
t
w
o
en
h
an
ce
d
P
SO
d
ev
el
o
p
s
w
er
e
p
r
o
p
o
s
e,
w
h
ic
h
f
o
u
n
d
ed
o
n
f
u
n
ct
io
n
al
co
n
s
tr
ictio
n
f
ac
to
r
a
n
d
f
u
n
cti
o
n
al
in
er
tia
w
ei
g
h
t.
I
n
[
4
]
,
th
e
b
asic
P
SO
v
elo
cit
y
f
o
r
m
u
la
w
a
s
s
p
lit
in
to
t
w
o
p
ar
ts
an
d
th
e
t
w
o
lear
n
i
n
g
f
ac
to
r
s
w
er
e
u
p
g
r
ad
ed
.
In
[
8
]
,
a
m
u
tatio
n
o
p
er
ato
r
b
ased
o
n
is
o
tr
o
p
ic
Gau
s
s
ian
i
s
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ith
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tio
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A
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in
[
1
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A
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er
n
o
r
-
t
u
r
b
in
e
f
o
r
a
s
in
g
le
p
o
w
er
p
lan
t
b
y
u
s
i
n
g
SeP
SO
alg
o
r
ith
m
w
a
s
p
r
o
p
o
s
ed
in
[
5
]
.
I
m
p
r
o
v
ed
P
SO
w
a
s
u
t
ilized
in
d
if
f
er
e
n
t
tech
n
iq
u
e
s
f
o
r
i
m
a
g
e
p
r
o
ce
s
s
in
g
[
1
1
]
.
Fi
n
all
y
,
a
s
u
r
v
e
y
o
f
P
SO
al
g
o
r
ith
m
ap
p
licatio
n
s
i
n
a
n
te
n
n
a
cir
cu
it
w
as r
ep
o
r
ted
in
[
1
2
]
.
I
n
th
is
p
ap
er
,
th
e
p
r
o
p
o
s
ed
PS
O
alg
o
r
it
h
m
is
co
n
s
tr
u
c
t
ed
b
y
allo
w
i
n
g
th
e
p
ar
a
m
eter
s
o
f
th
e
b
asic
alg
o
r
ith
m
to
b
e
ad
o
p
ted
d
ep
e
n
d
in
g
o
n
th
e
iter
atio
n
v
ar
iab
le.
Mo
r
eo
v
er
,
s
o
m
e
o
f
th
e
p
ar
ticles
'
p
o
s
itio
n
s
i
n
a
s
w
ar
m
ar
e
u
p
d
ated
b
ased
o
n
b
o
u
n
d
ed
r
an
d
o
m
f
as
h
io
n
.
T
h
es
e
m
o
d
if
ica
tio
n
s
ar
e
s
u
g
g
es
ted
f
o
r
th
e
p
u
r
p
o
s
e
th
a
t
th
e
p
ar
ticles d
iv
er
s
it
y
i
s
i
n
cr
ea
s
ed
in
a
s
w
ar
m
f
o
r
in
cr
ea
s
in
g
t
h
e
o
p
p
o
r
tu
n
it
y
o
f
o
b
tain
i
n
g
t
h
e
GOS
.
E
n
d
u
r
e
o
f
th
e
p
ap
er
is
o
r
g
an
ized
in
th
e
f
o
llo
w
i
n
g
:
t
h
e
P
SO
is
a
b
r
ief
d
is
c
u
s
s
io
n
in
Sectio
n
2
.
T
h
e
ap
p
r
o
ac
h
o
f
th
e
p
r
o
p
o
s
ed
E
P
SO
w
ill
b
e
d
esi
g
n
a
te
d
in
Sectio
n
3
.
T
h
e
test
f
u
n
ctio
n
s
,
s
etti
n
g
o
f
th
e
p
ar
a
m
eter
s
an
d
o
u
tco
m
e
s
w
ill
b
e
estab
lis
h
ed
in
Secti
o
n
4
.
L
astl
y
,
in
Sect
io
n
5
th
e
co
n
clu
s
io
n
s
ar
e
illu
s
tr
ated
.
2.
T
H
E
B
ASI
C
P
SO
I
n
b
asic
P
SO,
a
p
r
o
b
lem
o
f
o
p
ti
m
izatio
n
lean
s
to
o
b
tain
a
s
et
o
f
p
ar
am
eter
=
(
1
,
2
,
…
,
)
o
f
d
i
m
en
s
io
n
v
ar
iab
les
i.e
.
(
)
≤
≤
,
=
1
,
2
,
…
,
(
1
)
A
l
g
o
r
ith
m
1
o
f
f
er
in
g
s
th
e
p
r
o
ce
d
u
r
e
o
f
b
asic P
SO.
I
n
P
SO
l
o
g
ar
ith
m
,
ea
ch
ℎ
p
ar
ticle
in
a
s
w
ar
m
o
f
p
ar
ticles
m
o
v
in
g
i
n
a
s
p
ac
e
o
f
-
d
i
m
e
n
s
io
n
is
c
h
ar
ac
ter
ized
b
y
its
p
o
s
itio
n
an
d
v
elo
cit
y
th
at
ar
e
lab
eled
as
=
(
1
,
2
,
,
…
.
,
)
an
d
=
(
1
,
2
,
,
…
.
,
)
,
r
esp
ec
tiv
el
y
.
I
n
th
e
o
r
ig
in
al
P
SO
alg
o
r
ith
m
,
th
e
u
p
d
ate
la
w
o
f
th
e
p
ar
ticles
'
v
el
o
cit
y
an
d
p
o
s
itio
n
ar
e
d
escr
ib
ed
as
[1
,
1
3
]
.
+
1
=
+
1
1
(
−
)
+
2
2
(
−
)
(
2
)
+
1
=
+
+
1
(
3
)
w
h
er
e
1
is
th
e
co
g
n
itiv
e
ac
ce
l
er
atio
n
co
ef
f
icie
n
t,
an
d
2
is
th
e
s
o
cial
ac
ce
ler
atio
n
co
ef
f
icien
t,
1
an
d
2
ar
e
th
e
r
an
d
o
m
v
al
u
es b
et
w
ee
n
[
0
,
1
]
,
is
th
e
p
er
s
o
n
al
b
est o
f
th
e
p
ar
ticle
an
d
is
th
e
g
lo
b
al
b
est o
f
th
e
p
ar
ticle.
is
th
e
c
u
r
r
en
t
p
o
s
itio
n
o
f
ℎ
p
ar
ticle
at
iter
ati
on
a
.
is
th
e
v
elo
cit
y
o
f
ℎ
p
ar
ticle
at
iter
a
tio
n
.
M
a
o
r
eo
v
er
,
to
p
r
ev
en
t
p
r
e
m
atu
r
e
co
n
v
er
g
e
n
ce
a
n
in
er
tia
w
ei
g
h
ti
n
g
f
ac
to
r
w
as
ad
d
ed
t
o
(
1
)
.
T
h
e
m
o
d
if
ied
u
p
d
atin
g
la
w
o
f
t
h
e
v
elo
cit
y
(
2
)
w
a
s
s
u
g
g
e
s
ted
as
[
1
3
]
.
+
1
=
+
1
1
(
−
)
+
2
2
(
−
)
(
4
)
w
h
er
e
is
t
h
e
in
er
tia
w
e
ig
h
t.
Alg
o
rit
h
m
1
(
P
SO a
lg
o
r
ith
m
)
Step
1
.
1
:
I
n
itialize
p
o
p
u
latio
n
w
i
th
r
a
n
d
o
m
p
o
s
it
io
n
an
d
v
elo
cit
y
v
ec
t
o
r
s
.
Step
1
.
2
:
E
v
alu
a
tio
n
f
it
n
ess
o
f
ea
ch
p
ar
t
icle
in
(
1
)
.
Step
1
.
3
:
C
o
m
p
ar
e
ea
ch
p
ar
ticle
'
s
f
it
n
es
s
ev
al
u
atio
n
w
i
th
t
h
e
c
u
r
r
en
t p
ar
ticle's to
o
b
tain
.
Step
1
.
4
:
C
o
m
p
ar
e
f
it
n
es
s
ev
a
lu
at
io
n
w
i
th
th
e
p
o
p
u
latio
n
'
s
o
v
er
all
p
r
e
v
io
u
s
b
est to
o
b
tain
.
Step
1
.
5
:
Up
d
ate
(
4
)
an
d
(
2
)
.
Step
1
.
6
:
I
F
NO
T
th
e
Sto
p
p
in
g
co
n
d
it
io
n
s
ati
s
f
ied
T
H
E
N
G
O
T
O
Ste
p
2
.
Step
1
.
7
:
E
nd
3.
E
NH
ANC
E
D
P
AR
T
I
C
L
E
S
WARM
O
P
T
I
M
I
Z
AT
I
O
N
(
E
P
SO
)
T
h
e
p
r
o
p
o
s
ed
E
P
SO
h
as
b
ee
n
d
ev
elo
p
ed
th
r
o
u
g
h
t
w
o
m
a
i
n
s
tep
s
.
T
h
e
f
ir
s
t
e
n
h
a
n
ce
m
e
n
t
i
n
v
o
l
v
es
th
e
ad
o
p
tio
n
o
f
t
h
e
b
asic
al
g
o
r
ith
m
p
ar
a
m
eter
s
,
1
,
an
d
2
th
r
o
u
g
h
t
h
e
u
s
e
o
f
t
h
e
i
ter
atio
n
v
ar
iab
le
to
d
eter
m
in
e
t
h
e
cu
r
r
e
n
t v
al
u
es o
f
th
e
b
asic p
ar
a
m
eter
s
.
Mo
d
if
y
in
g
(
4
)
to
b
e
ex
p
r
ess
ed
as:
=
0
e
xp
(
−
⁄
)
(
5
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
6
,
Dec
em
b
er
2
0
1
9
:
4
9
0
4
-
4
9
0
7
4906
1
=
01
(
1
+
1
⁄
)
(
6
)
2
=
02
(
1
+
2
⁄
)
(
7
)
+
1
=
+
1
1
(
−
)
+
2
2
(
−
)
(
8
)
w
h
er
e
is
t
h
e
cu
r
r
en
t
E
DI
W
,
1
is
th
e
c
u
r
r
en
t
co
g
n
iti
v
e
ac
c
eler
atio
n
co
ef
f
icie
n
t
,
2
is
t
h
e
cu
r
r
en
t
s
o
cial
ac
ce
ler
atio
n
co
ef
f
icie
n
t
at
ite
r
atio
n
,
a
n
d
is
th
e
lar
g
es
t
ti
m
e
o
f
iter
atio
n
s
.
T
h
e
i
n
it
ial
v
alu
e
s
o
f
t
h
e
p
ar
am
eter
s
,
1
,
an
d
2
ar
e
0
,
01
,
an
d
02
,
r
esp
ec
tiv
el
y
.
T
h
is
en
h
a
n
ce
d
a
lg
o
r
ith
m
is
i
m
p
le
m
e
n
t
in
th
e
ai
d
o
f
th
r
ee
p
ar
a
m
eter
s
w
h
ic
h
ar
e
,
1
,
an
d
2
.
T
h
e
s
ec
o
n
d
en
h
an
ce
m
e
n
t
is
i
m
p
le
m
e
n
ted
f
o
r
th
e
r
ea
s
o
n
t
h
at
th
e
p
ar
ticles
d
iv
er
s
it
y
i
s
in
c
r
ea
s
ed
in
a
s
w
ar
m
f
o
r
in
cr
ea
s
in
g
t
h
e
o
p
p
o
r
tu
n
i
t
y
o
f
r
es
u
lt
t
h
e
G
AS
i
n
wh
ich
p
o
s
th
e
itio
n
o
f
s
o
m
e
o
f
t
h
e
p
ar
ticles
i
n
a
s
w
ar
m
i
s
m
o
d
i
f
ied
r
an
d
o
m
l
y
w
it
h
i
n
a
ce
r
tain
r
a
n
g
e
ac
co
r
d
in
g
to
:
I
f
3
>
3
T
H
E
N
+
1
=
+
+
1
(
1
+
2
(
4
−
0
.
5
)
)
,
E
L
SE
+
1
=
+
+
1
w
h
er
e
3
an
d
4
ar
e
th
e
r
an
d
o
m
v
alu
es
b
et
w
ee
n
[
0
,
1
]
,
3
is
th
e
p
er
ce
n
tag
e
o
f
p
ar
ticles
co
v
er
ed
b
y
v
elo
cit
y
ch
an
g
e
an
d
is
th
e
m
ax
i
m
u
m
p
er
ce
n
tag
e
i
n
cr
ea
s
e
i
n
s
p
ee
d
th
e
o
f
p
a
r
ticles.
4.
NUM
E
RICAL
S
I
M
UL
AT
I
O
N
Fo
r
th
e
p
u
r
p
o
s
e
o
f
test
in
g
th
e
s
u
g
g
ested
en
h
an
ce
d
alg
o
r
it
h
m
,
f
iv
e
test
f
u
n
ctio
n
s
(
B
o
o
t
h
f
u
n
ctio
n
(
0
)
,
H
o
l
d
e
r
-
T
a
b
l
e
f
u
n
c
t
i
o
n
(
1
)
,
Mc
C
o
r
m
ic
k
f
u
n
c
tio
n
(
2
)
,
Mc
C
o
r
m
ic
k
f
u
n
ct
io
n
(
2
)
,
Sp
here
F
un
ct
io
n
(
3
)
,
T
hree
-
H
u
m
p
Ca
m
el
F
un
ct
i
o
n
(
4
)
)
ar
e
ite
m
ized
i
n
T
ab
le
1
.
Fo
r
th
e
p
u
r
p
o
s
e
o
f
r
elati
n
g
t
h
e
E
P
SO
w
it
h
b
asic
P
SO;
all
th
e
f
i
v
e
te
s
t
f
u
n
ctio
n
s
ar
e
r
ep
etitiv
e
1
0
0
0
tim
es.
T
h
e
Sta
n
d
ar
d
Dev
iatio
n
(
ST
D)
an
d
Min
i
m
u
m
Valu
e
(
MI
N)
ar
e
s
elec
ted
t
o
r
ev
ea
l
th
e
al
g
o
r
ith
m
s
ad
v
an
tag
e
s
an
d
d
is
ad
v
an
tag
e
s
.
I
n
th
is
e
x
p
er
i
m
e
n
t,
th
e
p
ar
a
m
eter
s
o
f
t
h
e
b
asic
P
SO
a
n
d
t
h
e
E
P
SO
ar
e
lis
ted
i
n
T
ab
le
2
.
T
h
e
n
u
m
er
ical
r
es
u
lts
o
f
ap
p
l
y
i
n
g
b
o
th
alg
o
r
ith
m
s
o
f
th
e
f
iv
e
te
s
t
f
u
n
ctio
n
s
ar
e
lis
ted
in
T
ab
le
3
.
T
h
e
r
esu
lt
s
in
d
icate
d
in
T
ab
le
3
clea
r
ly
ill
u
s
tr
ate
s
th
e
s
u
p
er
io
r
it
y
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
to
t
h
e
b
asic
al
g
o
r
ith
m
as
a
re
s
u
lt
o
f
th
e
c
h
an
g
e
t
h
e
v
alu
e
o
f
th
e
alg
o
r
it
h
m
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RE
F
E
R
E
NC
E
S
[1
]
T
.
Y.
Ch
e
n
a
n
d
T
.
M
.
C
h
i,
“
On
t
h
e
im
p
ro
v
e
m
e
n
ts
o
f
th
e
p
a
rti
c
le
s
w
a
r
m
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
,
”
Ad
v
.
En
g
.
S
o
ft
w
.
,
v
o
l.
4
1
,
p
p
.
2
2
9
-
2
3
9
,
2
0
1
0
.
[2
]
H.
W
a
n
g
,
e
t
a
l
.
,
“
Div
e
rsit
y
e
n
h
a
n
c
e
d
p
a
rti
c
le
sw
a
r
m
o
p
ti
m
iz
a
ti
o
n
w
it
h
n
e
ig
h
b
o
r
h
o
o
d
se
a
rc
h
,
”
In
f.
S
c
i.
(
Ny
).
,
v
o
l.
2
2
3
,
p
p
.
1
1
9
-
1
3
5
,
2
0
1
3
.
[3
]
D.
C.
T
ra
n
,
e
t
a
l
.
,
“
A
N
e
w
A
p
p
ro
a
c
h
o
f
Div
e
rsit
y
En
h
a
n
c
e
d
P
a
rti
c
le
S
wa
r
m
Op
ti
m
iza
ti
o
n
w
it
h
Ne
ig
h
b
o
rh
o
o
d
S
e
a
rc
h
,
”
p
p
.
1
4
3
-
1
4
4
,
2
0
1
4
.
[4
]
Z
.
Zh
o
u
a
n
d
B.
Jia
o
,
“
Im
p
ro
v
e
m
e
n
t
o
f
P
a
rti
c
le S
w
a
r
m
Op
ti
m
iz
a
ti
o
n
,
”
PIE
R
S
On
li
n
e
,
v
o
l.
5
,
p
p
.
2
6
1
-
2
6
4
,
2
0
0
9
.
[5
]
A
.
S
.
Ja
b
e
r,
e
t
a
l
.
,
“
A
n
e
w
p
a
ra
m
e
ters
id
e
n
ti
f
ica
ti
o
n
o
f
sin
g
le
a
re
a
p
o
w
e
r
s
y
st
e
m
b
a
se
d
L
F
C
u
sin
g
S
e
g
m
e
n
tatio
n
P
a
rti
c
le S
w
a
rm
Op
ti
m
iza
ti
o
n
(S
e
P
S
O) alg
o
rit
h
m
,
”
Asia
-
P
a
c
if
ic P
o
we
r E
n
e
rg
y
En
g
.
C
o
n
f.
AP
PE
EC
,
2
0
1
3
.
[6
]
Y.
L
u
,
e
t
a
l
.
,
“
Im
p
ro
v
e
d
p
a
rti
c
le
sw
a
r
m
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
a
n
d
it
s
a
p
p
l
ica
ti
o
n
i
n
tex
t
f
e
a
tu
re
se
lec
ti
o
n
,
”
Ap
p
l.
S
o
ft
Co
mp
u
t.
J
.
,
v
o
l.
3
5
,
p
p
.
6
2
9
-
6
3
6
,
2
0
1
5
.
[7
]
X
.
Ya
n
,
e
t
a
l
.
,
“
A
n
I
m
p
ro
v
e
d
P
a
rti
c
le
S
wa
r
m
Op
ti
m
iz
a
ti
o
n
A
lg
o
r
it
h
m
a
n
d
It
s
A
p
p
li
c
a
ti
o
n
,
”
v
o
l.
1
0
,
p
p
.
3
1
6
-
3
2
4
,
2
0
1
3
.
[8
]
D.
F
u
rm
a
n
,
e
t
a
l
.
,
“
En
h
a
n
c
e
d
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iz
a
ti
o
n
A
lg
o
rit
h
m
:
Ef
f
i
c
ien
t
T
ra
in
in
g
o
f
Re
a
x
F
F
Re
a
c
ti
v
e
F
o
rc
e
F
ield
s,”
J
.
Ch
e
m.
T
h
e
o
ry
C
o
mp
u
t
.
,
v
o
l
.
1
4
,
p
p
.
3
1
0
0
-
3
1
1
2
,
2
0
1
8
.
[9
]
M
.
R.
A
lRas
h
id
i
a
n
d
M
.
E.
El
-
Ha
w
a
r
y
,
“
A
su
rv
e
y
o
f
p
a
rti
c
le
s
w
a
r
m
o
p
ti
m
iz
a
ti
o
n
a
p
p
li
c
a
ti
o
n
s
i
n
e
lec
tri
c
p
o
w
e
r
s
y
ste
m
s,”
IEE
E
T
ra
n
s.
Evo
l
.
Co
m
p
u
t.
,
v
o
l.
1
3
,
p
p
.
9
1
3
-
9
1
8
,
2
0
0
9
.
[1
0
]
A
.
S
.
Ja
b
e
r,
e
t
a
l
.
,
“
A
d
v
a
n
c
e
Two
-
A
re
a
L
o
a
d
F
re
q
u
e
n
c
y
Co
n
tro
l
Us
in
g
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iza
ti
o
n
S
c
a
led
F
u
z
z
y
L
o
g
ic,”
Ad
v
.
M
a
ter
.
Res
.
,
v
o
l.
6
2
2
-
6
2
3
,
p
p
.
8
0
-
8
5
,
2
0
1
2
.
[1
1
]
R.
W
a
n
g
,
“
R
e
se
a
r
c
h
o
n
Im
a
g
e
P
ro
c
e
ss
in
g
Ba
se
d
o
n
I
m
p
ro
v
e
d
P
a
rt
icle
S
wa
r
m
Op
ti
m
iza
ti
o
n
,
”
2
0
1
8
1
0
t
h
In
t.
C
o
n
f
.
M
e
a
s.
T
e
c
h
n
o
l
.
M
e
c
h
a
tro
n
ics
Au
t
o
m.
,
p
p
.
5
3
8
-
5
4
0
,
2
0
1
8
.
[1
2
]
Q.
P
i
a
n
d
H.
Ye
,
“
S
u
rv
e
y
o
f
p
a
r
ti
c
le
s
w
a
r
m
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
s
in
a
n
ten
n
a
c
ircu
it
,
”
2
0
1
5
IEE
E
In
t.
Co
n
f.
Co
mm
u
n
.
Pr
o
b
l
.
ICCP
2
0
1
5
,
p
p
.
4
9
2
-
4
9
5
,
2
0
1
6
.
[1
3
]
G
.
Ya
n
g
,
“
A
m
o
d
if
ied
p
a
rti
c
le
sw
a
r
m
o
p
ti
m
ize
r
a
l
g
o
rit
h
m
,
”
2
0
0
7
8
th
In
t
.
Co
n
f.
El
e
c
tro
n
.
M
e
a
s.
In
stru
me
n
ts,
ICEM
I
,
p
p
.
2
6
7
5
-
2
6
7
9
,
2
0
0
7
.
[1
4
]
M
.
El
k
h
e
c
h
a
f
i,
e
t
a
l
.
,
“
F
iref
l
y
A
l
g
o
rit
h
m
f
o
r
S
u
p
p
ly
Ch
a
in
O
p
ti
m
iza
ti
o
n
,
”
Lo
b
a
c
h
e
v
sk
ii
J
.
M
a
th
.
,
v
o
l.
3
9
,
p
p
.
3
5
5
-
3
6
7
,
2
0
1
8
.
[1
5
]
S
.
G
.
De
-
L
o
s
-
Co
b
o
s
-
S
i
lv
a
,
e
t
a
l
.
,
“
A
n
E
f
f
i
c
ien
t
A
l
g
o
rit
h
m
f
o
r
Un
c
o
n
stra
i
n
e
d
Op
ti
m
iza
ti
o
n
,
”
M
a
t
h
.
Pro
b
l.
E
n
g
.
,
v
o
l.
2
0
1
5
,
2
0
1
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.