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ller
(
FLC)
b
ec
o
m
e
s
o
n
e
o
f
th
e
m
o
s
t
r
eq
u
ir
ed
m
et
h
o
d
s
in
th
e
f
ield
o
f
p
ar
a
m
eter
ad
ap
tatio
n
in
h
eu
r
i
s
tic
an
d
m
eta
h
eu
r
i
s
tic
alg
o
r
ith
m
s
[
6
]
.
I
n
f
ac
t,
t
h
e
co
n
ce
p
t
o
f
F
L
C
i
s
v
er
y
ea
s
y
to
co
m
p
r
e
h
e
n
d
,
s
in
ce
it
p
o
s
s
es
s
es
a
h
u
m
a
n
li
k
e
i
n
t
u
itio
n
w
h
ic
h
m
ak
e
s
it p
r
ef
er
ab
le
f
o
r
th
e
co
n
tr
o
ller
s
an
d
th
e
ad
ap
ter
s
[
7
]
.
Ma
n
y
r
esear
ch
er
s
h
a
v
e
ap
p
lied
th
e
F
L
C
to
s
e
v
er
al
v
ar
ia
n
ts
o
f
A
n
t
C
o
lo
n
y
Op
ti
m
izat
io
n
a
lg
o
r
ith
m
s
to
ad
j
u
s
t
th
eir
p
ar
a
m
eter
s
.
I
n
[
8
]
,
L
i
et
al
d
ev
elo
p
ed
a
f
u
zz
y
a
n
t
co
lo
n
y
o
p
ti
m
iza
tio
n
(
FA
C
O)
to
ad
ap
t
th
e
ev
ap
o
r
ated
an
d
d
ep
o
s
ited
v
alu
e
o
f
p
h
er
o
m
o
n
e
tr
ail
ap
p
lied
in
a
o
n
e
-
p
iece
f
lo
w
p
r
o
d
u
ctio
n
s
y
s
te
m
,
u
s
i
n
g
t
h
e
a
g
e
o
f
p
h
er
o
m
o
n
e
tr
ail
a
n
d
t
h
e
a
n
t
'
s
f
it
n
ess
as
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
es
f
o
r
t
h
e
F
L
C
a
lg
o
r
it
h
m
.
A
l
s
o
,
Ah
m
ad
izar
an
d
So
ltan
p
an
ah
i
n
[
9
]
p
r
o
p
o
s
ed
a
Fu
zz
y
L
o
g
ic
co
n
ce
p
t
to
en
h
an
ce
t
h
e
p
er
f
o
r
m
an
ce
o
f
AC
O,
b
y
d
ev
elo
p
in
g
an
ef
f
ec
t
iv
e
A
n
t
C
o
lo
n
y
Op
ti
m
iza
tio
n
to
d
ea
l
w
it
h
r
elia
b
ilit
y
o
p
ti
m
i
za
tio
n
p
r
o
b
lem
f
o
r
a
s
er
ies
s
y
s
te
m
w
it
h
v
ar
io
u
s
c
h
o
ices.
Fo
r
t
h
eir
w
o
r
k
,
t
h
e
y
c
o
n
s
id
er
ed
th
e
p
h
er
o
m
o
n
e
tr
ail
s
an
d
th
e
h
e
u
r
is
tic
in
f
o
r
m
atio
n
a
s
a
f
u
zz
y
s
et.
Am
ir
et
al.
[
1
0
]
,
p
r
o
p
o
s
ed
in
t
h
eir
w
o
r
k
,
a
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
(
FLC)
to
ad
ap
t
a
n
d
q
0
p
ar
am
eter
s
au
to
m
at
icall
y
w
h
ile
s
o
l
v
i
n
g
th
e
p
r
o
b
lem
u
s
in
g
th
e
e
r
r
o
r
o
f
th
e
s
o
f
ar
b
est
to
u
r
co
m
p
ar
ed
to
th
e
b
est
-
k
n
o
w
n
to
u
r
f
o
r
th
e
T
SP
p
r
o
b
lem
an
d
th
e
d
iv
er
s
it
y
b
et
w
ee
n
th
e
f
o
u
n
d
s
o
lu
tio
n
s
b
y
t
h
e
p
o
p
u
latio
n
o
f
an
ts
a
s
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
e
s
.
Fo
r
t
h
eir
p
ar
ts
,
Ne
y
o
y
et
al.
[
1
1
]
,
u
s
ed
a
FLC
to
d
y
n
a
m
icall
y
ad
ap
tin
g
th
e
p
ar
a
m
eter
,
i
n
o
r
d
er
to
av
o
id
ea
r
l
y
co
n
v
er
g
e
n
ce
.
T
h
e
m
ai
n
id
ea
is
in
cr
ea
s
in
g
t
h
e
v
a
lu
e
o
f
p
ar
a
m
eter
w
it
h
t
h
e
u
s
e
o
f
er
r
o
r
an
d
ch
an
g
e
o
f
er
r
o
r
w
h
ic
h
ar
e
co
n
s
id
er
ed
as
in
p
u
ts
o
f
F
L
C
,
w
h
ile
r
es
p
ec
tin
g
t
h
e
av
er
ag
e
la
m
b
d
a
b
r
an
ch
i
n
g
f
ac
to
r
t
h
at
in
d
icate
s
t
h
e
e
x
p
lo
r
atio
n
lev
el
in
t
h
e
s
ea
r
ch
ar
ea
b
y
m
ea
s
u
r
i
n
g
t
h
e
d
is
tr
ib
u
tio
n
o
f
th
e
p
h
er
o
m
o
n
e
tr
ails
v
a
lu
es.
A
l
s
o
,
Oliv
a
s
et
al.
[
1
2
]
,
p
r
o
p
o
s
ed
a
d
y
n
a
m
ic
co
n
tr
o
l
f
o
r
ex
p
lo
r
atio
n
an
d
ex
p
lo
itatio
n
ca
p
ab
ilit
ie
s
o
f
t
h
e
s
ea
r
ch
s
p
ac
e
in
a
n
A
C
O
alg
o
r
ith
m
,
b
y
d
y
n
a
m
icall
y
ad
ap
tin
g
t
h
e
g
lo
b
al
p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
a
m
eter
u
s
i
n
g
f
u
zz
y
lo
g
ic
co
n
tr
o
ll
er
(
FL
C
)
.
T
o
th
is
en
d
,
th
e
y
u
s
ed
d
iv
er
s
it
y
an
d
iter
atio
n
m
etr
ics
as
i
n
p
u
t
s
o
f
th
e
Fu
zz
y
s
y
s
te
m
,
i
n
o
r
d
er
to
m
ea
s
u
r
e
th
e
al
g
o
r
ith
m
p
er
f
o
r
m
an
ce
,
an
d
th
e
p
ar
am
eter
w
a
s
co
n
s
id
er
ed
as o
u
tp
u
t.
As an
ad
d
itio
n
to
Oli
v
as
et
al
ap
p
r
o
a
ch
,
I
n
[
1
3
]
au
th
o
r
s
p
r
o
p
o
s
ed
an
ev
o
lv
ed
An
t
C
o
lo
n
y
S
y
s
te
m
al
g
o
r
ith
m
b
y
d
y
n
a
m
icall
y
ad
ap
tin
g
th
e
lo
ca
l
p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
a
m
eter
u
s
i
n
g
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
.
T
h
e
in
p
u
ts
f
o
r
th
e
i
r
f
u
zz
y
s
y
s
te
m
ar
e
th
e
s
a
m
e
as
in
Oli
v
as
p
r
o
p
o
s
ed
m
et
h
o
d
.
B
esid
es
th
e
ad
ap
t
atio
n
o
f
AC
O
p
ar
a
m
eter
s
,
f
u
zz
y
lo
g
ic
w
a
s
ap
p
lied
in
o
th
er
m
eta
h
eu
r
i
s
tic
alg
o
r
i
th
m
s
.
Su
c
h
as
[
1
4
]
,
w
h
er
e
Vald
ez
et
al
d
ef
in
ed
a
h
y
b
r
id
p
ar
ticle
s
w
ar
m
o
p
tim
izatio
n
alg
o
r
it
h
m
w
it
h
g
en
et
ic
al
g
o
r
ith
m
w
h
ic
h
u
s
e
s
f
u
zz
y
lo
g
ic
s
y
s
t
e
m
f
o
r
p
ar
a
m
eter
ad
ap
tatio
n
an
d
d
ec
is
io
n
m
ak
in
g
.
T
o
d
o
s
o
,
th
e
y
p
r
o
p
o
s
ed
th
r
ee
f
u
z
z
y
s
y
s
te
m
s
;
th
e
f
ir
s
t
o
n
e
g
iv
es
d
ec
is
io
n
s
ab
o
u
t
th
e
b
est
r
es
u
lt
s
o
f
t
h
e
FP
S
O
+
FG
A
,
w
h
ile
t
h
e
t
w
o
s
e
co
n
d
s
ar
e
r
esp
o
n
s
ib
le
o
f
v
ar
y
in
g
t
h
e
v
alu
e
s
o
f
th
e
cr
o
s
s
o
v
er
,
t
h
e
m
u
tatio
n
,
th
e
s
o
cial
ac
ce
ler
atio
n
,
an
d
th
e
c
o
g
n
iti
v
e
ac
ce
ler
atio
n
p
ar
a
m
ete
r
s
.
I
n
[
1
5
]
a
f
u
zz
y
lo
g
ic
m
et
h
o
d
w
as
p
r
o
p
o
s
ed
to
i
m
p
r
o
v
e
th
e
co
n
v
er
g
e
n
ce
a
n
d
th
e
d
is
p
er
s
io
n
o
f
th
e
p
o
p
u
latio
n
i
n
P
SO
al
g
o
r
ith
m
b
y
d
y
n
a
m
icall
y
ad
ap
tin
g
th
e
co
g
n
i
tiv
e
an
d
th
e
s
o
cial
f
ac
to
r
s
,
u
s
in
g
t
h
r
e
e
Fu
zz
y
S
y
s
te
m
s
w
h
ic
h
ta
k
es
th
e
av
er
ag
e
er
r
o
r
,
th
e
d
iv
er
s
i
t
y
o
f
t
h
e
s
w
ar
m
an
d
t
h
e
iter
atio
n
s
o
f
th
e
al
g
o
r
ith
m
a
s
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
es.
So
m
b
r
a
et
al.
[
1
6
]
d
ev
elo
p
ed
a
Fu
zz
y
L
o
g
ic
ap
p
r
o
ac
h
to
u
p
d
ate
t
h
e
alp
h
a
p
ar
a
m
eter
o
f
a
g
r
av
ita
tio
n
al
s
ea
r
ch
alg
o
r
ith
m
(
GS
A
)
b
ased
o
n
t
h
e
e
x
p
l
o
r
atio
n
an
d
ex
p
lo
itat
io
n
ab
i
liti
es.
T
h
r
ee
f
u
z
z
y
r
u
les
w
er
e
m
o
d
elled
ac
co
r
d
in
g
to
t
h
e
elap
s
ed
iter
atio
n
s
.
T
h
e
m
ai
n
id
ea
i
s
t
h
at
alp
h
a
s
h
o
u
ld
b
e
s
et
to
a
lo
w
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.
10
,
No
.
5
,
Octo
b
e
r
2
0
2
0
:
5
4
3
6
-
5444
5438
v
alu
e
i
n
ea
r
l
y
iter
atio
n
s
f
o
r
b
etter
ex
p
lo
r
atio
n
o
f
th
e
s
ea
r
ch
ar
ea
o
th
er
w
is
e
it
s
h
o
u
ld
b
e
s
et
to
a
h
ig
h
v
al
u
e
in
later
iter
atio
n
s
to
r
ea
ch
a
b
ette
r
ex
p
lo
itatio
n
o
f
ac
cu
m
u
lated
i
n
f
o
r
m
atio
n
s
.
I
n
[
1
7
]
L
alao
u
i
et
al
p
r
o
p
o
s
ed
a
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
t
o
ad
ap
t
th
e
n
eig
h
b
o
r
h
o
o
d
s
tr
u
ctu
r
e
o
f
s
i
m
u
lated
an
n
ea
li
n
g
d
y
n
a
m
ic
all
y
.
T
h
e
m
ai
n
g
o
al
o
f
t
h
eir
w
o
r
k
,
is
a
v
o
i
d
in
g
a
p
r
em
a
t
u
r
e
co
n
v
er
g
en
ce
o
r
s
tag
n
atio
n
b
y
b
alan
ci
n
g
b
et
wee
n
th
e
e
x
p
lo
r
atio
n
an
d
ex
p
lo
itatio
n
.
I
n
[
1
8
]
au
th
o
r
s
p
r
o
p
o
s
ed
a
h
y
b
r
id
izatio
n
b
et
w
ee
n
g
e
n
etic
h
e
u
r
is
tic
an
d
f
u
zz
y
lo
g
ic
alg
o
r
ith
m
ap
p
lied
in
w
ir
eles
s
s
en
s
o
r
n
et
w
o
r
k
s
,
in
th
e
p
u
r
p
o
s
e
to
m
i
n
i
m
ize
t
h
e
en
er
g
y
co
n
s
u
m
p
tio
n
b
y
c
h
o
o
s
in
g
a
n
o
p
ti
m
al
n
u
m
b
er
o
f
cl
u
s
ter
h
ea
d
s
.
B
esid
e
th
e
u
s
e
o
f
F
L
C
as
a
co
n
tr
o
ller
o
f
p
ar
a
m
eter
s
,
o
th
er
m
ac
h
i
n
e
lear
n
i
n
g
al
g
o
r
ith
m
s
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
b
y
s
ev
e
r
al
r
esear
ch
er
s
f
o
r
th
e
s
a
m
e
p
u
r
p
o
s
e.
W
e
ca
n
cite
th
e
f
o
llo
w
i
n
g
w
o
r
k
s
[
1
9
-
2
9
]
as e
x
a
m
p
les.
I
n
th
is
p
ap
er
,
o
u
r
co
n
tr
ib
u
tio
n
co
n
s
i
s
ts
o
n
p
r
o
p
o
s
in
g
a
n
o
n
li
n
e
d
y
n
a
m
ic
ad
ap
tatio
n
o
f
lo
ca
l
an
d
g
lo
b
al
p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
am
eter
s
u
s
i
n
g
th
e
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
(
FL
C
)
ac
co
r
d
in
g
to
s
o
m
e
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
es,
th
e
n
a
co
m
p
ar
is
o
n
b
et
w
ee
n
th
o
s
e
ad
ap
tatio
n
s
w
a
s
u
n
d
er
ta
k
en
to
s
t
u
d
y
t
h
e
b
eh
av
io
u
r
o
f
A
C
S
-
T
SP
d
u
r
in
g
t
h
is
u
p
d
ate.
T
h
e
m
o
s
t
i
m
p
o
r
ta
n
t
f
ea
t
u
r
e
o
f
th
i
s
co
n
tr
ib
u
tio
n
is
r
ef
lecte
d
in
th
e
a
u
to
m
atio
n
o
f
th
e
p
r
o
p
o
s
ed
m
ec
h
a
n
i
s
m
.
Als
o
,
th
e
o
n
li
n
e
p
r
o
p
er
t
y
o
f
th
e
p
r
o
p
o
s
ed
ad
ap
ter
allo
w
s
it
to
le
ar
n
w
h
ile
s
o
lv
i
n
g
th
e
in
s
ta
n
ce
s
,
s
o
t
h
at
th
er
e
i
s
n
o
n
ee
d
to
w
aste ti
m
e
o
n
tr
ai
n
i
n
g
.
T
h
e
r
em
ai
n
o
f
t
h
is
p
ap
er
is
o
r
g
an
is
ed
as
f
o
llo
w
s
:
I
n
s
ec
ti
o
n
2
w
e
d
escr
ib
e
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
.
T
h
e
ex
p
er
im
e
n
tal
r
es
u
lt
s
ar
e
d
is
cu
s
s
ed
in
s
ec
t
io
n
3
.
Fin
all
y
,
in
Sectio
n
4
co
n
cl
u
s
io
n
s
an
d
f
u
t
u
r
e
w
o
r
k
ar
e
p
r
esen
ted
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
Sev
er
al
m
etr
ic
s
h
av
e
b
ee
n
p
r
o
p
o
s
ed
in
f
u
zz
y
lo
g
ic
s
y
s
te
m
s
as
f
u
zz
y
s
et
to
p
er
f
o
r
m
a
d
y
n
a
m
i
c
p
ar
am
eter
ad
ap
tatio
n
in
A
C
O
alg
o
r
ith
m
s
.
I
n
t
h
is
p
ap
er
,
o
u
r
co
n
tr
ib
u
tio
n
co
n
s
is
t
i
n
th
e
d
y
n
a
m
ical
ad
a
p
tatio
n
o
f
AC
S
’
d
ec
a
y
p
ar
a
m
e
ter
s
,
b
ased
o
n
th
e
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
es
u
s
ed
in
a
n
t
co
lo
n
y
o
p
ti
m
izatio
n
w
it
h
p
ar
am
eter
ad
ap
tatio
n
u
s
i
n
g
f
u
zz
y
lo
g
ic
f
o
r
T
SP
p
r
o
b
lem
s
p
r
o
p
o
s
ed
b
y
Oli
v
as
et
al.
,
i
n
w
h
ic
h
t
h
e
y
u
s
ed
elap
s
e
d
iter
atio
n
s
d
escr
ib
ed
i
n
(
5
)
,
an
d
d
i
v
er
s
it
y
o
f
a
n
t
c
o
lo
n
y
d
escr
ib
ed
i
n
(
6
)
,
as
m
etr
ics
to
m
ea
s
u
r
e
th
e
d
iv
er
s
i
f
ica
tio
n
a
n
d
th
e
in
te
n
s
i
f
icatio
n
ab
ilit
ies i
n
t
h
e
s
ea
r
ch
s
p
ac
e.
=
(
5
)
=
1
∑
√
∑
(
(
)
−
̅
(
)
)
2
=
1
=
1
(
6
)
W
h
er
e,
C
u
r
r
en
t
iter
atio
n
is
t
h
e
n
u
m
b
er
o
f
p
as
s
ed
iter
atio
n
s
,
an
d
to
tal
o
f
iter
atio
n
is
t
h
e
to
tal
n
u
m
b
er
o
f
iter
atio
n
s
r
eq
u
i
r
ed
f
o
r
tes
tin
g
th
e
al
g
o
r
ith
m
,
m
i
s
th
e
s
ize
o
f
co
lo
n
y
,
i
is
th
e
i
n
d
ex
o
f
th
e
a
n
t,
n
is
th
e
n
u
m
b
er
o
f
d
i
m
e
n
s
io
n
s
,
j
is
th
e
n
u
m
b
er
o
f
th
e
d
i
m
en
s
io
n
,
x
ij
is
th
e
j
d
im
e
n
s
io
n
o
f
th
e
i
th
an
t,
̅
is
th
e
j
d
i
m
en
s
io
n
o
f
t
h
e
c
u
r
r
en
t
b
es
t
an
t
o
f
t
h
e
co
lo
n
y
.
I
n
ad
d
itio
n
to
t
h
e
d
y
n
a
m
ic
ad
ap
tatio
n
f
o
r
th
e
g
lo
b
al
d
ec
a
y
p
ar
am
eter
p
er
f
o
r
m
ed
b
y
Oli
v
as
et
a
l,
w
e
d
ev
elo
p
ed
a
f
u
zz
y
s
y
s
te
m
to
ad
ap
t
th
e
lo
ca
l
d
ec
a
y
p
ar
a
m
ete
r
d
y
n
a
m
icall
y
.
T
h
e
p
r
o
p
o
s
ed
(
FLC)
co
n
s
i
s
ts
o
f
t
h
r
ee
m
ai
n
p
ar
ts
:
F
u
zz
i
f
icatio
n
,
R
u
le
I
n
f
er
en
ce
,
a
n
d
Def
u
zz
if
icatio
n
.
2
.
1
.
F
uzzif
ica
t
io
n
T
o
co
n
v
er
t
th
e
cr
is
p
in
p
u
t
v
a
r
iab
le
to
f
u
zz
y
v
al
u
e,
w
e
u
s
e
d
th
e
Ma
m
d
an
i
tr
ia
n
g
u
lar
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
d
escr
ib
ed
b
elo
w
.
T
h
is
p
r
o
ce
s
s
ca
l
led
F
u
zz
if
icatio
n
an
d
it
allo
w
s
t
h
e
i
n
p
u
t
s
(
I
ter
atio
n
a
n
d
Di
v
er
s
it
y
)
an
d
o
u
tp
u
ts
(
an
d
)
v
ar
iab
les
to
b
e
q
u
an
ti
f
ied
in
li
n
g
u
i
s
ti
c
ter
m
s
.
I
n
th
i
s
p
ap
er
,
th
r
ee
t
er
m
s
ar
e
d
ef
in
ed
to
q
u
alif
y
t
h
e
i
n
p
u
ts
,
w
h
ic
h
ar
e:
L
o
w
,
Me
d
iu
m
,
an
d
Hi
g
h
.
So
w
e
ca
n
w
r
ite,
I
ter
atio
n
=
{
L
o
w
,
Me
d
i
u
m
,
Hi
g
h
}
an
d
Di
v
er
s
it
y
=
{
L
o
w
,
Me
d
iu
m
,
Hig
h
}
a
s
s
et
o
f
d
ec
o
m
p
o
s
itio
n
s
f
o
r
th
e
lin
g
u
is
t
ic
v
ar
iab
les.
W
h
er
e,
L
o
w
=
[
0
,
0
.
5
]
,
Me
d
iu
m
=
[
0
,
1
]
,
an
d
Hi
g
h
=
[
0
.
5
,
1
]
.
T
h
e
Fu
zz
i
f
icatio
n
p
r
o
ce
s
s
s
i
m
p
l
if
i
es
t
h
e
ap
p
licatio
n
o
f
r
u
les
to
d
escr
ib
e
th
e
s
y
s
te
m
i
n
a
s
i
m
p
le
m
a
n
n
er
[
3
0
-
3
2
]
.
I
n
th
is
w
o
r
k
w
e
u
s
ed
a
T
r
ian
g
u
lar
MFs
w
h
ic
h
is
co
n
s
id
er
ed
as
a
li
n
ea
r
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
.
T
h
e
ch
o
ice
o
f
th
is
t
y
p
e
o
f
MFs
is
d
u
e
t
o
its
s
i
m
p
licit
y
o
f
i
m
p
le
m
en
ta
tio
n
an
d
ef
f
icac
y
o
f
co
m
p
u
ta
tio
n
[
3
3
]
.
T
h
e
p
u
r
p
o
s
e
f
r
o
m
t
h
e
m
e
m
b
er
s
h
ip
f
u
n
c
tio
n
s
is
to
tr
an
s
f
o
r
m
f
u
zz
y
li
n
g
u
i
s
ticter
m
s
in
to
n
o
n
-
f
u
zz
y
in
p
u
t v
al
u
es
an
d
v
ice
v
er
s
a.
I
n
Fig
u
r
e
1
th
e
iter
atio
n
i
n
p
u
t
v
ar
iab
le
is
m
ap
p
ed
to
th
r
ee
t
r
ian
g
u
lar
m
e
m
b
er
s
h
ip
f
u
n
c
tio
n
s
w
it
h
a
r
an
g
e
f
r
o
m
0
to
1
is
illu
s
tr
ated
.
I
n
F
ig
u
r
e
2
th
e
Div
er
s
it
y
i
n
p
u
t
v
ar
iab
le
g
r
an
u
lated
in
to
th
r
ee
tr
ian
g
u
la
r
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
is
sh
o
w
n
w
i
th
a
r
an
g
e
f
r
o
m
0
to
1
.
I
n
Fi
g
u
r
e
3
th
e
f
i
v
e
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
o
f
ea
c
h
o
u
tp
u
t v
ar
iab
le
a
n
d
ar
e
s
h
o
w
n
,
tak
i
n
g
in
to
ac
co
u
n
t t
h
e
u
s
e
o
f
I
ter
atio
n
an
d
Di
v
er
s
it
y
a
s
in
p
u
ts
v
ar
iab
les.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
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n
g
I
SS
N:
2
0
8
8
-
8708
Th
e
b
eh
a
vio
u
r
o
f A
C
S
-
TS
P
a
l
g
o
r
ith
m
w
h
en
a
d
a
p
tin
g
b
o
th
p
h
ero
mo
n
e
p
a
r
a
met
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u
s
in
g
...
(
S
a
fa
e
B
o
u
z
b
ita
)
5439
Fig
u
r
e
1
.
I
ter
atio
n
as in
p
u
t
v
ar
iab
le
Fig
u
r
e
2
.
Div
er
s
it
y
as i
n
p
u
t
v
a
r
iab
le
Fig
u
r
e
3
.
o
r
o
u
tp
u
t v
ar
iab
le
2
.
2
.
Rule
infe
re
nce
Fo
r
th
e
r
u
le
i
n
f
er
en
ce
s
tep
,
w
e
u
s
ed
a
Ma
m
d
a
n
i
’
s
f
u
zz
y
co
n
j
u
n
ct
io
n
f
u
zz
y
r
u
le
w
h
ic
h
i
s
b
ased
o
n
I
F
-
T
h
en
r
u
les
[
3
4
,
3
5
]
.
I
n
f
ac
t,
w
e
h
av
e
b
ee
n
in
s
p
ir
ed
in
th
e
co
n
s
tr
u
ctio
n
o
f
t
h
e
f
u
zz
y
r
u
les
f
o
r
th
e
p
ar
am
eter
f
r
o
m
Oli
v
as
e
t
al.
,
th
e
n
w
e
h
av
e
d
e
v
elo
p
ed
o
u
r
o
w
n
r
u
l
e
s
f
o
r
th
e
p
ar
a
m
eter
b
ased
o
n
th
e
r
u
le
s
o
f
p
ar
am
eter
an
d
t
h
e
p
r
ev
io
u
s
k
n
o
w
led
g
e
t
h
at
p
la
y
s
an
o
p
p
o
s
ite
r
o
le
t
o
th
e
p
ar
am
eter
,
th
u
s
,
w
h
e
n
I
ter
atio
n
is
"
L
o
w
"
w
e
ar
e
o
n
ea
r
lier
s
tate
an
d
w
h
e
n
th
e
Div
er
s
it
y
is
"
L
o
w
"
t
h
e
an
ts
ar
e
s
o
n
ea
r
to
th
e
b
es
t
an
t,
s
o
w
e
n
ee
d
to
m
o
r
e
ex
p
lo
r
atio
n
b
y
s
ett
in
g
i
n
a
"
L
o
w
"
v
al
u
e.
An
d
w
h
e
n
I
ter
atio
n
i
s
"
h
ig
h
"
an
d
Div
er
s
it
y
i
s
"
h
ig
h
"
,
th
at
i
s
m
ea
n
w
e
ar
e
i
n
ad
v
a
n
ce
d
s
tate
s
an
d
a
n
ts
ar
e
s
o
s
p
r
ea
d
,
s
o
w
e
n
ee
d
to
ex
p
lo
it
th
e
p
r
ev
io
u
s
in
f
o
r
m
a
tio
n
co
ll
ec
ted
b
y
a
n
ts
b
y
s
etti
n
g
t
o
a
"
h
ig
h
"
v
alu
e.
T
ab
le
1
an
d
T
ab
le
2
p
r
esen
t
th
e
r
u
les
o
f
th
e
p
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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8708
I
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&
C
o
m
p
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n
g
,
Vo
l.
10
,
No
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5
,
Octo
b
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r
2
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2
0
:
5
4
3
6
-
5444
5440
I
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in
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4
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tp
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ig
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r
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if
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s
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Fig
u
r
e
4
.
Fu
zz
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y
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te
m
f
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r
p
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er
o
m
o
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p
ar
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m
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s
ad
ap
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in
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S
w
i
th
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d
d
i
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it
y
as i
n
p
u
t
s
2
.
3
.
Def
f
uzif
ica
t
io
n
T
h
e
o
u
tp
u
t
v
ar
iab
le
is
o
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tain
e
d
as
a
lin
g
u
is
tic
ter
m
f
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m
th
e
b
r
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s
s
tep
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o
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to
tr
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s
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s
f
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a
m
p
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C
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ter
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m
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m
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(
MO
M)
m
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d
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t
m
eth
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ter
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d
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b
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(5
)
to
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u
zz
i
f
y
th
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o
b
tain
ed
r
es
u
lt
s
:
∑
[
]
9
=
1
∑
[
]
9
=
1
(
8
)
w
h
er
e,
p
=9
is
th
e
n
u
m
b
er
o
f
a
ll
ev
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u
ated
r
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les
,
is
th
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s
i
n
g
l
eto
n
m
e
m
b
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s
h
ip
f
u
n
ctio
n
f
o
r
o
u
tp
u
t
v
ar
iab
le
,
an
d
th
e
r
esu
lt o
f
all
r
u
le
ev
al
u
atio
n
.
T
h
e
Fu
z
y
s
in
g
leto
n
s
m
e
m
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ip
f
u
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tio
n
f
o
r
ar
e
:
=
1
6
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2
6
,
3
6
,
2
6
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3
6
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3
6
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6
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6
T
h
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Fu
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ip
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5
6
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4
6
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3
6
,
4
6
,
3
6
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2
6
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3
6
,
2
6
,
1
6
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
I
n
th
i
s
s
ec
tio
n
w
e
g
iv
e
t
h
e
r
esu
lt
s
f
r
o
m
s
t
u
d
y
i
n
g
t
h
e
b
eh
av
io
u
r
o
f
AC
S
d
u
r
in
g
t
h
is
a
d
ap
tatio
n
.
T
o
th
is
en
d
,
w
e
test
ed
it
o
n
s
ev
er
al
T
SP
b
en
ch
m
ar
k
in
s
ta
n
ce
s
.
Firs
t,
w
e
u
p
d
ate
j
u
s
t
th
e
lo
ca
l
p
h
er
o
m
o
n
e
d
ec
ay
p
ar
a
m
eter
,
th
e
n
an
ad
ap
tatio
n
o
f
th
e
g
lo
b
al
p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
a
m
eter
is
p
er
f
o
r
m
ed
,
f
i
n
all
y
w
e
ad
ap
t b
o
th
p
ar
a
m
eter
s
s
i
m
u
lta
n
eo
u
s
l
y
.
3
.
1
.
E
x
peri
m
e
nt
s
et
up
T
h
e
m
o
s
t
co
m
m
o
n
u
s
ed
b
en
ch
m
ar
k
T
SP
in
s
tan
ce
s
u
s
ed
in
th
e
liter
at
u
r
e
ar
e
ch
o
s
en
as
a
s
et
o
f
ex
p
er
i
m
e
n
tal
i
n
s
tan
ce
s
i
n
t
h
is
s
tu
d
y
,
w
h
ich
w
er
e
s
ele
cted
f
r
o
m
t
h
e
T
SP
L
I
B
[
3
6
]
.
T
h
e
in
s
ta
n
ce
s
h
a
v
e
b
ee
n
r
u
n
3
0
ti
m
es
Su
cc
e
s
s
i
v
el
y
o
n
M
AT
L
A
B
[
3
7
]
,
1
0
0
0
iter
atio
n
s
e
ac
h
ti
m
e,
w
h
er
e
t
h
e
i
n
itial
p
o
s
itio
n
o
f
all
an
ts
i
s
ch
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s
en
r
a
n
d
o
m
l
y
o
n
all
ex
p
er
i
m
en
ts
,
w
it
h
th
e
p
r
o
v
e
n
b
est
v
alu
es
o
f
AC
S
al
g
o
r
ith
m
p
ar
am
eter
s
:
=2
,
=0
.
1
,
an
d
,
q
0
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.
9
[
3
8
]
.
T
ab
le
3
g
iv
es
th
e
s
izes
a
n
d
th
e
b
est
k
n
o
w
n
le
n
g
t
h
s
f
o
r
t
h
e
c
h
o
s
e
n
T
SP
in
s
tan
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s
u
s
ed
in
th
is
e
x
p
er
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m
e
n
t.
T
ab
le
3
.
C
h
ar
ar
ter
is
tics
o
f
T
SP
b
en
ch
m
ar
k
i
n
s
tan
ce
s
T
S
P
a
t
t
4
8
b
e
r
l
i
n
5
2
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h
1
3
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d
1
9
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i
l
5
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l
7
6
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k
r
o
A
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i
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5
P
r
2
2
6
N
u
mb
e
r
o
f
c
i
t
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s
48
52
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3
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51
76
1
0
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2
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6
b
e
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6
2
8
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6
1
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5
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1
2
8
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4
3
7
9
8
0
3
6
9
Ma
m
d
an
i
(
9
R
u
les)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
Th
e
b
eh
a
vio
u
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o
f A
C
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-
TS
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a
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5441
3
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2
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Co
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T
ab
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4
g
iv
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th
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m
i
n
i
m
u
m
an
d
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3
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r
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d
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p
r
ev
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s
ta
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t
h
e
C
P
U
ti
m
e
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s
h
o
w
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T
h
e
m
ea
n
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n
g
o
f
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u
s
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n
o
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o
n
s
i
n
T
ab
le
4
a
r
e
as
f
o
llo
w
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:
-
Fu
zz
y
lo
ca
l is t
h
e
r
es
u
lt
f
r
o
m
ap
p
ly
i
n
g
th
e
p
r
o
p
o
s
ed
(
FL
C
)
t
o
th
e
A
C
S
-
T
SP
alg
o
r
ith
m
,
i
n
o
r
d
er
to
a
d
j
u
s
t
th
e
lo
ca
l p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
a
m
eter
.
-
Fu
zz
y
g
lo
b
al
is
th
e
r
es
u
lt
f
r
o
m
ap
p
l
y
in
g
t
h
e
p
r
o
p
o
s
ed
to
t
h
e
AC
S
-
T
SP
alg
o
r
ith
m
,
i
n
o
r
d
er
to
ad
ap
t
th
e
g
lo
b
al
p
h
er
o
m
o
n
e
d
ec
a
y
p
ar
a
m
eter
.
-
AC
S i
s
th
e
r
es
u
lt
f
r
o
m
r
u
n
n
in
g
th
e
s
tan
d
ar
d
an
t c
o
lo
n
y
s
y
s
t
e
m
alg
o
r
it
h
m
w
it
h
f
i
x
ed
p
ar
am
eter
s
.
-
Fu
zz
y
is
t
h
e
r
esu
lt
f
r
o
m
ap
p
l
y
in
g
t
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
(
F
L
C
)
to
th
e
AC
S
-
T
SP
alg
o
r
ith
m
f
o
r
ad
j
u
s
tin
g
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ted
.
RE
F
E
R
E
NC
E
S
[1
]
M.
Do
rig
o
a
n
d
L
.
M
.
G
a
m
b
a
rd
e
ll
a
,
“
A
n
t
c
o
lo
n
y
s
y
ste
m
:
a
c
o
o
p
e
ra
ti
v
e
lea
rn
in
g
a
p
p
r
o
a
c
h
to
th
e
trav
e
li
n
g
sa
les
m
a
n
p
ro
b
lem
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
e
v
o
lu
ti
o
n
a
ry
c
o
m
p
u
t
a
ti
o
n
,
v
o
l.
1
,
n
o
.
1
,
p
p
.
5
3
-
66
,
1
9
9
7
.
[2
]
M.
Do
rig
o
a
n
d
T
.
S
tü
tzle
,
“
A
n
t
c
o
lo
n
y
o
p
ti
m
iza
ti
o
n
:
o
v
e
rv
ie
w
a
n
d
re
c
e
n
t
a
d
v
a
n
c
e
s
,
”
i
n
Ha
n
d
b
o
o
k
o
f
m
e
tah
e
u
risti
c
s
,
S
p
ri
n
g
e
r,
Bo
sto
n
,
M
A
,
p
p
.
2
2
7
-
2
6
3
,
2
0
1
0
.
[3
]
K.
C.
Yin
g
a
n
d
C.
J.
L
iao
,
“
A
n
a
n
t
c
o
lo
n
y
s
y
st
e
m
f
o
r
p
e
rm
u
tatio
n
f
lo
w
-
sh
o
p
se
q
u
e
n
c
i
n
g
,
”
Co
mp
u
ter
s
&
Op
e
ra
ti
o
n
s R
e
se
a
rc
h
,
v
o
l
.
3
1
,
n
o
.
5
,
p
p
.
7
9
1
-
8
0
1
,
2
0
0
4
.
[4
]
M.
Do
rig
o
a
n
d
C
.
Blu
m
,
“
A
n
t
c
o
lo
n
y
o
p
ti
m
iza
ti
o
n
t
h
e
o
ry
:
A
s
u
rv
e
y
,
”
T
h
e
o
re
ti
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a
l
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o
mp
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ter
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e
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l.
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4
4
,
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.
2
-
3
,
p
p
.
2
4
3
-
2
7
8
,
2
0
0
5
.
[5
]
M.
Do
rig
o
a
n
d
L
.
M
.
G
a
m
b
a
rd
e
ll
a
,
“
A
n
t
c
o
lo
n
ies
f
o
r
th
e
trav
e
ll
in
g
sa
les
m
a
n
p
ro
b
lem
,
”
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io
sy
ste
ms
,
v
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l.
4
3
,
n
o
.
2
,
p
p
.
7
3
-
81
,
1
9
9
7
.
[6
]
F.
V
a
l
d
e
z
,
e
t
a
l.
,
“
A
su
rv
e
y
o
n
n
a
tu
re
-
in
s
p
ired
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
s
w
it
h
f
u
z
z
y
lo
g
ic
f
o
r
d
y
n
a
m
ic
p
a
r
a
m
e
ter
a
d
a
p
tatio
n
,
”
Exp
e
rt sy
ste
ms
wit
h
a
p
p
li
c
a
ti
o
n
s
,
v
o
l.
4
1
,
n
o
.
1
4
,
p
p
.
6
4
5
9
-
6
4
6
6
,
2
0
1
4
.
[7
]
R.
Krish
n
a
,
e
t
a
l.
,
“
S
p
e
e
d
c
o
n
tr
o
l
o
f
se
p
a
ra
tel
y
e
x
c
it
e
d
DC
m
o
to
r
u
sin
g
f
u
z
z
y
lo
g
ic
c
o
n
tro
ll
e
r
,”
T
h
è
se
d
e
d
o
c
to
ra
t
,
Na
ti
o
n
a
l
In
st
it
u
te
o
f
T
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c
h
n
o
lo
g
y
,
Ro
u
rk
e
la,
Od
ish
a
,
2
0
1
5
.
[8
]
S
.
G
.
Li
a
n
d
Y.
L
.
Ro
n
g
,
“
T
h
e
re
li
a
b
le
d
e
sig
n
o
f
o
n
e
-
p
iec
e
flo
w
p
ro
d
u
c
ti
o
n
sy
ste
m
u
sin
g
f
u
z
z
y
a
n
t
c
o
lo
n
y
o
p
ti
m
iza
t
io
n
,”
C
o
mp
u
ter
s
&
Op
e
ra
ti
o
n
s R
e
se
a
rc
h
,
v
o
l
.
36
,
n
o
.
5
,
p
p
.
1
6
5
6
-
1
6
6
3
,
2
0
0
9
.
[9
]
F.
A
h
m
a
d
iza
r
a
n
d
H.
S
o
lt
a
n
p
a
n
a
h
,
“
Re
li
a
b
il
it
y
o
p
ti
m
iza
ti
o
n
o
f
a
se
ries
s
y
ste
m
w
it
h
m
u
lt
ip
le
-
c
h
o
ice
a
n
d
b
u
d
g
e
t
c
o
n
stra
in
ts
u
sin
g
a
n
e
f
f
icie
n
t
a
n
t
c
o
lo
n
y
a
p
p
ro
a
c
h
,”
Ex
p
e
rt sy
ste
ms
wi
th
A
p
p
l
ica
ti
o
n
s
,
v
o
l
.
38
,
n
o
.
4
,
p
p
.
3
6
4
0
-
3
6
4
6
,
A
p
r
.
2
0
1
1
.
[1
0
]
C.
Am
ir,
e
t
a
l.
,
“
A
f
u
z
z
y
lo
g
ic
c
o
n
tr
o
ll
e
r
f
o
r
a
n
t
a
lg
o
rit
h
m
s
,
”
Co
mp
u
ti
n
g
a
n
d
I
n
fo
rm
a
ti
o
n
S
y
ste
ms
,
v
o
l.
1
1
,
n
o
.
5
,
p
p
.
2
6
-
34
,
2
0
0
7
.
[1
1
]
H.
Ne
y
o
y
,
e
t
a
l.
,
“
Dy
n
a
m
i
c
f
u
z
z
y
lo
g
ic
p
a
ra
m
e
ter
tu
n
in
g
f
o
r
A
CO
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
in
T
S
P
p
ro
b
le
m
s
,
”
i
n
Rec
e
n
t
Ad
v
a
n
c
e
s o
n
Hy
b
ri
d
In
telli
g
e
n
t
S
y
ste
ms
,
v
o
l.
4
5
1
,
p
p
.
2
5
9
-
2
7
1
,
2
0
1
3
.
[1
2
]
F.
Oliv
a
s,
e
t
a
l.
,
“
A
n
t
Co
lo
n
y
O
p
ti
m
iza
ti
o
n
w
it
h
p
a
ra
m
e
t
e
r
a
d
a
p
tatio
n
u
si
n
g
f
u
z
z
y
lo
g
ic
f
o
r
T
S
P
p
ro
b
lem
s
,
”
i
n
De
sig
n
o
f
I
n
telli
g
e
n
t
S
y
ste
ms
Ba
se
d
o
n
Fu
zz
y
L
o
g
ic,
Ne
u
ra
l
Ne
two
rk
s
a
n
d
N
a
t
u
re
-
In
sp
ire
d
Op
ti
miza
ti
o
n
,
p
p
.
5
9
3
-
603
,
2
0
1
5
.
[1
3
]
A
.
El
Af
ia,
e
t
a
l.
,
“
T
h
e
E
ff
e
c
t
o
f
Up
d
a
ti
n
g
th
e
L
o
c
a
l
P
h
e
ro
m
o
n
e
o
n
A
CS
P
e
rf
o
rm
a
n
c
e
u
sin
g
F
u
z
z
y
L
o
g
ic
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
7
,
n
o
.
4
,
p
p
.
2
1
6
1
-
2
1
6
8
,
2
0
1
7
.
[1
4
]
F.
V
a
ld
e
z
,
e
t
a
l.
,
“
A
n
im
p
ro
v
e
d
e
v
o
lu
ti
o
n
a
ry
m
e
th
o
d
w
it
h
f
u
z
z
y
lo
g
ic
f
o
r
c
o
m
b
in
in
g
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
a
n
d
g
e
n
e
ti
c
a
lg
o
rit
h
m
s
,
”
Ap
p
l
ied
S
o
ft
Co
mp
u
ti
n
g
,
v
o
l.
1
1
,
n
o
.
2
,
p
p
.
2
6
2
5
-
2
6
3
2
,
2
0
1
1
.
[1
5
]
P.
M
e
li
n
,
e
t
a
l.
,
“
Op
ti
m
a
l
d
e
sig
n
o
f
f
u
z
z
y
c
las
si
f
ica
ti
o
n
s
y
ste
m
s
u
sin
g
P
S
O
w
it
h
d
y
n
a
m
ic
p
a
ra
m
e
ter
a
d
a
p
tatio
n
th
ro
u
g
h
f
u
z
z
y
lo
g
ic
,
”
Exp
e
rt S
y
ste
ms
wit
h
Ap
p
li
c
a
ti
o
n
s
,
v
o
l.
4
0
,
n
o
.
8
,
p
p
.
3
1
9
6
-
3
2
0
6
,
2
0
1
3
.
[1
6
]
A
.
S
o
m
b
ra
,
e
t
a
l.
,
“
A
n
e
w
g
ra
v
it
a
ti
o
n
a
l
se
a
rc
h
a
lg
o
rit
h
m
u
sin
g
f
u
z
z
y
lo
g
ic
to
p
a
ra
m
e
t
e
r
a
d
a
p
tatio
n
,
”
in
2
0
1
3
IEE
E
Co
n
g
re
ss
o
n
Evo
lu
ti
o
n
a
ry
Co
m
p
u
ta
ti
o
n
,
p
p
.
1
0
6
8
-
1
0
7
4
,
2
0
1
3
.
[1
7
]
M.
L
a
lao
u
i,
e
t
a
l.
,
“
S
im
u
late
d
A
n
n
e
a
li
n
g
w
it
h
A
d
a
p
ti
v
e
Ne
i
g
h
b
o
r
h
o
o
d
u
si
n
g
F
u
z
z
y
L
o
g
ic
Co
n
tr
o
ll
e
r
,
”
i
n
Pro
c
e
e
d
in
g
s
o
f
th
e
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
L
e
a
rn
i
n
g
a
n
d
Op
t
imiza
ti
o
n
A
lg
o
rith
ms
:
T
h
e
o
ry
a
n
d
A
p
p
li
c
a
ti
o
n
s
,
p
p
.
1
-
6
,
2
0
1
8
.
[1
8
]
P
.
K.
Ka
sh
y
a
p
a
n
d
S
.
Ku
m
a
r,
“
G
e
n
e
ti
c
-
F
u
z
z
y
b
a
s
e
d
lo
a
d
b
a
l
a
n
c
e
d
p
ro
t
o
c
o
l
f
o
r
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
s
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
2
,
p
p
.
1
1
6
8
-
1
1
8
3
,
2
0
1
9
.
[1
9
]
M.
M.
Ka
b
b
a
j
a
n
d
A.
El
A
f
i
a
,
“
To
w
a
rd
s
lea
rn
in
g
in
teg
ra
l
stra
teg
y
o
f
b
ra
n
c
h
a
n
d
b
o
u
n
d
,
”
in
2
0
1
6
5
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
u
lt
ime
d
i
a
C
o
mp
u
ti
n
g
a
n
d
S
y
ste
ms
(
ICM
CS
),
p
p
.
6
2
1
-
6
2
6
,
2
0
1
6
.
[2
0
]
A.
El
Af
ia
a
n
d
M.
M.
Ka
b
b
a
j,
“
S
u
p
e
rv
ise
d
lea
rn
in
g
in
Bra
n
c
h
-
a
n
d
-
c
u
t
stra
teg
ies
,
”
in
Pro
c
e
e
d
i
n
g
s
o
f
th
e
2
n
d
in
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
o
n
B
ig
Da
ta
,
C
lo
u
d
a
n
d
A
p
p
l
ica
ti
o
n
s
,
p
p
.
1
-
6
,
2
0
1
7
.
[2
1
]
S.
Bo
u
z
b
i
ta,
e
t
a
l.
,
“
A
n
o
v
e
l
b
a
se
d
Hid
d
e
n
M
a
rk
o
v
M
o
d
e
l
a
p
p
r
o
a
c
h
f
o
r
c
o
n
tro
ll
in
g
th
e
A
CS
-
TS
P
e
v
a
p
o
ra
ti
o
n
p
a
r
a
m
e
ter
,
”
in
2
0
1
6
5
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
u
lt
ime
d
i
a
Co
mp
u
t
in
g
a
n
d
S
y
ste
ms
(
ICM
CS
),
p
p
.
6
3
3
-
6
3
8
,
2
0
1
6
.
[2
2
]
S.
Bo
u
z
b
it
a
,
e
t
a
l.
,
“
Dy
n
a
m
ic
a
d
a
p
tatio
n
of
th
e
A
CS
-
T
S
P
lo
c
a
l
p
h
e
ro
m
o
n
e
d
e
c
a
y
p
a
ra
m
e
ter
ba
se
d
on
t
h
e
Hid
d
e
n
M
a
rk
o
v
M
o
d
e
l
,
”
in
2
0
1
6
2
n
d
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Cl
o
u
d
C
o
mp
u
ti
n
g
T
e
c
h
n
o
lo
g
ies
a
n
d
Ap
p
li
c
a
ti
o
n
s
(
Clo
u
d
T
e
c
h
),
p
p
.
3
4
4
-
3
4
9
,
2
0
1
6
.
[2
3
]
S.
Bo
u
z
b
it
a
,
et
a
l.
,
“
Hid
d
e
n
M
a
rk
o
v
M
o
d
e
l
c
las
sif
ier
f
o
r
t
h
e
a
d
a
p
ti
v
e
A
CS
-
T
S
P
p
h
e
ro
m
o
n
e
p
a
ra
m
e
ter
,
”
in
B
i
o
in
s
p
ire
d
He
u
ristics
f
o
r Op
ti
miza
ti
o
n
,
pp.
1
53
-
16
9
,
2
0
1
9
.
[2
4
]
M.
L
a
lao
u
i,
e
t
a
l
.
,
“
Hid
d
e
n
M
a
rk
o
v
M
o
d
e
l
f
o
r
a
se
lf
-
lea
r
n
in
g
of
S
im
u
late
d
A
n
n
e
a
li
n
g
c
o
o
li
n
g
law
,
”
5
th
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
M
u
lt
ime
d
ia
C
o
mp
u
ti
n
g
a
n
d
S
y
ste
ms
(
IC
M
CS
),
p
p
.
5
5
8
-
5
6
3
,
2
0
1
6
.
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.
10
,
No
.
5
,
Octo
b
e
r
2
0
2
0
:
5
4
3
6
-
5444
5444
[2
5
]
M.
L
a
lao
u
i,
e
t
a
l
.
,
“A
se
lf
-
tu
n
e
d
sim
u
late
d
a
n
n
e
a
li
n
g
a
lg
o
r
it
h
m
u
sin
g
h
id
d
e
n
m
a
rk
o
v
m
o
d
e
l
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
8
,
n
o
.
1
,
p
p
.
291
-
2
9
8
,
2
0
1
8
.
[2
6
]
M.
L
a
lao
u
i,
e
t
a
l.
,
“A
se
lf
-
a
d
a
p
ti
v
e
v
e
r
y
f
a
st
si
m
u
late
d
a
n
n
e
a
li
n
g
b
a
se
d
on
Hid
d
e
n
M
a
rk
o
v
m
o
d
e
l
,
”
3
rd
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
f
Clo
u
d
Co
m
p
u
ti
n
g
T
e
c
h
n
o
lo
g
ies
a
n
d
A
p
p
li
c
a
ti
o
n
s
(
Clo
u
d
T
e
c
h
)
,
p
p
.
1
-
8,
2
0
1
7
.
[2
7
]
O.
A
o
u
n
,
e
t
a
l.
,
“
In
v
e
stig
a
ti
o
n
of
h
id
d
e
n
m
a
rk
o
v
m
o
d
e
l
f
o
r
th
e
tu
n
i
n
g
of
m
e
tah
e
u
risti
c
s
in
a
irl
in
e
sc
h
e
d
u
li
n
g
p
ro
b
lem
s
,”
IFA
C
-
Pa
p
e
rs
On
L
in
e
,
v
o
l.
49
,
no.
3,
p
p
.
3
4
7
-
3
5
2
,
20
16
.
[2
8
]
O.
A
o
u
n
,
e
t
a
l.
,
“
Hid
d
e
n
m
a
rk
o
v
m
o
d
e
l
c
las
sif
i
e
r
f
o
r
th
e
a
d
a
p
ti
ve
p
a
rti
c
le
s
w
a
r
m
o
p
ti
m
iz
a
ti
o
n
,
”
in
Rec
e
n
t
De
v
e
lo
p
me
n
ts i
n
M
e
ta
h
e
u
ristics
,
pp.
1
-
15
,
2
0
1
8
.
[2
9
]
A.
El
Af
ia,
et
a
l.
,
“
Hid
d
e
n
m
a
rk
o
v
m
o
d
e
l
c
o
n
tro
l
of
in
e
rti
a
w
e
ig
h
t
a
d
a
p
tati
o
n
f
or
P
a
rti
c
le
sw
a
r
m
o
p
ti
m
iza
ti
o
n
,
”
IFA
C
-
Pa
p
e
rs
On
L
in
e
,
v
o
l.
50
,
n
o
.
1
,
pp.
9
9
9
7
-
1
0
0
0
2
,
2
0
1
7
.
[3
0
]
L
.
A
.
Zad
e
h
,
“
F
u
z
z
y
se
ts
,
”
i
n
Ad
v
a
n
c
e
s
in
Fu
zz
y
S
y
ste
ms
-
Ap
p
li
c
a
ti
o
n
s
a
n
d
T
h
e
o
ry
:
Fu
zz
y
S
e
ts,
Fu
zz
y
L
o
g
ic,
An
d
Fu
zz
y
S
y
ste
ms
,
p
p
.
3
9
4
-
4
3
2
,
1
9
9
6
.
[3
1
]
J.
M
.
M
e
n
d
e
l,
“
F
u
z
z
y
lo
g
ic
s
y
ste
m
s
f
o
r
e
n
g
in
e
e
rin
g
:
a
tu
to
rial
,
”
Pro
c
e
e
d
in
g
s
o
f
th
e
IEE
E
,
v
o
l.
8
3
,
n
o
.
3
,
p
p
.
3
4
5
-
377
,
1
9
9
5
.
[3
2
]
T
.
J.
Ro
ss
,
“
F
u
z
z
y
lo
g
ic
w
it
h
e
n
g
in
e
e
rin
g
a
p
p
li
c
a
ti
o
n
s
,”
Jo
h
n
W
il
e
y
&
S
o
n
s,
2
0
10
.
[3
3
]
O.
A
.
M
.
A
li
,
e
t
a
l.
,
“
Co
m
p
a
riso
n
b
e
tw
e
e
n
th
e
e
ffe
c
ts
o
f
d
i
ff
e
re
n
t
ty
p
e
s
o
f
m
e
m
b
e
r
sh
ip
f
u
n
c
ti
o
n
s
o
n
f
u
z
z
y
lo
g
ic
c
o
n
tro
ll
e
r
p
e
rf
o
rm
a
n
c
e
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
r
n
a
l
o
f
Eme
rg
in
g
E
n
g
i
n
e
e
rin
g
Res
e
a
rc
h
a
n
d
T
e
c
h
n
o
lo
g
y
,
v
o
l.
3
,
n
o
.
3
,
p
p
.
7
6
-
83
,
2
0
1
5
.
[3
4
]
M
.
G
.
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“
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tro
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5
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riff
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ter
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[3
6
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.
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lt
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tra
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.
[3
7
]
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iv
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m
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t
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l.
,
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,
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iza
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to
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s se
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rc
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,
p
p.
1
9
1
-
215
,
2
0
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1
.
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),
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S
c
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m
m
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ica
ti
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.
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