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anc
e
of
a t
r
ans
m
i
s
s
i
on
lin
e
b
y
a
c
t
i
n
g as
an i
nduc
t
i
v
e or
c
apac
i
t
i
v
e c
om
pens
at
i
on d
ev
i
c
e
[
3]
.
V
ar
i
ous
s
t
ud
i
es
ha
v
e
b
een
c
onduc
t
e
d
on o
pt
i
m
al
pl
ac
e
m
ent
of
F
A
C
T
S
de
v
i
c
es
i
n
a po
w
er
s
y
s
t
em
t
o ac
hi
e
v
e
v
ar
i
ous
go
al
s
s
uc
h as
m
i
ni
m
i
z
i
ng t
h
e t
ot
al
po
w
er
l
os
s
i
n a p
o
w
er
s
y
s
t
em
,
i
m
pr
ov
em
ent
of
v
ol
t
a
ge pr
of
i
l
e,
opt
i
m
al
po
w
er
f
l
o
w
,
m
ax
i
m
i
z
at
i
on
of
av
a
i
l
ab
l
e t
r
a
ns
f
er
c
apac
i
t
y
.
P
ar
t
i
c
l
e
S
w
ar
m
O
pt
i
m
i
z
at
i
o
n
(
P
S
O
)
t
ec
h
ni
q
ue
has
b
ee
n
w
i
d
el
y
i
m
pl
em
ent
ed t
o s
o
l
v
e
pr
ob
l
em
s
on
opt
i
m
al
F
A
C
T
S
de
v
i
c
es
pl
ac
em
ent
s
uc
h pow
er
l
o
s
s
r
educ
t
i
on
[
4]
,
v
ol
t
age
pr
of
i
l
e i
m
pr
ov
em
ent
[
5]
,
m
a
x
i
m
i
s
at
i
on of
l
oa
di
n
g m
ar
gi
n and c
om
bi
nat
i
ons
of
al
l
pr
o
bl
em
s
[
6]
.
V
ar
i
ous
ot
h
er
t
ec
hn
i
qu
e
s
hav
e b
een
i
m
pl
em
ent
ed t
o s
o
l
v
e
opt
i
m
al
F
A
C
T
S
de
v
i
c
e
al
l
oc
a
t
i
on
s
uc
h as
G
ene
t
i
c
A
l
gor
i
t
hm
(
G
A
)
[
7]
,
T
eac
hi
ng Le
ar
ni
ng B
as
ed
O
pt
i
m
i
z
at
i
on (
T
LB
O
)
[
8]
,
H
ar
m
on
y
S
e
ar
c
h (
H
S
)
A
l
g
or
i
t
hm
[
9]
,
E
v
ol
u
t
i
o
nar
y
P
r
ogr
am
m
i
ng
(
E
P
)
[
10]
,
D
i
f
f
er
ent
i
a
l
E
v
o
lu
t
io
n
(
D
E
)
[
11]
a
n
d
C
at
S
w
ar
m
O
pt
i
m
i
z
at
i
on (
C
S
O
)
[
12
]
.
D
es
pi
t
e of
t
he i
m
pl
em
ent
at
i
on of
v
ar
i
ous
op
t
i
m
i
s
at
i
on t
ec
hni
que
s
,
e
ac
h of
t
he
t
ec
hni
qu
e
i
m
pos
es
s
er
i
ous
dr
a
w
bac
k
s
w
hi
c
h r
educ
e
s
t
he
qu
al
i
t
y
of
t
h
e f
i
na
l
s
o
l
ut
i
o
n.
T
o
ov
er
c
om
e t
he
pr
obl
em
,
t
hi
s
pa
per
pr
es
en
t
s
t
he
ap
pl
i
c
at
i
on
of
C
haos
E
m
bedded
S
y
m
bi
ot
i
c
O
r
gani
s
m
s
S
ear
c
h
(
C
SO
S)
t
e
c
h
n
i
q
ue t
o s
o
l
v
e opt
i
m
al
F
A
C
T
S
dev
i
c
es
al
l
oc
at
i
on i
n a t
r
ans
m
i
s
s
i
on s
y
s
t
em
t
o
i
m
pr
ov
e t
he
v
o
l
t
a
ge pr
of
i
l
e
and
v
o
l
t
ag
e s
ec
ur
i
t
y
i
n t
he
s
y
s
t
em
.
T
he v
ol
t
age
pr
of
i
l
e
i
n t
h
e s
y
s
t
em
i
s
obs
er
v
ed t
hr
oug
h t
h
e v
a
l
ue
of
t
ot
al
v
o
l
t
a
ge d
ev
i
a
t
i
on i
ndex
i
n t
h
e s
y
s
t
em
w
h
i
l
e
t
he v
o
l
t
a
ge
s
ec
ur
i
t
y
i
s
obs
er
v
ed us
i
ng a v
ol
t
ag
e s
t
abi
l
i
t
y
i
n
dex
k
now
n as
F
as
t
V
ol
t
ag
e S
t
a
bi
l
i
t
y
I
ndex
(
F
V
S
I
)
.
T
he
m
ai
n obj
ec
t
i
v
e of
t
hi
s
r
es
ear
c
h i
s
t
o
i
m
pr
ov
e t
h
e v
o
l
t
ag
e pr
of
i
l
e t
hr
ou
gh
m
i
ni
m
i
z
at
i
on of
v
o
l
t
ag
e
de
v
i
a
t
i
o
n
i
nd
ex
a
nd
i
m
pr
ov
em
ent
of
v
ol
t
age
s
e
c
u
r
it
y
v
ia
m
in
im
iz
a
t
io
n
o
f
t
h
e
w
o
r
s
t
F
V
S
I
v
a
l
ue.
C
om
par
at
i
v
e s
t
ud
i
es
ar
e al
s
o c
o
nduc
t
ed
w
it
h
E
P a
n
d
P
SO
,
h
i
gh
l
i
ght
i
ng
t
h
e s
uper
i
or
i
t
y
of
C
S
O
S
i
n
t
er
m
of
s
ol
ut
i
on
q
ual
i
t
y
pr
o
v
i
ded
b
y
t
h
e
op
t
i
m
i
s
at
i
on
a
lg
o
r
it
h
m
.
2.
R
e
sea
r
ch
M
et
h
o
d
T
o
s
ol
v
e
t
he
pr
o
bl
em
s
s
t
at
ed
as
i
n
s
ec
t
i
on
1,
C
S
O
S
t
ec
hni
que
i
s
app
l
i
ed
t
o
obt
a
i
n
t
he
opt
i
m
al
F
A
C
T
S
d
ev
i
c
e a
l
l
oc
at
i
o
n
w
h
i
c
h ar
e
S
V
C
s
i
z
i
ng a
nd T
C
S
C
c
om
pens
a
t
i
on r
at
i
o t
o
be
i
m
pl
em
ent
ed
i
n
a
po
w
er
s
y
s
t
em
.
T
he
det
ai
l
of
t
h
e
pr
o
bl
em
s
r
el
at
ed
t
o
t
he
o
p
t
im
is
a
t
io
n
pr
oc
es
s
s
uc
h
as
o
bj
ec
t
i
v
e
f
unc
t
i
on
and
t
he
c
ons
t
r
a
i
nt
s
i
m
pos
ed
ar
e
d
i
s
c
us
s
ed
i
n
s
ec
t
i
on
2.
1
w
hi
l
e
br
i
ef
ex
pl
a
nat
i
on
ab
out
t
he C
S
O
S
t
ec
h
ni
q
ue
i
s d
i
scu
sse
d
i
n
s
ec
t
i
on
2.
2.
2
.
1
.
P
r
o
b
l
e
m
F
o
r
m
u
l
a
ti
o
n
T
he
goal
of
t
hi
s
r
es
e
ar
c
h
i
s
t
o
i
m
pl
em
ent
C
S
O
S
t
ec
h
ni
q
ue
f
or
s
ol
v
i
ng
t
he
opt
i
m
al
SVC
and T
C
S
C
al
l
oc
at
i
on
i
n
a t
r
ans
m
i
s
s
i
on s
y
s
t
em
.
T
he ob
j
ec
t
i
v
e
of
t
he
o
p
t
im
is
a
t
io
n
t
ec
hni
que
i
s
t
o
s
ol
v
e
m
i
ni
m
i
z
at
i
on
of
m
ul
t
i
-
obj
ec
t
i
v
e pr
ob
l
em
s
r
el
at
ed t
o v
o
l
t
a
ge pr
of
i
l
e an
d v
ol
t
a
ge s
ec
ur
i
t
y
i
s
s
ue.
T
he f
i
r
s
t
obj
ec
t
i
v
e
of
t
he
opt
i
m
i
s
at
i
on
i
s
t
o
i
m
pr
ov
e
t
he
v
ol
t
age
pr
of
i
l
e
of
t
he s
y
s
t
em
b
y
m
i
ni
m
i
s
i
ng
t
he
t
ot
a
l
v
ol
t
ag
e
de
v
i
a
t
i
on
i
ndex
(
V
D
I
)
of
t
he
s
y
s
t
em
.
T
he
f
i
t
nes
s
f
unc
t
i
on
of
V
D
I
is
r
epr
es
ent
e
d
b
y:
1
=
=
,
−
,
2
=
1
(
1)
W
he
r
e
VD
I
is
t
h
e
t
o
t
a
l
v
o
l
t
age
de
v
i
at
i
on
i
n
dex
of
t
he
bus
es
i
n
t
he
s
y
s
t
em
.
I
n
[
1
3]
,
VD
I
i
s
o
n
l
y
c
ons
i
der
e
d
at
l
oa
d bus
es
.
T
her
ef
or
e,
v
ol
t
a
ge d
ev
i
at
i
on at
b
us
es
ot
h
er
t
ha
n l
o
ad bus
es
ar
e
ex
c
l
ude
d
f
r
om
t
h
e
to
ta
l
VD
I
.
R
ef
er
enc
e v
al
ue of
bus
v
ol
t
a
ge
i
n t
h
e s
y
s
t
em
i
s se
t
t
o un
i
t
y
.
I
n t
hi
s
s
t
ud
y
,
t
he
r
ef
er
enc
e v
a
l
u
e
of
l
oad
bus
es
i
s
s
et
t
o
1.
0
0
p.
u.
w
h
i
l
e
r
ef
er
enc
e
v
al
u
e
of
s
l
ac
k
bus
and
gen
er
at
or
b
us
es
ar
e s
e
t
at
t
h
ei
r
v
o
l
t
a
ge s
et
po
i
nt
as
i
n t
he
po
w
er
f
l
o
w
a
l
gor
i
t
hm
.
T
he s
ec
ond
obj
ec
t
i
v
e of
t
h
e
opt
i
m
i
s
at
i
on
pr
oc
es
s
i
s
t
o
i
m
pr
ov
e
t
he
v
o
l
t
ag
e
s
ec
ur
i
t
y
of
t
he
s
y
s
t
em
.
T
o
as
s
es
s
t
he
v
o
l
t
ag
e
s
ec
ur
i
t
y
of
t
he
po
w
er
s
y
s
t
em
,
v
ol
t
ag
e
s
t
a
bi
l
i
t
y
i
n
dex
c
an
be
i
m
pl
em
ent
ed.
I
n t
h
i
s
r
es
ea
r
c
h,
t
he v
ol
t
age s
t
a
bi
l
i
t
y
i
n
dex
us
ed i
s
F
as
t
V
o
l
t
ag
e
S
t
ab
i
l
i
t
y
I
n
dex
(
F
VSI
)
de
v
e
l
op
ed b
y
Mus
i
r
i
n
et
al
.
[
1
4]
.
T
o i
m
pr
ov
e t
he
v
ol
t
age s
t
a
bi
l
i
t
y
,
t
h
e v
a
l
ue
of
w
or
s
t
F
VSI
s
houl
d
b
e
m
in
im
is
e
d
.
T
he
w
or
s
t
r
ef
er
s
t
o t
he
h
i
ghes
t
F
VSI
v
al
ue.
T
her
ef
or
e,
t
he
f
i
t
nes
s
f
unc
t
i
on
f
or
t
he s
ec
ond
opt
i
m
i
s
at
i
on
obj
ec
t
i
v
e c
an
be
ex
pr
es
s
ed
by
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
25
02
-
4
752
I
J
E
EC
S
V
o
l.
8
,
N
o.
1,
O
c
t
o
ber
20
17
:
1
46
–
1
53
148
2
=
=
4
2
2
(
2)
I
n
t
h
i
s
s
t
u
d
y
,
t
h
er
e
ar
e
2
op
t
i
m
i
s
at
i
on
o
bj
ec
t
i
v
es
w
hi
c
h
ne
eds
t
o
b
e
c
ons
i
der
ed.
N
or
m
al
l
y
,
a
n
o
pt
i
m
i
s
at
i
o
n
p
r
oc
es
s
w
i
l
l
c
at
er
o
nl
y
1
obj
ec
t
i
v
e.
T
o
c
at
er
a
l
l
t
he
s
t
at
ed
o
bj
ec
t
i
v
es
,
m
u
lt
i
-
ob
j
ec
t
i
v
e
opt
i
m
i
s
at
i
on
m
ode
s
houl
d
be
i
m
pl
em
en
t
ed.
T
o
s
ol
v
e
m
ul
t
i
-
o
bj
ec
t
i
v
e
opt
i
m
i
s
at
i
on
pr
obl
em
,
w
ei
ght
e
d s
um
met
ho
d
is
e
m
p
lo
y
e
d
b
y
c
om
bi
n
i
ng
al
l
f
i
t
nes
s
f
unc
t
i
ons
and
w
e
i
g
ht
ed
us
i
ng
w
ei
gh
i
ng
f
ac
t
or
.
T
her
ef
or
e,
t
he
ov
er
al
l
o
bj
ec
t
i
v
e f
unc
t
i
o
n c
an
be
r
e
pr
es
en
t
ed
as
:
=
(
1
×
1
)
+
(
2
×
2
)
(
3)
I
n
w
e
i
ght
ed
s
um
m
et
hod,
s
u
m
of
al
l
w
e
i
gh
i
ng
f
ac
t
or
us
ed
s
ho
ul
d
be
equ
al
t
o
1.
T
her
ef
or
e,
t
he s
um
of
w
ei
g
hi
n
g f
ac
t
or
s
i
s
ex
pr
es
s
ed
a
s:
1
+
2
=
1
(
4)
S
V
C
i
s
a de
v
i
c
e
w
hi
c
h i
s
c
apab
l
e of
f
eedi
ng
or
dr
a
w
i
ng r
eac
t
i
v
e po
w
er
f
r
o
m
a
po
w
er
s
y
s
t
em
.
I
n t
hi
s
paper
,
t
he S
V
C
is
m
o
d
e
lle
d
as
an i
de
al
neg
at
i
v
e r
eac
t
i
v
e
po
w
er
l
oad.
P
os
i
t
i
v
e
v
a
l
ue
of
S
V
C
r
at
i
ng
i
nd
i
c
at
es
t
he
r
eac
t
i
v
e
po
w
er
bei
n
g
i
nj
ec
t
ed
f
r
o
m
S
V
C
i
nt
o
t
h
e
s
y
s
t
em
w
hi
l
e
nega
t
i
v
e
v
a
l
ue
of
S
V
C
r
at
i
n
g i
n
di
c
at
ed t
h
e r
eac
t
i
v
e
po
w
er
d
r
a
wn
f
r
om
t
he s
y
s
t
em
.
T
he s
i
z
i
n
g of
S
V
C
i
s
l
i
m
i
t
ed b
y
t
he c
ap
ac
i
t
y
of
t
he
S
V
C
an
d r
epr
es
e
nt
ed
b
y
:
≤
≤
(
5)
T
C
S
C
i
s
a de
v
i
c
e
w
h
i
c
h
c
an m
odi
f
y
i
t
s
r
eac
t
anc
e
t
o m
odi
f
y
t
he r
e
ac
t
anc
e
of
t
he
t
r
ans
m
i
s
s
i
on
l
i
ne.
I
n
t
hi
s
p
a
per
,
T
C
S
C
i
s
m
odel
l
ed
as
t
he
c
om
pens
at
i
on
r
at
i
o.
V
ar
i
ous
l
i
t
er
at
ur
e
has
s
ugges
t
e
d t
hat
t
h
e v
a
l
ue of
T
C
S
C
c
o
m
pens
at
i
o
n r
at
i
o s
hou
l
d b
e m
ai
nt
ai
n
ed
i
n t
he r
an
ge of
-
0.
8
up
t
o
0.
2
t
o
a
v
o
i
d
ov
er
c
o
m
pens
at
i
on
pr
o
bl
em
.
T
he
r
ang
e
of
T
C
S
C
c
om
pens
at
i
o
n
r
at
i
o
c
an
be ex
pr
es
s
ed
as
:
≤
≤
(
6)
T
o m
ai
nt
ai
n
ac
c
ep
t
ab
l
e v
ol
t
age pr
of
i
l
e,
a
l
l
b
us
v
o
l
t
ag
e
s
houl
d
be m
ai
nt
ai
ne
d
i
n b
e
t
w
een
t
he per
m
i
s
s
i
bl
e m
i
ni
m
u
m
and m
ax
i
m
u
m
v
ol
t
age
v
a
l
ue.
U
nder
-
v
ol
t
ag
e an
d
ov
er
-
v
ol
t
age
c
ondi
t
i
o
n s
hou
l
d
be a
v
oi
d
e
d
s
i
nc
e bot
h c
ond
i
t
i
on
s
c
an
c
aus
e
har
m
t
o t
he po
w
e
r
s
y
s
t
em
.
T
he
per
m
i
s
s
i
bl
e r
ang
e of
bus
v
o
l
t
ag
e
v
al
ue
i
s
r
epr
es
e
nt
ed
a
s
f
o
llo
w
s
:
≤
≤
(
7)
V
ar
i
ous
r
ef
er
enc
es
hav
e r
epor
t
e
d t
ha
t
t
he
al
l
o
w
e
d d
ev
i
at
i
on of
bus
v
ol
t
ag
e s
houl
d
be
k
ept
i
n t
he r
ang
e at
10%
a
b
ov
e a
nd b
el
o
w
t
he r
at
ed bu
s
v
ol
t
a
ge
[
1
3]
.
T
her
ef
or
e,
t
he per
m
i
s
s
i
bl
e
bus
v
ol
t
age r
ang
e us
ed
i
n
t
hi
s
pa
per
is
0.
9
0 p.
u.
a
nd 1
.
10 p
.
u.
2.
2.
C
h
ao
s
E
m
b
e
d
d
e
d
S
y
m
b
i
o
ti
c
O
r
g
a
n
i
s
m
s
S
e
a
r
c
h
T
o s
ol
v
e
opt
i
m
al
F
A
C
T
S
dev
i
c
e al
l
oc
at
i
on
i
n
a
t
r
a
ns
m
i
s
s
i
on
s
y
s
t
em
f
or
v
ol
t
ag
e
pr
of
i
l
e
and
v
ol
t
age
s
ec
ur
i
t
y
i
m
pr
ov
em
ent
,
C
S
O
S
has
be
en
i
m
pl
e
m
ent
ed
t
o
obt
a
i
n
t
h
e
opt
i
m
al
s
ol
ut
i
on
t
o t
h
e pr
o
bl
em
.
C
S
O
S
w
a
s
dev
el
o
pe
d b
y
S
.
S
ah
a
and
V
.
Muk
her
j
ee i
n
20
16
[
15]
t
o
so
l
ve
opt
i
m
al
pl
ac
em
ent
and
s
i
z
i
ng
of
di
s
t
r
i
but
ed
ge
ner
at
or
s
i
n
a
r
adi
a
l
di
s
t
r
i
b
ut
i
on
s
y
s
t
em
.
C
S
O
S
i
s
dev
el
ope
d bas
ed on n
ov
el
S
O
S
al
gor
i
t
hm
,
w
hi
c
h em
ul
at
e
s
t
he i
nt
er
ac
t
i
on of
or
gani
s
m
’
s
r
el
i
a
nc
e
on
ot
h
er
s
pec
i
es
i
n
a
n
ec
o
s
y
s
t
em
f
or
i
t
s
s
ur
v
i
v
al
a
nd
s
us
t
enanc
e.
T
he
det
ai
l
pr
o
c
es
s
of
C
S
O
S
i
n s
ear
c
h
i
ng
t
he
opt
i
m
al
F
A
C
T
S
dev
i
c
e a
l
l
oc
at
i
on
i
s
s
u
m
m
ar
i
z
e
d as
f
ol
l
o
w
s
:
S
t
ep
1:
I
ni
t
i
a
l
i
z
at
i
on
p
has
e.
In
t
hi
s
phas
e,
a
s
et
of
v
ar
i
a
bl
es
c
ons
i
s
t
s
of
S
V
C
s
i
z
i
ng
a
nd
T
C
S
C
c
o
m
pens
at
i
on r
a
t
i
o
ar
e r
an
dom
l
y
g
ener
at
ed
as
s
t
at
ed
i
n (
5
)
and (
6
)
.
T
he gener
at
ed
v
a
l
ue s
ho
ul
d al
l
o
w
t
he
p
o
w
er
f
l
ow
s
o
l
ut
i
on
t
o c
on
v
er
ge
an
d
y
i
e
l
d
l
o
w
er
f
i
t
nes
s
v
a
l
ue
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
EC
S
IS
S
N
:
2
502
-
4
752
C
haos
E
mb
edd
ed
S
y
mb
i
ot
i
c
O
r
gani
s
ms
S
ear
c
h
…
(
Mo
hama
d K
ha
i
r
u
z
z
a
ma
n M
.Z
)
149
c
o
m
par
ed t
o f
i
t
n
es
s
v
a
l
u
e
w
i
t
hou
t
t
he F
A
C
T
S
d
ev
i
c
es
.
I
n
t
h
i
s
s
t
ud
y
,
20
ac
c
e
pt
ed
or
gan
i
s
m
s
ar
e
c
ons
i
der
ed
as
1 ec
os
y
s
t
em
and us
ed f
or
t
he
opt
i
m
i
s
at
i
on
pr
oc
es
s
.
S
t
ep
2:
B
es
t
or
g
an
i
s
m
i
dent
i
f
i
c
at
i
o
n
ph
as
e.
D
ur
i
n
g t
h
i
s
ph
as
e,
an
or
ga
ni
s
m
w
i
t
h
t
he
m
i
ni
m
al
f
i
t
nes
s
v
a
l
ue
is
c
hos
en
t
o
b
e t
he
bes
t
or
gan
i
s
m
.
S
et
i
e
qua
l
t
o
1.
S
t
ep
3:
Mut
u
al
i
s
m
phas
e.
I
n
t
hi
s
p
has
e,
i
t
h
s
et
of
F
A
C
T
S
de
v
i
c
e
r
at
i
ng
X
i
i
s
c
hos
en
.
T
he
n,
j
th
s
et
of
F
A
C
T
S
dev
i
c
e r
at
i
n
g
X
j
i
s
c
hos
en r
andom
l
y
f
r
om
t
he ec
os
y
s
t
em
w
her
e
j
≠
i
.
B
ot
h s
et
s
of
t
he de
v
i
c
e r
at
i
ng ar
e t
hen m
odi
f
i
ed bas
ed on t
h
ei
r
m
ut
ual
r
el
a
t
i
on
s
hi
p.
B
ot
h
m
odi
f
i
ed F
A
C
T
S
de
v
i
c
e r
at
i
ng
s
ar
e
c
om
par
ed
t
o t
h
ei
r
or
i
g
i
n
al
F
A
C
T
S
d
ev
i
c
e
r
es
pec
t
i
v
el
y
i
n t
er
m
s
of
t
h
ei
r
f
i
t
nes
s
v
a
l
u
e.
M
odi
f
i
e
d
F
A
C
T
S
dev
i
c
e r
at
i
ng
r
epl
ac
e
s
t
hei
r
or
i
gi
nal
r
at
i
n
gs
i
f
t
he
y
hav
e
a
bet
t
er
f
i
t
nes
s
v
al
u
e.
T
he
m
ut
ual
r
el
at
i
ons
hi
p
of
t
he
or
gan
i
s
m
s
i
s
ex
pr
es
s
ed
as
:
,
=
+
(
0
,
1
)
×
(
−
×
1
)
(
8)
,
=
+
(
0
,
1
)
×
(
−
×
2
)
(
9)
=
+
2
(
10)
w
her
e
MV
i
s
t
he m
ut
ual
v
ec
t
or
,
X
i
,
n
ew
a
nd
X
j
,
n
ew
ar
e
t
he n
e
w
s
et
of
S
V
C
s
i
z
i
ng
an
d
T
CS
C c
o
m
pens
at
i
o
n r
at
i
o
pr
oduc
e
d f
r
o
m
t
he
m
ut
ual
r
el
at
i
ons
h
i
p.
T
he
r
an
d
(
0
,
1)
is
def
i
ned
as
a
r
and
om
nu
m
ber
r
an
ged
f
r
om
0
t
o
1,
X
b
es
t
i
s
t
h
e b
es
t
s
et
of
S
V
C
s
i
z
i
ng
and T
C
S
C
c
om
pens
at
i
on
r
at
i
o
w
h
i
c
h
y
i
el
d
t
h
e b
es
t
f
i
t
nes
s
v
a
l
u
e.
BF
1
and
BF
2
a
r
e t
he
benef
i
t
f
ac
t
or
w
h
i
c
h
i
s
an
i
n
t
eger
r
a
ndom
num
ber
ei
t
he
r
1 or
2.
S
t
ep
4:
C
om
m
ens
al
i
s
m
phas
e.
D
ur
i
ng
t
hi
s
phas
e,
i
t
h
s
e
t
of
F
A
C
T
S
dev
i
c
e
r
at
i
ng
X
i
i
s
ch
o
se
n
.
T
hen,
j
th
s
et
of
F
A
C
T
S
dev
i
c
e r
at
i
ng
X
j
i
s
r
and
om
l
y
c
h
o
s
en
f
r
o
m
t
he ec
os
y
s
t
em
w
h
i
c
h
j
≠
i
.
T
hen,
X
i
i
s
t
hen m
odi
f
i
ed
w
i
t
h t
he as
s
i
s
t
a
nc
e of
X
j
us
i
ng c
om
m
ens
al
s
y
m
bi
os
i
s
r
el
at
i
ons
h
i
p.
T
he
m
odi
f
i
ed
X
i
r
ep
l
ac
e
s
t
h
e
or
i
gi
nal
X
i
i
f
t
he
m
odi
f
i
ed
X
i
pr
o
v
i
des
b
et
t
er
f
i
t
nes
s
v
al
u
e
c
om
par
ed
t
o
t
he
or
i
g
i
na
l
X
i
.
Ma
t
hem
at
i
c
a
l
ex
pr
es
s
i
on
us
ed
t
o
m
odel
t
he
pr
oduc
t
i
on
of
ne
w
X
i
i
s
s
t
at
ed as
f
ol
l
o
w
:
,
=
+
(
−
1
,
1
)
×
−
(
11)
w
her
e
X
i
,
n
ew
i
s
t
h
e m
odi
f
i
ed
s
et
of
F
A
C
T
S
de
v
i
c
e
r
at
i
ng,
r
and(
-
1,
1)
i
s
a r
and
om
num
ber
i
n t
he r
a
nge
of
-
1 t
o
1,
X
b
es
t
i
s
t
he
bes
t
s
e
t
of
F
A
C
T
S
d
ev
i
c
e r
at
i
ng
w
h
i
c
h
y
i
e
l
d
t
he
bes
t
f
i
t
nes
s
v
a
l
ue.
S
t
ep
5:
P
ar
as
i
t
i
s
m
phas
e.
I
n par
a
s
i
t
i
s
m
phas
e,
i
th
s
et
of
F
A
C
T
S
dev
i
c
e r
at
i
ng
X
i
i
s
c
hos
en
.
T
hen,
j
th
s
et
of
F
A
C
T
S
dev
i
c
e
r
at
i
n
g
X
j
i
s
t
hen
r
and
o
m
l
y
c
hos
en
f
r
o
m
t
he
ec
os
y
s
t
e
m
w
her
e
j
≠
i
.
T
hen,
a
par
as
i
t
e
v
ec
t
or
i
s
c
r
eat
ed
by
d
u
pl
i
c
at
i
ng
X
i
.
Lat
er
,
r
an
dom
di
m
ens
i
on
of
t
h
e
p
ar
as
i
t
e
i
s
m
odi
f
i
ed
us
i
ng
r
and
om
v
al
u
e
of
S
V
C
s
i
z
i
ng
an
d/
or
T
CS
C
c
o
m
pens
at
i
on
r
at
i
o.
T
he
f
i
t
nes
s
v
a
l
u
e
of
t
he
par
as
i
t
e
i
s
t
hen
ev
al
uat
e
d
.
If
th
e
p
a
r
a
s
i
te
has
a b
et
t
er
f
i
t
n
es
s
v
a
l
u
e
X
j
,
t
he
n t
h
e par
as
i
t
e
r
e
pl
ac
e
s
X
j
.
S
t
ep
6:
B
es
t
or
ga
ni
s
m
i
dent
i
f
i
c
at
i
o
n.
A
t
t
h
i
s
phas
e,
t
he s
et
o
f
F
A
C
T
S
dev
i
c
e r
at
i
ng
w
i
t
h t
he
bes
t
f
i
t
nes
s
v
a
l
u
e
i
s ch
o
se
n
as
t
he
bes
t
or
g
ani
s
m
.
I
f
al
l
or
ga
ni
s
m
s
hav
e un
der
gone
s
t
ep
3
un
t
i
l
s
t
ep
6,
t
he
n
pr
oc
eed
t
o
s
t
ep
7.
O
t
her
w
i
s
e
,
i
nc
r
eas
e
i
b
y
1
an
d
go
b
a
c
k
t
o
s
t
ep 3.
S
t
ep
7:
C
haot
i
c
l
oc
al
s
e
ar
c
h
ph
as
e.
A
t
t
h
i
s
ph
as
e,
c
ha
ot
i
c
l
o
c
al
s
ear
c
h
(
C
L
S
)
is
in
it
i
a
t
e
d
.
T
o
s
t
ar
t
C
LS
,
a c
o
unt
er
f
or
C
LS
i
t
er
at
i
o
n c
ou
nt
er
is
in
it
i
a
li
z
e
d
a
nd a
c
ha
ot
i
c
v
ar
i
a
bl
e
is
gener
at
ed
f
r
o
m
a r
andom
n
um
ber
i
n t
he r
ang
e of
0 t
o
1.
I
t
c
an
be ex
pr
es
s
ed
as
:
=
1
(
12)
=
(
0
,
1
)
(
13)
S
t
ep
8:
C
haot
i
c
v
ar
i
a
bl
e
up
dat
e
p
has
e.
D
ur
i
ng
t
hi
s
p
has
e,
t
he c
hao
t
i
c
v
ar
i
a
bl
e
is
u
pd
at
ed
us
i
ng
P
i
ec
e
w
i
s
e
Li
near
C
haot
i
c
M
ap (
P
LC
M)
.
A
c
o
nt
r
ol
par
am
et
er
p
c
ont
r
o
l
s
t
he
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
25
02
-
4
752
I
J
E
EC
S
V
o
l.
8
,
N
o.
1,
O
c
t
o
ber
20
17
:
1
46
–
1
53
150
upda
t
i
n
g
pr
oc
es
s
.
R
ef
er
enc
e
[
16]
s
ugges
t
e
d
t
ha
t
t
h
e
v
a
l
ue
of
p
c
an
be
c
hos
en
i
n
t
he
in
t
e
r
v
a
l
of
[
]
5
.
0
,
0
∈
p
.
T
he P
L
C
M c
a
n
be m
at
hem
at
i
c
al
l
y
ex
pr
es
s
ed
as
:
+
1
=
⎩
⎨
⎧
∈
(
0
,
)
(
1
−
)
(
1
−
)
∈
(
,
1
)
(
14)
S
t
ep
9:
C
haot
i
c
v
ar
i
ab
l
e m
appi
ng
phas
e.
T
he c
haot
i
c
v
ar
i
ab
l
e gener
a
t
ed at
s
t
ep 8 i
s
t
hen
m
apped
bac
k
t
o
t
he
bes
t
o
r
gani
s
m
obt
ai
ned
f
r
o
m
s
t
ep
6.
A
f
t
er
t
he
v
ar
i
a
bl
e
h
as
been
m
apped
,
f
i
t
nes
s
v
al
ue
of
t
h
e m
apped
v
ar
i
ab
l
e
i
s
t
h
en c
om
put
ed.
T
he v
ar
i
a
bl
e m
appi
n
g
c
an
be m
at
hem
at
i
c
al
l
y
ex
pr
es
s
ed
as
:
+
1
=
+
(
2
+
1
−
1
)
(
15)
S
t
ep
10:
I
f
t
he
m
apped
v
ar
i
ab
l
e
h
as
a
bet
t
er
f
i
t
nes
s
v
a
l
ue
c
om
par
ed
t
o
t
he
f
i
t
n
es
s
v
a
l
ue
of
t
he
bes
t
or
gan
i
s
m
obt
ai
ned
f
r
om
s
t
ep
6,
t
hen
r
epl
ac
e
t
h
e
bes
t
or
gan
i
s
m
w
i
t
h
t
he
m
a
pped
v
ar
i
ab
l
e an
d go t
o nex
t
s
t
ep.
O
t
h
er
w
i
s
e,
g
o bac
k
t
o s
t
ep 8 un
t
i
l
m
ax
i
m
u
m
C
L
S
i
t
er
at
i
on
c
oun
t
er
i
s
r
e
ac
hed
.
S
t
ep
11:
R
educ
e
t
he
c
haot
i
c
s
ear
c
h
s
pac
e
r
ad
i
us
b
y
a f
ac
t
or
of
r
andom
num
ber
i
n
t
he
r
ange
f
r
o
m
0 t
o 1,
an
d i
t
c
an
be e
x
pr
es
s
ed
as
:
=
×
(
16)
=
(
0
,
1
)
(
17)
St
e
p
12:
C
on
v
er
ge
nc
e t
es
t
.
C
hec
k
i
f
t
he
opt
i
m
i
s
at
i
on
pr
oc
e
s
s
has
r
eac
hed i
t
s
m
ax
i
m
u
m
i
t
er
at
i
on
.
I
f
not
,
go
bac
k
t
o s
t
ep 3.
O
t
her
w
i
s
e
,
ha
l
t
t
he
o
p
t
im
is
a
t
io
n
pr
oc
es
s
.
3.
R
e
su
l
t
s an
d
A
n
al
y
s
i
s
I
n
t
hi
s
r
es
e
ar
c
h,
t
he
pr
opo
s
ed
C
S
O
S
i
s
t
es
t
e
d
on
I
E
E
E
2
6
-
bus
R
e
l
i
ab
i
l
i
t
y
T
e
s
t
S
ys
t
e
m
(
R
T
S
)
t
o s
ol
v
e opt
i
m
al
F
A
C
T
S
dev
i
c
e a
l
l
oc
at
i
on pr
o
bl
em
i
n t
he ef
f
or
t
t
o i
m
pr
o
v
e t
h
e v
o
l
t
a
g
e
pr
of
i
l
e a
nd
v
o
l
t
a
ge s
ec
ur
i
t
y
of
t
he t
es
t
s
y
s
t
em
.
T
he t
es
t
s
y
s
t
em
c
o
m
pr
i
s
es
6 gener
at
i
o
n un
i
t
s
and 17
l
oa
d c
ent
r
es
.
D
ur
i
n
g t
he op
t
i
m
i
s
at
i
on pr
oc
es
s
,
t
he num
ber
of
or
gani
s
m
s
ar
e
s
et
t
o 20
w
hi
l
e t
he
num
ber
of
S
V
C
a
nd T
C
S
C
i
ns
t
a
l
l
ed
i
n t
he
t
e
s
t
s
y
s
t
em
i
s se
t
at
3
un
i
t
s
.
T
he
m
ax
i
m
u
m
i
t
er
at
i
on
of
t
he
op
t
i
m
i
s
at
i
o
n pr
oc
es
s
is
lim
it
e
d
at
1
00
i
t
er
a
t
i
o
ns
.
T
o t
es
t
t
he r
o
b
us
t
nes
s
of
t
he
o
p
t
im
is
a
t
io
n
t
ec
h
ni
que,
t
he
o
p
t
im
is
a
t
io
n
pr
o
bl
em
i
s
s
ubj
ec
t
ed
t
o
di
f
f
er
ent
c
as
e s
t
ud
i
es
i
n ef
f
or
t
t
o
t
es
t
w
h
et
h
er
t
h
e
o
pt
i
m
i
s
at
i
on
t
ec
hn
i
qu
e
c
an
s
uc
c
es
s
f
ul
l
y
pr
o
v
i
de opt
i
m
al
s
ol
u
t
i
on i
n v
ar
i
ous
po
w
er
s
y
s
t
em
oper
at
i
on c
ond
i
t
i
ons
.
C
as
e s
t
ud
i
es
c
ons
i
d
er
ed
i
n
t
hi
s
r
es
e
ar
c
h
ar
e l
i
s
t
e
d as
f
o
llo
w
s
:
C
as
e 1
:
I
n
t
h
i
s
s
c
enar
i
o,
t
he
p
o
w
er
s
y
s
t
em
i
s
oper
a
t
i
ng
at
i
t
s
nom
i
nal
c
o
ndi
t
i
on.
T
he
t
es
t
s
ys
t
e
m
i
s
not
s
ubj
ec
t
ed
t
o
an
y
c
han
ges
.
T
hi
s
c
ondi
t
i
on i
s
k
now
n as
bas
e c
as
e
c
ondi
t
i
o
n.
C
as
e 2
:
I
n t
h
i
s
s
c
enar
i
o,
t
h
e r
eac
t
i
v
e
po
w
er
l
o
ad a
t
bus
18
i
s
r
educ
ed t
o 1
0M
V
A
r
w
hi
l
e
k
eepi
ng
ot
her
par
am
et
er
s
of
t
he t
es
t
s
y
s
t
em
as
i
n
i
t
s
bas
e c
as
e
c
ond
i
t
i
on.
T
hi
s
c
ondi
t
i
o
n i
s
k
no
w
n
as
l
i
ght
-
l
oad
i
ng c
o
nd
i
t
i
on.
C
as
e 3
:
I
n
t
hi
s
s
c
enar
i
o,
t
he
r
eac
t
i
v
e
po
w
er
l
o
ad
at
bus
17
i
s
i
nc
r
eas
ed
t
o
10
0M
V
A
r
w
hi
l
e
k
eepi
ng ot
her
par
am
et
er
s
of
t
he t
es
t
s
y
s
t
em
as
i
n
i
t
s
bas
e c
as
e
c
ond
i
t
i
on.
T
hi
s
c
ondi
t
i
o
n i
s
k
no
w
n
as
hea
v
y
-
l
o
ad
i
ng c
o
nd
i
t
i
on.
T
o obs
er
v
e
t
he
v
ar
i
at
i
on
of
r
es
ul
t
s
pr
o
duc
ed
b
y
t
he
o
p
t
im
is
a
t
io
n
al
gor
i
t
hm
,
eac
h
c
as
e
s
t
ud
y
i
s
ex
ec
ut
ed
f
or
20 t
i
m
e
s
.
U
pon t
he c
om
pl
et
i
o
n of
t
he ex
ec
ut
i
on
,
r
es
ul
t
s
ar
e ana
l
y
s
e
d
.
T
he
ana
l
y
s
e
d
dat
a
c
ons
i
s
t
of
t
he
f
i
t
nes
s
v
al
ue
w
h
i
c
h
c
om
pr
i
s
es
t
he
t
ot
al
v
o
l
t
ag
e
de
v
i
at
i
on
i
nd
ex
i
n
t
he t
es
t
s
y
s
t
em
and t
he w
o
r
s
t
F
V
S
I
v
al
ue i
n t
h
e s
y
s
t
e
m
.
T
o i
l
l
us
t
r
at
e t
h
e ef
f
ec
t
i
v
enes
s
of
C
S
O
S
i
n
s
ol
v
i
ng
t
h
i
s
pr
ob
l
em
,
t
he
pr
obl
em
is
s
ol
v
e
d
us
i
n
g
P
S
O
and
E
P
w
i
t
h
t
he
s
i
m
i
l
a
r
c
as
e
s
t
udi
es
and t
he r
es
u
l
t
s
o
bt
a
i
ne
d
is
c
o
m
par
ed
w
i
t
h C
S
O
S
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
EC
S
IS
S
N
:
2
502
-
4
752
C
haos
E
mb
edd
ed
S
y
mb
i
ot
i
c
O
r
gani
s
ms
S
ear
c
h
…
(
Mo
hama
d K
ha
i
r
u
z
z
a
ma
n M
.Z
)
151
3.
1.
B
ase
C
as
e C
o
n
d
i
t
i
o
n
D
ur
i
n
g t
h
i
s
c
ond
i
t
i
on
,
t
h
e
po
w
er
s
y
s
t
em
is
op
er
at
es
at
i
t
s
nom
i
na
l
c
on
di
t
i
on
a
nd n
o
c
hanges
has
b
ee
n s
ubj
ec
t
e
d
t
o
t
he
po
w
er
s
y
s
t
em
.
D
ur
i
ng
t
h
i
s
c
ond
i
t
i
on,
S
V
C
is
i
n
s
t
a
ll
e
d
at
b
us
24,
25
and
2
3 a
nd
t
he
T
C
S
C
s
ar
e i
ns
t
a
l
l
ed
at
t
r
ans
m
i
s
s
i
on
l
i
nes
w
hi
c
h
c
onn
ec
t
b
u
s
4 t
o
b
us
12
,
bus
4
t
o
bus
8,
and
bus
3
t
o
13.
T
he r
es
ul
t
s
obt
ai
ne
d
f
r
o
m
t
he
o
p
t
im
is
a
t
io
n
al
g
or
i
t
hm
i
s
t
he
n
ana
l
y
s
e
d an
d t
a
bu
l
at
ed as
i
n T
abl
e 1
.
T
abl
e 1.
O
p
t
im
is
a
t
io
n
r
es
ul
t
s
dur
i
ng
bas
e
c
as
e c
ond
i
t
i
o
n
P
ar
a
m
et
er
s
T
ec
hni
que
R
es
ul
t
s
T
ot
al
V
di
W
or
s
t
F
V
S
I
F
i
t
nes
s
v
al
ue
P
re
-
opt
i
m
i
z
ed
0.
00483
0.
35376
0.
17929
B
es
t
po
s
t
-
opt
i
m
i
z
ed
CS
O
S
0.
00222
0.
33861
0.
17042
PSO
0.
00282
0.
33896
0.
17089
EP
0.
00196
0.
34112
0.
17154
W
or
s
t
p
os
t
-
op
t
i
m
i
z
ed
CS
O
S
0.
00179
0.
34040
0.
17109
PSO
0.
00197
0.
34219
0.
17208
EP
0.
00199
0.
34208
0.
17203
R
ef
er
r
i
ng t
o T
abl
e 1
,
i
t
c
a
n
be
o
bs
er
v
e
d
t
h
a
t
C
SO
S,
P
SO
a
n
d
E
P
w
er
e m
anagi
n
g t
o
s
ol
v
e t
he
F
A
C
T
S
d
ev
i
c
e
al
l
oc
at
i
on
pr
ob
l
em
w
i
t
h
C
S
O
S
pr
ov
i
d
i
ng
hi
gher
s
ol
ut
i
o
n
qu
al
i
t
y
c
o
m
par
ed t
o
P
S
O
and
E
P
.
A
f
t
er
2
0 ex
ec
u
t
i
o
ns
of
t
h
e
o
p
t
im
is
a
t
io
n
pr
oc
es
s
,
t
h
e bes
t
r
es
ul
t
s
pr
oduc
e
d
r
ev
e
al
e
d
t
hat
C
S
O
S
has
per
f
or
m
ed
bet
t
er
i
n
s
ol
v
i
ng
t
h
e
obj
ec
t
i
v
e
f
unc
t
i
on
c
om
par
ed
t
o P
S
O
a
nd
E
P
.
H
o
w
e
v
er
,
w
hi
l
e
E
P
has
ac
hi
ev
ed t
he
l
o
w
es
t
t
ot
al
V
d
i
,
i
t
al
s
o
y
i
e
l
d
ed t
he
hi
g
hes
t
w
or
s
t
F
V
S
I
v
a
l
u
e
w
hi
c
h
i
nd
i
c
at
es
i
t
c
an
pr
oduc
e
r
es
ul
t
s
w
hi
c
h
s
i
g
ni
f
i
c
ant
l
y
i
m
pr
ov
e
t
he
v
o
l
t
a
ge
pr
of
i
l
e
of
t
he
s
y
s
t
em
at
t
h
e
c
os
t
of
i
t
s
v
ol
t
ag
e s
t
a
bi
l
i
t
y
i
nd
ex
.
T
he
w
or
s
t
r
es
ul
t
s
y
i
e
l
d
ed
b
y
t
he
o
p
t
im
is
a
t
io
n
pr
oc
es
s
i
nd
i
c
a
t
es
t
ha
t
C
S
O
S
has
m
anag
ed
t
o
pr
o
duc
e
bet
t
er
r
es
u
l
t
s
c
o
m
par
ed
t
o
PSO
a
n
d
EP
i
n
t
er
m
s
o
f
f
i
t
nes
s
v
a
l
ue,
t
ot
al
V
d
i
and
w
or
s
t
F
V
S
I
v
a
l
u
e.
C
S
O
S
c
a
n
i
m
pr
ov
e
t
h
e
v
o
l
t
ag
e pr
of
i
l
e a
nd
v
o
l
t
a
ge
s
t
abi
l
i
t
y
b
et
t
er
t
ha
n ot
her
t
e
c
hni
q
ues
a
l
t
ho
ug
h at
i
s
w
or
s
t
.
3
.2
. L
ig
h
t
-
L
o
a
d
i
n
g
C
o
n
d
i
t
i
o
n
I
n t
hi
s
c
ond
i
t
i
on,
t
he r
eac
t
i
v
e po
w
er
l
oa
d at
bus
18 of
t
he t
es
t
s
y
s
t
em
i
s
r
educ
ed t
o
10M
V
A
r
w
hi
l
e m
ai
nt
a
i
n
i
n
g
ot
her
p
ar
am
et
er
s
as
i
n
i
t
s
b
as
e c
as
e c
ond
i
t
i
on.
T
he l
o
c
a
t
io
n
s
o
f
SV
C
t
o be i
ns
t
a
l
l
ed
ar
e
bus
24,
bus
25,
and bus
23.
A
t
t
he s
am
e t
i
m
e,
T
C
S
C
s
w
er
e i
ns
t
al
l
e
d
on
t
r
ans
m
i
s
s
i
on
l
i
n
es
c
onnec
t
i
ng
bus
4
t
o
bus
12
,
bus
4
t
o
bus
8
and
bus
3
t
o
b
us
1
3.
T
he
r
es
ul
t
s
obt
a
i
ne
d f
r
om
t
he
opt
i
m
i
s
at
i
on
pr
oc
es
s
ar
e t
a
bu
l
at
ed
a
s
i
n T
abl
e
2.
T
abl
e 2.
O
p
t
im
is
a
t
io
n
r
es
ul
t
s
dur
i
ng
l
i
gh
t
-
l
oa
di
ng c
o
ndi
t
i
on
P
ar
a
m
et
er
s
T
ec
hni
que
R
es
ul
t
s
T
ot
al
V
di
W
or
s
t
F
V
S
I
F
i
t
nes
s
v
al
ue
P
re
-
opt
i
m
i
z
ed
0.
00445
0.
35258
0.
17851
B
es
t
po
s
t
-
opt
i
m
i
z
ed
CS
O
S
0.
00182
0.
33945
0.
17064
PSO
0.
00189
0.
34024
0.
17107
EP
0.
00289
0.
34198
0.
17244
W
or
s
t
p
os
t
-
op
t
i
m
i
z
ed
CS
O
S
0.
00252
0.
33975
0.
17113
PSO
0.
00375
0.
34137
0.
17256
EP
0.
00289
0.
34198
0.
17244
T
abl
e
2
i
l
l
us
t
r
at
es
t
he
r
es
ul
t
s
of
t
he
opt
i
m
i
s
at
i
on
pr
oc
e
s
s
dur
i
ng
l
i
ght
-
l
oa
di
ng
c
on
di
t
i
on.
F
r
o
m
t
he r
es
u
l
t
s
o
bt
a
i
ne
d,
ev
en
t
ho
ugh
C
S
O
S
,
P
S
O
and
E
P
c
a
n s
o
l
v
e t
h
e
opt
i
m
al
F
A
C
T
S
dev
i
c
e
al
l
oc
at
i
on
pr
o
bl
em
,
C
S
O
S
has
pr
o
v
en
i
t
s
s
upe
r
i
or
i
t
y
ov
er
P
S
O
and
E
P
i
n
pr
o
v
i
d
i
n
g
t
he
bes
t
o
p
t
im
is
a
t
io
n
r
es
u
l
t
s
b
y
ac
hi
ev
i
n
g
t
he
l
o
w
es
t
f
i
t
nes
s
v
a
l
ue
w
i
t
h
m
i
ni
m
al
t
o
t
al
V
d
i
and
l
o
w
es
t
w
or
s
t
F
V
S
I
v
a
l
u
e.
T
he s
am
e s
c
enar
i
o c
a
n
be
obs
er
v
e
d
i
n t
he
w
or
s
t
o
p
t
im
is
a
t
io
n
r
e
s
u
lt
s
y
ie
ld
e
d
b
y
t
h
e opt
i
m
i
s
at
i
on a
l
gor
i
t
h
m
s
.
T
her
ef
or
e,
C
S
O
S
per
f
or
m
s
bet
t
er
t
han
P
S
O
an
d
E
P
i
n
s
ol
v
i
n
g
opt
i
m
al
F
A
C
T
S
d
e
v
i
c
e
al
l
o
c
at
i
on
pr
ob
l
em
dur
i
ng
l
i
ght
-
l
oa
di
n
g c
on
di
t
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
25
02
-
4
752
I
J
E
EC
S
V
o
l.
8
,
N
o.
1,
O
c
t
o
ber
20
17
:
1
46
–
1
53
152
3.
3.
H
eav
y
-
L
o
a
d
i
n
g
C
o
n
d
i
ti
o
n
D
ur
i
n
g t
h
i
s
c
as
e,
t
h
e r
eac
t
i
v
e po
w
er
l
oad
at
bus
1
7
w
as
i
nc
r
eas
e
d
t
o
10
0M
V
A
r
w
h
i
l
e
m
ai
nt
ai
n
i
ng
ot
h
er
p
ar
am
et
er
s
as
i
n
i
t
s
bas
e
c
as
e
c
on
di
t
i
on.
S
V
C
i
s
pr
o
pos
ed
t
o
b
e
in
s
t
a
lle
d
a
t
bus
17,
bus
24
,
and
b
us
25.
T
he
T
C
S
C
s
ar
e
i
ns
t
al
l
e
d
at
t
r
ans
m
i
s
s
i
on
l
i
nes
c
onn
ec
t
i
ng
b
us
4
t
o
bus
12,
bus
4 t
o bus
8 a
nd b
us
16
t
o
bus
1
7.
T
he
opt
i
m
i
s
at
i
on
r
e
su
l
t
s
ar
e
t
abu
l
at
e
d
a
s
in
T
abl
e 3.
T
abl
e 3.
O
p
t
im
is
a
t
io
n
r
es
ul
t
s
dur
i
ng
he
av
y
-
l
oad
i
n
g c
on
di
t
i
on
P
ar
a
m
et
er
s
T
ec
hni
que
R
es
ul
t
s
T
ot
al
V
di
W
or
s
t
F
V
S
I
F
i
t
nes
s
v
al
ue
P
re
-
opt
i
m
i
z
ed
0.
00772
0.
35731
0.
18251
B
es
t
po
s
t
-
opt
i
m
i
z
ed
CS
O
S
0.
00154
0.
33959
0.
17057
PSO
0.
00170
0.
34095
0.
17132
EP
0.
00355
0.
34176
0.
17266
W
or
s
t
p
os
t
-
op
t
i
m
i
z
ed
CS
O
S
0.
00168
0.
34004
0.
17086
PSO
0.
00330
0.
34380
0.
173
55
EP
0.
00355
0.
34176
0.
17266
A
s
s
een
i
n
T
abl
e
3,
C
S
O
S
m
anaged
t
o
pr
o
v
i
de
t
he
h
i
ghes
t
qua
l
i
t
y
s
ol
ut
i
on
am
ong
t
he
bes
t
pos
t
-
o
pt
i
m
i
z
e
d
r
es
ul
t
s
pr
ov
i
de
d
b
y
C
S
O
S
,
P
S
O
and
E
P
.
C
S
O
S
has
s
i
gn
i
f
i
c
ant
l
y
i
m
pr
ov
e
t
he
v
o
l
t
ag
e pr
of
i
l
e of
t
h
e s
y
s
t
em
w
hi
l
e i
m
pr
ov
i
n
g
t
he v
ol
t
a
ge
s
t
a
bi
l
i
t
y
b
y
pr
o
v
i
d
i
n
g
r
eac
t
i
v
e po
w
er
s
uppor
t
on
t
he
he
av
i
l
y
l
o
a
ded
bus
.
C
S
O
S
a
l
s
o m
anaged
t
o
pr
o
v
i
de
a b
et
t
er
s
ol
ut
i
o
n q
ua
l
i
t
y
am
ong
t
he
w
or
s
t
p
os
t
-
o
p
t
im
i
s
ed
r
es
ul
t
s
b
y
ha
v
i
ng
t
he
l
o
w
es
t
f
i
t
n
es
s
v
a
l
u
e
am
ong
ot
h
er
o
p
t
im
is
a
t
io
n
t
ec
hn
i
qu
e
s
.
T
he
r
ef
or
e,
C
S
O
S
c
ap
ab
i
l
i
t
y
t
o
s
ol
v
e
opt
i
m
al
F
A
C
T
S
dev
i
c
e
a
l
l
oc
at
i
on
pr
obl
em
f
or
v
ol
t
age
pr
of
i
l
e
and s
ec
ur
i
t
y
i
m
pr
ov
em
ent
i
n
a he
av
i
l
y
l
oa
ded
po
w
e
r
s
y
s
t
em
has
been
pr
o
v
ed
.
4
.
C
o
n
c
l
u
s
i
o
n
T
he i
m
pl
em
ent
at
i
o
n of
C
haos
E
m
bedded
S
y
m
b
i
ot
i
c
O
r
gani
s
m
s
S
ear
c
h t
ec
hni
q
u
e
in
s
ol
v
i
ng o
pt
i
m
al
F
A
C
T
S
de
v
i
c
e a
l
l
oc
at
i
on
f
or
v
ol
t
a
ge
pr
of
i
l
e an
d
s
ec
ur
i
t
y
i
m
pr
ov
em
ent
pr
obl
em
has
bee
n pr
es
e
nt
e
d
i
n t
h
i
s
paper
.
A
g
ood
v
ol
t
age
pr
of
i
l
e
in
d
ic
a
t
e
s
a h
eal
t
h
y
po
w
er
s
y
s
t
em
w
hi
l
e
an
i
m
pr
ov
em
ent
i
n
v
o
l
t
a
g
e s
ec
ur
i
t
y
c
a
n e
ns
ur
e t
h
a
t
t
he
po
w
er
s
y
s
t
em
i
s
ab
l
e t
o
r
e
t
a
in
it
s
oper
at
i
o
n ev
en i
n c
ont
i
nge
nc
y
c
o
nd
i
t
i
on
w
i
t
ho
ut
ex
c
e
edi
ng i
t
s
s
t
ab
i
l
i
t
y
l
i
m
i
t
s
.
T
o
ac
hi
e
v
e t
h
i
s
,
opt
i
m
al
al
l
oc
at
i
on of
F
A
C
T
S
dev
i
c
es
s
ho
ul
d be ex
e
r
c
i
s
ed t
o av
o
i
d u
nder
-
c
om
pens
at
i
on a
nd
ov
er
-
c
om
pens
at
i
o
n
i
s
s
ues
.
F
r
o
m
t
he
c
as
e
s
t
udi
es
c
onduc
t
e
d
i
n
t
h
i
s
pap
er
,
t
he
pr
op
os
ed
o
p
t
im
is
a
t
io
n
t
ec
hni
que
i
s
c
apab
l
e
of
s
ol
v
i
ng
op
t
i
m
al
F
A
C
T
S
de
v
i
c
e a
l
l
oc
at
i
on
pr
ob
l
em
.
T
he
s
uc
c
es
s
of
t
he
o
p
t
im
is
a
t
io
n
t
ec
hn
i
qu
e t
o r
educ
e
t
he
f
i
t
nes
s
v
a
l
ue,
w
hi
c
h r
ef
l
e
c
t
s
t
he v
o
l
t
age
dev
i
at
i
o
n
i
nd
ex
an
d F
V
S
I
v
al
u
e
i
nd
i
c
at
es
t
he
i
m
pr
ov
e
m
ent
of
t
he
v
o
l
t
ag
e
pr
of
i
l
e
and
t
he
v
ol
t
ag
e
s
ec
ur
i
t
y
i
n
t
he s
y
s
t
em
.
C
o
m
par
at
i
v
e
s
t
ud
i
es
w
i
t
h
ot
h
er
t
ec
hni
ques
d
i
s
c
us
s
ed
i
n
t
he pap
er
has
r
e
ve
a
l
e
d
t
h
e
s
up
er
i
or
i
t
y
of
C
S
O
S
c
om
par
ed
t
o
P
S
O
a
nd
E
P
b
y
pr
ov
i
d
i
n
g
be
t
t
er
per
f
or
m
anc
e
in
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h Manag
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R
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i
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Mi
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h
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R
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er
en
ces
[1
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lija
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i
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ue
s
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,
H
adj
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ah
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pt
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al
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ber
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o
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at
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h I
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t
er
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t
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D
13
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ha
ngha
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.
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013:
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.
[2
]
Sa
k
r
WS
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El
-
S
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h
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e
m
y R
A
,
A
zm
y A
M
.
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pt
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m
al
al
l
oc
at
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o
n o
f
T
C
S
C
s
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y
adapt
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v
e D
E
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h
m
.
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E
T
G
ener
at
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on,
T
r
ans
m
i
s
s
i
on &
D
i
s
t
r
i
b
ut
i
o
n
.
2
016
;
10
(
15
):
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844
–
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
EC
S
IS
S
N
:
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502
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haos
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ear
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h
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hama
d K
ha
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ma
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.Z
)
153
[3
]
D
i
x
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r
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genc
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om
m
u
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at
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on N
et
w
or
k
s
.
B
h
opal
.
201
4
:
1
184
–
118
7
.
[4
]
J
um
aat
S
A
,
M
us
i
r
i
n I
,
O
t
hm
a
n M
M
,
M
ok
hl
i
s
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.
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ar
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opt
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m
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on t
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t
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on
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d
s
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z
i
ng
of
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hy
r
i
s
t
or
c
on
t
r
ol
l
ed
s
er
i
es
c
a
pa
c
i
t
or
.
2012
I
nt
er
nat
i
on
al
C
o
nf
er
enc
e o
n
I
nnov
at
i
on M
anagem
ent
and T
ec
hn
ol
o
gy
R
es
ear
c
h
.
M
al
ac
c
a
.
2012
:
6
40
–
6
45
.
[5
]
B
enabi
d
R
,
B
oudo
ur
M
,
A
bi
do
MA
.
O
pt
i
m
al
pl
ac
em
ent
of
F
A
C
T
S
dev
i
c
es
f
or
m
ul
t
i
-
ob
j
ec
t
i
v
e
v
o
l
t
ag
e
s
t
a
b
ilit
y
pr
obl
em
.
200
9 I
E
E
E
/
P
E
S
P
ow
er
S
y
s
t
em
s
C
o
nf
er
e
nc
e and E
x
pos
i
t
i
on
.
S
eat
t
l
e
.
200
9
:
1
–
11
.
[6
]
V
a
lle
Y
,
H
er
nand
ez
J
,
V
enay
agam
oor
t
hy
G
,
H
ar
l
ey
R
.
O
pt
i
m
al
S
T
A
T
C
O
M
S
i
z
i
ng and P
l
ac
em
en
t
U
s
i
ng P
ar
t
i
c
l
e S
w
ar
m
O
pt
i
m
i
z
at
i
on
.
2006 I
E
E
E
/
P
E
S
T
r
an
s
m
i
s
s
i
on &
D
i
s
t
r
i
but
i
on C
o
nf
er
enc
e an
d
E
x
pos
i
t
i
on:
Lat
i
n A
m
er
i
c
a
.
C
ar
ac
a
s
.
20
06
:
1
–
6
.
[7
]
A
ghaebr
ahi
m
i
M
R
,
G
ol
k
hand
an R
K
,
A
hm
ad
ni
a S
.
Lo
c
al
i
z
at
i
on a
nd s
i
z
i
ng of
F
A
C
T
S
dev
i
c
e
s
f
or
opt
i
m
al
pow
er
f
l
ow
i
n
a
s
y
s
t
em
c
on
s
i
s
t
i
n
g
w
i
nd
pow
er
us
i
n
g
H
B
M
O
.
2016
1
8t
h
M
edi
t
er
r
a
nea
n
E
l
ec
t
r
ot
e
c
hn
i
c
a
l
C
onf
er
en
c
e (
M
E
LE
C
O
N
)
.
Lem
es
os
.
201
6
:
1
–
7
.
[8
]
A
gr
aw
al
R
,
B
har
adw
aj
S
K
,
K
o
t
har
i
D
P
.
O
pt
i
m
al
l
o
c
at
i
on
and
s
i
z
i
ng of
S
V
C
c
on
s
i
der
i
ng
t
r
a
ns
m
i
s
s
i
o
n
l
o
s
s
a
nd
i
ns
t
al
l
at
i
o
n c
os
t
u
s
ing
T
L
B
O
.
20
15 A
n
nua
l
I
E
E
E
I
ndi
a C
o
nf
er
enc
e (
I
N
D
I
C
O
N
)
.
N
ew
D
el
hi
.
2015
:
1
–
6
.
[9
]
K
az
em
i
A
,
P
ar
i
z
ad A
,
B
ag
hae
e H
R
.
O
n t
he us
e of
h
ar
m
ony
s
ear
c
h al
gor
i
t
hm
i
n opt
i
m
a
l
pl
ac
em
ent
o
f
f
ac
t
s
de
v
i
c
e
s
t
o
i
m
pr
ov
e pow
er
s
y
s
t
em
s
e
c
ur
i
t
y
.
I
E
E
E
E
URO
CO
N 2
0
0
9
.
St
.
-
P
et
er
s
bur
g
.
2009
:
570
–
576
.
[
10]
Sa
l
i
m
N
AB,
M
a
i
k
a
J
.
O
pt
i
m
al
al
l
o
c
at
i
on
of
F
A
C
T
S
de
v
i
c
e
t
o
i
m
pr
ov
e
v
o
l
t
ag
e
pr
of
i
l
e
and
p
ow
er
l
os
s
us
i
n
g
e
v
ol
ut
i
onar
y
pr
ogr
am
m
i
ng
t
e
c
hn
i
qu
e
.
2
016
I
E
E
E
R
eg
i
on
10
C
onf
er
en
c
e
(
T
E
N
C
O
N
)
.
S
i
ng
apor
e
.
2016
:
120
8
–
12
15
.
[
11]
R
as
hed
G
I
,
S
u
n Y
,
Li
u
K
-
P.
O
pt
i
m
al
pl
a
c
em
ent
of
T
hy
r
i
s
t
or
C
ont
r
ol
l
ed S
er
i
e
s
C
om
pe
ns
at
i
on i
n po
we
r
s
y
s
t
em
ba
s
ed
on D
i
f
f
er
en
t
i
a
l
E
v
ol
u
t
i
on
al
g
or
i
t
hm
.
201
1 S
ev
ent
h I
nt
er
n
at
i
o
nal
C
onf
er
enc
e
on N
at
ur
al
C
om
put
at
i
o
n
.
S
h
angh
ai
.
201
1
:
2204
–
221
0
.
[
12]
N
av
een
K
u
m
ar
G
,
S
ur
y
a
K
a
l
av
at
hi
M
.
C
at
S
w
ar
m
O
pt
i
m
i
z
at
i
on
f
or
o
pt
i
m
al
pl
ac
e
m
e
nt
of
m
ul
t
i
pl
e
UP
F
C’
s
i
n
v
o
l
t
a
ge
s
t
a
bi
l
i
t
y
en
hanc
em
e
nt
under
c
ont
i
nge
nc
y
.
I
nt
er
nat
i
ona
l
J
our
n
al
of
E
l
ec
t
r
i
c
al
P
ow
er
& En
e
rg
y
Sy
s
t
e
m
s
.
201
4
; 5
7
:
97
–
1
04
.
[
13]
M
oham
ad
Z
am
ani
M
K
,
M
us
i
r
i
n I
,
S
ul
i
m
an S
I
.
S
y
m
b
i
ot
i
c
O
r
gani
s
m
s
S
ear
c
h T
ec
hni
qu
e f
or
S
V
C
I
ns
t
a
l
l
a
t
i
on
i
n V
o
l
t
a
ge C
ont
r
ol
.
I
ndo
nes
i
an
J
our
nal
of
E
l
ec
t
r
i
c
al
E
ngi
neer
i
ng
and C
om
pu
t
er
S
c
i
e
nc
e
.
2017
; 6
(
2
):
318
–
329
.
[
14]
M
odar
r
es
i
J
,
G
hol
i
pour
E
.
A
c
om
pr
ehe
ns
i
v
e
r
ev
i
ew
of
t
he
v
ol
t
age
s
t
abi
l
i
t
y
i
ndi
c
e
s
.
R
ene
w
abl
e
an
d
S
us
t
a
i
nab
l
e E
n
er
g
y
R
ev
i
ew
s
.
2016
; 6
3
:
1
–
12
.
[
15]
S
aha S
,
M
uk
her
j
ee
V
.
O
p
t
i
m
al
p
l
ac
em
e
nt
a
nd
s
i
z
i
n
g of
D
G
s
i
n R
D
S
us
i
ng
c
ha
os
em
b
edded
S
O
S
al
gor
i
t
h
m
.
I
E
T
G
e
ner
at
i
on,
T
r
a
ns
m
i
s
s
i
o
n &
D
i
s
t
r
i
b
ut
i
o
n
.
2
016
; 1
0
(
14
):
36
71
–
3680
.
[
16]
S
y
ed
M
us
t
af
f
a S
A
,
M
us
i
r
i
n I
,
O
t
hm
an M
M
,
M
ans
or
M
H
.
C
haot
i
c
M
ut
at
i
on I
m
m
u
ne
E
v
ol
ut
i
on
ar
y
P
r
ogr
am
m
i
ng f
or
V
ol
t
a
ge S
e
c
ur
i
t
y
w
i
t
h t
he P
r
e
s
e
nc
e
of
D
G
P
V
.
I
ndone
s
i
a
n J
o
ur
na
l
o
f
E
l
ec
t
r
i
c
al
E
ngi
ne
er
i
n
g an
d C
om
put
e
r
S
c
i
enc
e
.
20
17
; 6
(
3
):
72
1
–
729
.
Evaluation Warning : The document was created with Spire.PDF for Python.