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2
[
2
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lik
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[
4
-
5
]
;
co
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.
An
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IJ
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N:
2252
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8814
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1
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s
te
m
f
r
o
m
an
o
t
h
e
r
p
ar
t
b
y
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o
id
in
g
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s
y
s
te
m
f
r
o
m
th
e
co
m
p
le
x
co
n
tr
o
l.
2.
T
H
E
B
ASI
C
P
RINC
I
P
AL
A
ND
M
AT
H
E
M
AT
I
CAL M
O
DE
L
O
F
AN
T
CO
L
O
NY
A
L
G
O
R
I
T
H
M
E
x
p
lain
i
n
g
r
esear
ch
c
h
r
o
n
o
lo
g
ical,
in
c
lu
d
i
n
g
r
esear
c
h
d
esi
g
n
,
r
esear
c
h
p
r
o
ce
d
u
r
e
(
in
th
e
f
o
r
m
o
f
alg
o
r
ith
m
s
,
P
s
eu
d
o
co
d
e
o
r
o
th
er
)
,
h
o
w
to
test
an
d
d
ata
ac
q
u
is
itio
n
[1
-
3]
.
T
h
e
d
escr
ip
ti
o
n
o
f
th
e
co
u
r
s
e
o
f
r
esear
ch
s
h
o
u
ld
b
e
s
u
p
p
o
r
ted
r
ef
er
en
ce
s
,
s
o
th
e
ex
p
la
n
atio
n
ca
n
b
e
ac
ce
p
ted
s
cien
ti
f
icall
y
[
2
]
,
[
4
]
.
T
ab
les an
d
Fig
u
r
es a
r
e
p
r
esen
t
ed
ce
n
ter
,
as s
h
o
w
n
b
elo
w
a
n
d
cited
in
th
e
m
an
u
s
cr
ip
t.
T
h
e
s
u
r
v
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y
s
h
o
w
s
th
a
t
A
C
O
w
a
s
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s
ed
f
ir
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tl
y
i
n
th
e
T
r
av
elli
n
g
Sales
m
a
n
P
r
o
b
lem
(
T
SP
)
a
s
w
e
ll a
s
i
n
o
th
er
f
ield
s
i
n
v
ar
io
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s
ap
p
licat
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s
s
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c
h
as J
o
b
Sch
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li
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g
p
r
o
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lem
s
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n
d
T
elec
o
m
m
u
n
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i
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n
Net
w
o
r
k
as a
n
o
p
tim
izer
,
V
eh
icle
R
o
u
ti
n
g
; b
u
t it
h
a
s
n
e
v
er
u
s
ed
in
t
h
e
r
eg
u
latio
n
an
d
t
h
e
co
n
tr
o
l s
y
s
te
m
b
ef
o
r
e.
T
h
er
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o
r
e,
w
e
ai
m
,
th
r
o
u
g
h
t
h
is
p
ap
er
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to
o
p
en
a
n
e
w
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ate
f
o
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th
e
u
s
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f
th
e
ar
ti
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icial
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n
tel
lig
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n
t i
n
t
h
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d
o
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ai
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it b
ec
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h
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s
u
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t
o
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m
a
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y
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I
n
m
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y
an
t
s
p
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ie
s
,
an
ts
m
o
v
e
to
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d
f
r
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m
a
f
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o
d
s
o
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r
ce
d
ep
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s
itin
g
o
n
th
e
g
r
o
u
n
d
a
s
u
b
s
ta
n
ce
ca
lled
p
h
er
o
m
o
n
e.
An
an
t
en
c
o
u
n
ter
i
n
g
a
p
r
ev
io
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s
l
y
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tr
ail
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n
d
etec
t
t
h
e
d
en
s
e
o
f
p
h
er
o
m
o
n
e
tr
ail.
Ot
h
e
r
an
ts
p
er
ce
i
v
e
t
h
e
p
r
esen
ce
o
f
p
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er
o
m
o
n
e
a
n
d
ten
d
to
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o
llo
w
tr
ac
k
s
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er
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m
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co
n
ce
n
tr
atio
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i
s
h
i
g
h
er
an
d
r
ein
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ce
t
h
e
tr
ail
w
it
h
th
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o
w
n
p
h
er
o
m
o
n
e.
T
h
r
o
u
g
h
th
i
s
m
ec
h
an
is
m
,
t
h
e
a
n
t
co
lo
n
y
co
llecti
v
el
y
,
at
last
,
m
ar
k
s
th
e
s
h
o
r
test
p
ath
w
h
ich
h
a
s
th
e
lar
g
e
s
t
p
h
er
o
m
o
n
e
a
m
o
u
n
t.
A
ct
u
all
y
,
s
u
ch
s
i
m
p
le
i
n
d
ir
ec
t
co
m
m
u
n
icatio
n
w
a
y
a
m
o
n
g
a
n
ts
e
m
b
o
d
ies a
k
i
n
d
o
f
co
llecti
v
e
lear
n
i
n
g
m
ec
h
a
n
is
m
.
An
ts
ar
e
ab
le
to
tr
an
s
p
o
r
t
f
o
o
d
to
th
eir
n
est i
n
a
r
e
m
ar
k
a
b
ly
e
f
f
ec
ti
v
e
w
a
y
[
2
]
,
[
1
6
]
.
F
ig
u
r
e
1.
Sel
f
-
ad
ap
ti
v
e
B
eh
av
i
o
r
o
f
A
n
t C
o
lo
n
y
: (
A
)
R
ea
l
An
ts
Fo
llo
w
a
P
ath
B
et
w
ee
n
Ne
s
t
an
d
F
ood
s
o
u
r
ce
;
(
B
)
A
n
o
b
s
tacle
ap
p
ea
r
s
o
n
th
e
p
ath
:
an
ts
c
h
o
o
s
e
w
h
e
th
er
to
tu
r
n
lef
t
o
r
r
ig
h
t
w
it
h
eq
u
al
p
r
o
b
a
b
ilit
y
;
(
C
)
P
h
er
o
m
o
n
e
i
s
d
ep
o
s
ited
m
o
r
e
q
u
ic
k
l
y
o
n
s
h
o
r
ter
p
ath
;
(
D)
A
ll
an
ts
h
a
v
e
c
h
o
s
e
n
s
h
o
r
ter
p
ath
[
17]
T
h
e
p
r
in
cip
le
ex
p
er
i
m
e
n
t
o
f
AC
O
s
h
o
w
n
i
n
(
Fi
g
u
r
e
2
)
is
co
m
m
o
n
l
y
k
n
o
w
n
as
“
d
o
u
b
le
b
r
id
g
e
ex
p
er
i
m
e
n
t”,
an
d
it
d
e
m
o
n
s
tr
ates
th
e
r
ea
l
b
e
h
av
io
r
o
f
t
h
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a
n
ts
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Fi
r
s
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o
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all,
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li
n
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t
co
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s
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y
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w
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Star
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h
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y
ta
k
e
w
it
h
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d
o
m
f
lu
ct
u
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s
.
Af
ter
a
w
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ile,
o
n
e
o
f
t
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b
r
id
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a
h
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o
f
p
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m
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o
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attr
ac
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m
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r
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ts
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a
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b
r
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m
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attr
ac
tiv
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[
2
]
.
A
s
a
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th
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co
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v
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ce
o
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p
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o
n
th
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w
a
y
to
t
h
e
f
o
o
d
s
o
u
r
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
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2
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IJ
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Vo
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2
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201
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164
–
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164
F
ig
u
r
e
2.
Ex
p
er
i
m
e
n
tal
Setu
p
f
o
r
t
h
e
Do
u
b
le
B
r
id
g
e
E
x
p
er
i
m
en
t
[
2
]
T
h
e
b
asic
m
o
d
el
o
f
An
t
C
o
lo
n
y
Op
ti
m
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n
A
l
g
o
r
ith
m
is
f
ir
s
tl
y
g
iv
e
n
f
o
r
t
h
e
T
SP
p
r
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b
le
m
o
f
n
cities.
W
e
ca
n
d
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i
n
e
th
e
p
ar
a
m
eter
s
o
f
b
asic a
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t c
o
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alg
o
r
ith
m
as
f
o
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w
:
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m
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ill b
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m
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i,j=1
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w
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l b
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r
en
tl
y
in
p
ar
allel
w
it
h
th
e
m
ai
n
s
y
s
te
m
lo
o
p
,
th
e
p
r
o
g
r
ess
o
f
s
y
s
te
m
s
h
o
u
ld
b
e
s
y
n
ch
r
o
n
ized
.
Fo
r
th
i
s
r
ea
s
o
n
,
th
e
s
o
lu
t
io
n
s
ar
e
tr
an
s
f
er
r
ed
f
r
o
m
t
h
e
g
e
n
er
ato
r
m
o
d
u
le
t
h
r
o
u
g
h
a
s
h
i
f
t r
eg
i
s
te
r
th
at
co
n
tai
n
s
i
n
its
t
u
r
n
t
h
e
v
ec
to
r
M
n
X
.
T
h
e
p
r
o
b
lem
in
t
h
e
r
e
g
u
la
tio
n
s
y
s
te
m
o
f
t
h
e
r
ec
tifie
r
is
d
ig
ested
d
u
r
i
n
g
t
h
e
tr
an
s
ien
t
s
tate.
T
h
e
s
y
s
te
m
tr
ie
s
to
r
ea
ch
th
e
g
i
v
en
r
ef
er
en
ce
s
tar
ti
n
g
f
r
o
m
t
h
e
i
n
i
tial p
r
o
p
o
s
ed
s
o
lu
tio
n
.
5.
AL
G
O
RI
T
H
M
RE
G
UL
AT
I
O
N
P
RO
CE
SS
U
SI
N
G
ACO
M
E
T
H
O
D
T
h
e
f
o
llo
w
in
g
d
ia
g
r
a
m
d
e
m
o
n
s
tr
ates
th
e
r
eg
u
latio
n
p
r
o
ce
s
s
u
s
i
n
g
a
n
t
co
lo
n
y
m
et
h
o
d
.
Af
ter
th
e
in
itial
izatio
n
,
t
h
e
s
y
s
te
m
u
p
lo
ad
s
th
e
p
r
o
p
o
s
ed
s
o
lu
tio
n
s
f
r
o
m
t
h
e
SG
(
So
l
u
tio
n
Ge
n
e
r
ato
r
)
s
h
if
t
r
eg
is
ter
m
o
d
u
le.
Si
n
ce
e
v
er
y
s
o
lu
tio
n
i
s
r
ep
r
esen
ted
b
y
a
n
in
d
i
v
id
u
a
l
an
t,
th
e
in
ter
n
al
c
y
cle
s
tar
t
s
wh
er
e
th
e
a
n
ts
m
o
v
e
ac
co
r
d
in
g
to
th
e
p
r
o
b
ab
ilit
y
.
T
h
e
u
p
d
ate
o
f
th
e
p
h
er
o
m
o
n
e
an
d
p
ath
s
tates
i
s
d
o
n
e
b
y
t
h
e
ex
ec
u
tio
n
o
f
th
e
ex
ter
n
al
c
y
cle
.
T
h
e
in
f
o
r
m
ati
o
n
tr
an
s
lated
to
th
e
SG
m
o
d
u
le
f
r
o
m
th
e
b
est
s
o
lu
t
io
n
s
h
if
t
r
eg
is
ter
,
w
h
en
t
h
is
last
o
n
e
cr
ea
tes a
n
e
w
g
e
n
er
ati
o
n
o
f
s
o
lu
tio
n
s
ac
co
r
d
in
g
th
e
p
r
ev
io
u
s
o
n
e
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8814
IJ
AA
S
Vo
l.
6
,
No
.
2
,
J
u
n
e
201
7
:
164
–
1
7
4
170
F
ig
u
r
e
1
0
.
AC
O
Me
t
h
o
d
Diag
r
a
m
w
it
h
I
n
t
er
n
al
an
d
E
x
ter
n
al
C
lo
s
ed
L
o
o
p
I
n
o
r
d
er
t
o
in
cr
ea
s
e
th
e
f
it
n
e
s
s
o
f
th
e
s
o
lu
tio
n
s
,
to
g
et
a
b
est
co
n
v
er
g
e
n
ce
to
th
e
s
y
s
t
e
m
an
d
to
m
i
n
i
m
ize
t
h
e
e
x
ec
u
t
io
n
ti
m
e
o
f
t
h
e
s
y
s
te
m
,
s
in
ce
th
e
s
y
s
te
m
i
n
t
h
e
la
s
t
s
o
l
u
tio
n
w
ill
k
ee
p
j
u
s
t
t
h
e
b
es
t
s
o
lu
tio
n
s
t
h
at
a
s
s
u
r
e
t
h
e
co
n
v
er
g
e
n
ce
o
f
th
e
s
y
s
te
m
,
t
h
e
id
ea
is
to
cr
ea
te
a
s
in
g
le
v
e
cto
r
th
at
co
m
b
i
n
e
s
b
et
w
ee
n
th
e
b
est
s
o
lu
tio
n
s
,
w
e
ap
p
lied
a
GR
A
P
H
SO
L
UT
I
ON
DE
C
OM
P
OSI
T
I
ON
to
th
e
o
p
tim
u
m
s
o
l
u
tio
n
s
.
6.
G
RAP
H
SO
L
UT
I
O
N
DE
CO
M
P
O
SI
T
I
O
N
T
h
e
id
ea
b
ased
o
n
th
e
d
ec
o
m
p
o
s
itio
n
o
f
th
e
g
r
ap
h
s
o
f
ea
c
h
o
p
ti
m
ized
s
o
l
u
tio
n
,
w
h
ic
h
r
ep
r
esen
t
s
t
h
e
r
esp
o
n
s
e
o
f
t
h
e
s
y
s
te
m
to
r
ea
ch
t
h
e
d
esire
d
r
ef
er
en
ce
d
u
r
in
g
th
e
tr
an
s
ie
n
t
p
er
io
d
to
d
if
f
er
e
n
t
p
ar
ts
o
r
s
a
m
p
les
;
th
e
d
ec
o
m
p
o
s
itio
n
i
s
d
o
n
e
au
t
o
m
a
ticall
y
ac
co
r
d
in
g
to
:
1.
T
h
e
p
ath
len
g
t
h
t
h
at
tak
e
s
t
h
e
s
o
lu
tio
n
to
r
ea
ch
th
e
d
esire
d
r
ef
er
en
ce
.
2.
T
h
e
ti
m
e
th
at
ta
k
es
th
e
s
o
l
u
ti
o
n
s
to
g
et
th
r
o
u
g
h
t
h
e
p
at
h
,
s
i
n
ce
w
e
in
s
er
ted
an
au
to
-
i
n
itial
izatio
n
co
u
n
ter
th
at
r
eset
s
at
th
e
b
eg
in
n
i
n
g
o
f
ea
ch
n
e
w
s
a
m
p
le.
3.
T
h
e
f
ir
s
t
o
v
er
tak
i
n
g
o
f
th
e
s
o
l
u
tio
n
to
th
e
r
ef
er
en
ce
,
w
h
ich
i
s
a
p
r
in
cip
le
f
ac
to
r
to
d
eter
m
i
n
e
t
h
e
r
esp
o
n
s
e
o
f
th
e
s
y
s
te
m
,
th
is
i
s
r
elate
d
to
a
co
n
tin
u
atio
n
f
ac
to
r
”
()
h
n
”,
w
h
ic
h
is
t
h
e
r
es
u
lt
o
f
co
n
cu
r
r
en
tl
y
ex
ec
u
t
io
n
lo
o
p
th
at
m
ea
s
u
r
e
t
h
e
f
lu
c
tu
at
io
n
s
a
n
d
r
esp
o
n
s
e
o
f
th
e
s
y
s
te
m
to
t
h
e
p
r
o
p
o
s
ed
s
o
lu
tio
n
.
T
h
e
co
r
e
o
f
th
e
a
lg
o
r
it
h
m
b
ased
o
n
a
clo
s
e
lo
o
p
s
y
s
te
m
f
o
r
t
h
e
d
ec
o
m
p
o
s
it
io
n
d
eter
m
in
a
tio
n
o
f
th
e
g
r
ap
h
r
u
les.
F
ig
u
r
e
1
1
.
Gr
ap
h
Dec
o
m
p
o
s
iti
o
n
T
o
p
o
lo
g
y
w
i
th
AC
O
M
et
h
o
d
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
S
elf
-
Tu
n
in
g
V
GP
I
C
o
n
tr
o
ller
B
a
s
ed
o
n
A
C
O
Meth
o
d
A
p
p
lie
d
fo
r
W
T
GS
s
ystem
(
M.
Ma
d
a
ci
)
171
First,
th
e
d
ec
o
m
p
o
s
it
io
n
d
ata
i
s
s
et
u
n
d
er
th
e
f
o
r
m
:
De
c
o
p
o
siti
o
n
S
e
tT
a
b
le(
N;(
Pa
th
L
e
n
g
t
h
,
P
a
th
c
ro
ss
e
d
T
ime
,
Co
n
t
-
in
o
u
a
ti
o
n
Fa
c
t
o
r”
()
h
n
”
)),
“
h
”
d
eter
m
i
n
e
th
e
n
u
m
b
er
o
f
t
h
e
s
a
m
p
le
s
f
o
r
ea
c
h
s
y
s
te
m
r
esp
o
n
s
e
s
o
lu
tio
n
wh
ich
d
eter
m
i
n
e
s
t
h
e
D
C
b
u
s
v
o
ltag
e
c
u
r
v
e
f
o
r
(
n
)
ele
m
e
n
t o
f
t
h
e
v
ec
to
r
M
n
X
.
On
t
h
i
s
ca
s
e
n
h
l
an
d
n
h
Q
w
i
ll
b
e
r
esp
ec
tiv
el
y
t
h
e
MI
N
a
n
d
t
h
e
M
A
X
o
f
t
h
e
s
a
m
p
le
(
h
)
f
r
o
m
a
p
ar
t,
f
r
o
m
an
o
t
h
er
p
ar
t
(
(
)
)
,
(
(
)
)
hh
t
Q
n
t
l
n
ar
e
th
e
ti
m
e
ac
co
r
d
ed
to
th
e
s
a
m
p
le’
s
ex
t
r
e
m
ities
p
o
in
ts
n
h
l
an
d
n
h
Q
,
th
is
w
il
l
b
e
th
e
o
u
tp
u
t
o
f
th
e
au
to
-
in
itialized
co
u
n
ter
g
iv
e
n
u
n
d
er
th
e
f
o
r
m
o
f
v
ec
to
r
(
)
(
(
)
)
,
(
1
)
(
)
,
.
.
.
.
.
.
,
(
1
)
(
)
,
(
(
)
)
h
h
h
h
h
t
n
l
n
t
l
n
t
Q
n
t
Q
n
I
n
th
i
s
ca
s
e
(
)
(
)
(
)
h
h
h
n
n
n
(
2
3
)
W
ith
(
)
/
(
(
(
)
)
(
(
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)
h
h
h
n
t
Q
n
t
l
n
(
2
4
)
1
1
(
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(
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i
f
(
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()
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i
f
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h
h
h
h
h
h
h
h
h
n
n
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l
n
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n
n
Q
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l
n
(
2
5
)
Sin
ce
(
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(
(
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)
(
(
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h
h
h
h
h
n
Q
t
Q
n
l
t
l
n
(
2
6
)
T
h
e
last
f
i
n
ite
o
p
ti
m
ized
s
o
l
u
t
io
n
is
g
i
v
en
u
n
d
er
t
w
o
v
ec
to
r
s
w
h
ic
h
co
n
tai
n
b
o
th
:
th
e
b
e
s
t
s
o
lu
tio
n
i
n
ea
ch
d
ec
o
m
p
o
s
itio
n
p
ar
t
(
h
)
o
f
t
h
e
(
n
)
o
p
ti
m
ized
s
o
l
u
tio
n
s
,
an
d
th
e
ti
m
e
r
eq
u
ir
ed
i
m
p
l
icat
in
g
th
e
s
e
s
o
lu
tio
n
s
,
in
p
ar
allel
th
i
s
co
n
s
tr
u
ct
s
a
s
c
h
ed
u
le
o
f
s
u
cc
e
s
s
i
v
e
s
o
l
u
tio
n
s
to
th
e
DC
b
u
s
v
o
lta
g
e
r
eg
u
lati
o
n
p
r
o
b
lem
.
7.
SI
M
UL
AT
I
O
N
R
E
SU
L
T
S
A
ND
DIS
CU
T
I
O
N
T
h
e
s
i
m
u
latio
n
o
f
t
h
e
w
h
o
l
e
s
y
s
te
m
w
a
s
d
o
n
e
u
s
i
n
g
a
co
-
s
i
m
u
latio
n
b
et
w
ee
n
t
w
o
p
o
w
er
f
u
l
p
latf
o
r
m
s
w
h
ic
h
ar
e
MA
T
L
AB
an
d
P
SIM
,
th
e
ex
ec
u
tio
n
o
f
th
e
s
tu
d
ied
m
o
d
el
an
d
its
co
n
tr
o
l
n
ee
d
p
o
w
er
f
u
l
co
m
p
u
tatio
n
s
o
f
t
w
ar
e
a
n
d
h
ar
d
w
ar
e.
I
n
o
r
d
er
to
ac
h
ie
v
e
th
is
tas
k
w
h
ic
h
a
llo
w
u
s
to
r
ed
u
ce
t
h
e
s
i
m
u
lat
io
n
ti
m
e
f
r
o
m
a
p
ar
t
an
d
m
i
n
i
m
iz
e
th
e
er
r
o
r
s
f
r
o
m
an
o
t
h
er
w
e
u
s
ed
th
e
co
-
s
i
m
u
latio
n
b
et
w
ee
n
th
e
b
o
th
p
latf
o
r
m
s
b
y
d
i
v
id
in
g
t
h
e
tas
k
s
b
et
w
ee
n
th
e
m
.
Sin
ce
M
A
T
L
A
B
i
s
a
m
o
n
g
th
e
m
o
s
t
p
o
w
er
f
u
l
ca
lc
u
latio
n
p
ac
k
ag
es
in
t
h
e
ac
ad
e
m
ia
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