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Ka
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Dep
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1.
I
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RO
D
UCT
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A
M
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lt
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Mito
s
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s
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n
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Alg
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e
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ce
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s
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A
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n
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F
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m
m
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t
h
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th
e
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m
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s
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ce
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w
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clei
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etic
all
y
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tical
[
1
-
4
]
.
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n
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ilar
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2
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M
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Gen
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A
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MM
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m
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ild
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ased
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ated
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ated
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r
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cr
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lled
m
u
ltip
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m
ito
s
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cr
o
s
s
o
v
er
[
5
]
.
Gen
etic
A
l
g
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ith
m
(
G
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is
th
e
m
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s
t
co
m
m
o
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b
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lo
g
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i
n
s
p
ir
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tech
n
iq
u
es
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s
o
lv
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o
p
ti
m
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n
p
r
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b
lem
f
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w
id
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an
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m
at
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m
atic
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co
m
p
u
tatio
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f
in
a
n
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f
o
r
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asti
n
g
,
m
ed
ical
an
d
m
a
n
y
m
o
r
e
[
6
-
1
4
]
.
I
t
w
a
s
f
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t
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tr
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d
b
y
J
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ll
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in
1
9
7
5
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p
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izat
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tech
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iq
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ld
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[
1
5
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Fig
u
r
e
1
s
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IJ
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AI
I
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N:
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8938
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in
a
p
o
p
u
latio
n
h
as
to
b
e
d
iv
e
r
s
e.
GA
h
as
it
s
o
w
n
w
ea
k
n
es
s
w
h
er
e
it
h
a
s
th
e
p
o
s
s
ib
ilit
y
o
f
b
ein
g
tr
ap
p
ed
in
to
a
lo
ca
l
o
p
tim
u
m
w
h
er
e
it
c
an
ca
u
s
e
p
r
e
m
at
u
r
e
co
n
v
er
g
en
ce
d
u
e
to
lo
w
d
i
v
er
s
it
y
.
Sin
ce
m
u
tatio
n
a
n
d
cr
o
s
s
o
v
er
o
p
er
ato
r
s
ar
e
th
e
h
e
ar
t
o
f
g
e
n
etic
al
g
o
r
ith
m
,
it
ca
u
g
h
t
atte
n
tio
n
m
an
y
r
esear
ch
e
r
s
ar
o
u
n
d
th
e
w
o
r
ld
to
in
v
e
s
ti
g
ate
a
n
d
m
ak
e
i
m
p
r
o
v
e
m
e
n
t
o
f
t
h
e
o
r
ig
i
n
al
G
A
f
o
r
o
u
ts
ta
n
d
in
g
p
er
f
o
r
m
an
ce
in
f
i
n
d
in
g
it
s
o
p
ti
m
u
m
s
o
lu
tio
n
[
1
7
-
1
8
]
.
A
j
a
y
i
n
[
1
9
]
p
r
o
p
o
s
ed
Fin
e
-
T
u
n
ed
cr
o
s
s
o
v
er
in
s
p
ir
ed
b
y
u
n
t
ap
p
ed
id
ea
o
f
m
ito
ch
o
n
d
r
ial
DNA
in
o
r
d
er
to
i
m
p
r
o
v
e
t
h
e
p
er
f
o
r
m
a
n
c
e
o
f
n
o
r
m
a
l
G
A
b
y
r
ed
u
cin
g
t
h
e
r
a
te
o
f
d
il
u
tio
n
o
f
d
iv
er
s
i
t
y
a
n
d
d
elay
t
h
e
co
n
v
er
g
en
ce
.
Da
n
g
in
[
2
0
]
s
h
o
w
s
t
h
at
J
u
m
p
k
f
u
n
ct
io
n
h
elp
to
b
u
r
s
t
th
e
d
iv
er
s
it
y
to
r
ea
ch
th
e
g
lo
b
al
o
p
ti
m
u
m
.
I
n
[
2
1
]
,
Han
ee
n
p
r
esen
t
s
t
h
e
id
ea
o
f
ad
ap
tiv
e
p
ar
a
m
eter
co
n
tr
o
l to
en
h
an
ce
th
e
ef
f
icie
n
c
y
o
f
th
e
al
g
o
r
ith
m
b
y
p
r
o
v
id
in
g
a
n
e
f
f
ec
tiv
e
b
ala
n
ce
b
et
w
ee
n
d
iv
er
s
it
y
o
f
t
h
e
p
o
s
s
i
b
le
s
o
lu
tio
n
s
an
d
cr
o
s
s
o
v
er
s
elec
tio
n
.
Sh
i
k
h
a
in
[
2
2
]
p
r
o
p
o
s
ed
E
liti
s
t
an
d
DG
C
A
(
D
y
n
a
m
ic
Ge
n
etic
C
lu
s
te
r
in
g
A
l
g
o
r
it
h
m
)
to
r
ed
u
ce
th
e
e
f
f
ec
t
o
f
p
r
e
m
at
u
r
e
co
n
v
er
g
en
ce
p
r
o
b
le
m
.
I
n
[
2
3
]
,
J
am
es
i
n
cl
u
d
e
t
h
e
d
i
v
e
r
s
it
y
as
a
s
e
lectio
n
p
r
o
ce
s
s
in
G
A
w
h
er
e
h
e
p
r
o
p
o
s
ed
t
w
o
w
a
y
s
to
m
ea
s
u
r
e
t
h
e
d
iv
er
s
it
y
o
f
a
p
o
p
u
latio
n
.
I
t
is
f
o
u
n
d
t
h
at
b
y
m
ak
in
g
th
e
d
iv
er
s
it
y
a
s
o
n
e
o
f
th
e
f
ac
to
r
s
to
b
e
co
n
s
id
er
ed
d
u
r
in
g
th
e
s
elec
tio
n
p
r
o
ce
s
s
i
m
p
r
o
v
e
th
e
p
er
f
o
r
m
a
n
ce
o
f
G
A
f
r
o
m
p
r
e
m
at
u
r
e
co
n
v
er
g
en
ce
.
A
p
r
ilia
i
n
[
2
4
]
p
r
o
p
o
s
ed
h
y
b
r
id
GA
wh
er
e
o
r
ig
in
al
G
A
is
co
m
b
i
n
ed
w
ith
V
NS
(
Var
iab
le
Neig
h
b
o
r
h
o
o
d
Sear
ch
)
to
o
v
er
co
m
e
th
e
s
h
o
r
tco
m
i
n
g
s
o
n
GA
o
n
p
r
e
m
at
u
r
e
co
n
v
er
g
e
n
ce
an
d
lo
ca
l
ex
p
l
o
itatio
n
.
I
n
[
2
5
]
,
Am
m
ar
p
r
o
p
o
s
e
an
o
th
er
h
y
b
r
id
GA
w
h
er
e
h
e
co
m
b
i
n
ed
r
eo
r
d
er
in
g
cr
o
s
s
o
v
er
an
d
f
u
s
i
o
n
cr
o
s
s
o
v
er
to
r
ed
u
ce
t
h
e
p
o
s
s
ib
ilit
ie
s
o
f
p
r
e
m
at
u
r
e
co
n
v
e
r
g
en
ce
.
T
h
is
p
ap
er
p
r
esen
ts
t
h
e
id
ea
to
i
m
p
r
o
v
e
th
e
p
er
f
o
r
m
a
n
ce
o
f
s
i
m
p
le
G
A
f
r
o
m
p
r
e
m
a
tu
r
e
co
n
v
er
g
e
n
ce
an
d
i
m
p
r
o
v
e
t
h
e
d
iv
er
s
it
y
o
f
h
ig
h
-
q
u
ali
t
y
i
n
d
iv
id
u
al
s
b
y
p
r
o
p
o
s
in
g
Mu
ltip
l
e
Mito
s
is
Ge
n
etic
Alg
o
r
it
h
m
(
MM
GA
)
w
h
er
e
it
p
r
o
d
u
ce
h
ig
h
er
n
u
m
b
er
o
f
c
h
ild
r
en
i
n
o
n
e
g
en
er
atio
n
.
H
av
in
g
g
r
ea
ter
n
u
m
b
er
o
f
c
h
i
ld
r
en
in
cr
ea
s
e
t
h
e
p
o
s
s
ib
ilit
ies to
f
in
d
t
h
e
g
lo
b
al
o
p
tim
u
m
a
n
d
a
v
o
id
p
r
em
at
u
r
e
co
n
v
er
g
e
n
ce
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
Alg
o
rit
h
m
Fig
u
r
e
1
s
h
o
w
s
t
h
e
f
lo
w
ch
ar
t
o
f
s
i
m
p
le
Ge
n
etic
Alg
o
r
it
h
m
a
n
d
Fi
g
u
r
e
2
s
h
o
w
s
t
h
e
f
l
o
w
c
h
ar
t
o
f
Mu
ltip
le
Mito
s
i
s
Gen
etic
A
l
g
o
r
ith
m
.
A
s
d
is
c
u
s
s
ed
ab
o
v
e,
s
i
m
p
le
G
A
h
av
e
p
o
ten
tial
to
eli
m
i
n
ate
g
o
o
d
q
u
alit
y
o
f
g
en
e
s
in
t
h
e
n
e
w
g
en
er
atio
n
w
h
i
le
th
e
p
o
p
u
latio
n
g
o
in
g
th
r
o
u
g
h
t
h
e
p
r
o
ce
s
s
o
f
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
.
T
o
im
p
r
o
v
e
t
h
e
p
er
f
o
r
m
an
ce
o
f
GA
to
f
i
n
d
th
e
b
est
o
p
ti
m
u
m
a
n
s
w
er
w
h
ile
m
a
in
ta
in
i
n
g
t
h
e
g
o
o
d
q
u
alit
y
g
en
e
s
,
th
er
e
ar
e
th
r
ee
d
if
f
er
e
n
t
s
tep
s
p
r
o
p
o
s
ed
in
Mu
ltip
le
Mito
s
is
Ge
n
etic
A
l
g
o
r
ith
m
.
Step
1
: Set
Mu
ltip
l
y
i
n
g
Fac
to
r
,
M
I
n
MM
G
A
,
af
ter
s
elec
tio
n
p
r
o
ce
s
s
d
o
n
e,
a
m
u
l
tip
l
y
i
n
g
f
ac
to
r
,
M
is
s
e
t
b
y
th
e
u
s
er
o
r
it
ca
n
also
b
e
g
en
er
ated
r
a
n
d
o
m
l
y
.
M
w
il
l
d
eter
m
i
n
e
t
h
e
n
u
m
b
er
o
f
c
h
ild
r
en
t
h
at
w
i
ll
b
e
p
r
o
d
u
ce
d
in
t
h
e
n
e
x
t
g
en
er
atio
n
.
M
is
also
d
eter
m
i
n
i
n
g
t
h
e
n
u
m
b
er
o
f
g
e
n
er
atio
n
s
an
d
s
to
p
p
in
g
cr
iter
ia
f
o
r
th
e
Mu
ltip
le
Mito
s
is
Gen
etic
A
l
g
o
r
ith
m
.
Step
2
: M
u
ltip
le
Mito
s
i
s
C
r
o
s
s
o
v
er
Mu
ltip
le
Mito
s
is
C
r
o
s
s
o
v
er
i
s
p
r
o
p
o
s
ed
to
m
ai
n
tai
n
t
h
e
g
o
o
d
q
u
alit
y
g
e
n
es
t
o
p
r
o
d
u
ce
d
g
r
ea
ter
n
u
m
b
er
o
f
ch
ild
r
en
li
m
ited
b
y
t
h
e
m
u
l
ti
p
ly
in
g
f
ac
to
r
,
M.
I
f
th
e
v
a
lu
e
o
f
M
is
1
0
m
ea
n
s
th
a
t
1
g
en
e
w
il
l
p
r
o
d
u
ce
s
1
0
n
u
m
b
er
o
f
ch
ild
r
en
in
1
g
en
e
r
atio
n
.
B
y
d
o
in
g
t
h
is
,
q
u
a
lit
y
g
en
e
s
h
a
v
e
m
o
r
e
p
o
ten
tial
t
o
p
r
o
d
u
ce
ch
ild
r
e
n
in
h
er
i
t
t
h
e
g
o
o
d
q
u
alit
y
o
f
t
h
e
p
ar
en
ts
to
p
r
ev
en
t
t
h
e
p
o
te
n
tial
o
f
th
e
g
o
o
d
g
e
n
es
to
b
e
eli
m
in
a
ted
in
t
h
e
o
r
ig
in
al
p
r
o
ce
s
s
o
f
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
.
Step
3
: M
in
i L
o
o
p
I
n
s
i
m
p
le
G
A
,
s
elec
ted
p
ar
en
ts
w
ill
g
o
th
r
o
u
g
h
th
e
p
r
o
ce
s
s
o
f
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
o
n
e
t
i
m
e
in
o
n
e
g
e
n
er
atio
n
.
I
n
t
h
e
n
e
x
t
g
en
er
atio
n
,
t
h
e
o
ld
p
ar
en
ts
will
b
e
r
ep
lace
d
b
y
t
h
e
n
e
w
p
o
p
u
latio
n
w
h
ic
h
w
ill
r
ed
u
ce
th
e
p
o
s
s
ib
ilit
y
f
o
r
f
ast
co
n
v
er
g
e
n
ce
.
I
n
MM
G
A
,
m
in
i
lo
o
p
is
p
r
o
p
o
s
ed
to
p
r
ev
en
t
g
o
o
d
p
ar
en
ts
f
r
o
m
b
ein
g
e
li
m
in
ated
in
th
e
n
e
x
t
g
en
er
atio
n
a
n
d
p
r
o
d
u
ce
m
o
r
e
q
u
alit
y
ch
ild
r
en
t
h
at
i
n
h
er
it
g
o
o
d
g
en
es
f
r
o
m
th
e
p
ar
en
ts
w
h
er
e
it
w
i
ll h
elp
to
d
o
f
ast co
n
v
er
g
e
n
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
IJ
-
AI
Vo
l.
8
,
No
.
3
,
Sep
tem
b
er
20
1
9
:
2
52
–
2
58
254
Fig
u
r
e
1
.
Si
m
p
le
Ge
n
etic
A
l
g
o
r
ith
m
Fig
u
r
e
2
.
Mu
ltip
le
Mito
s
i
s
Ge
n
etic
A
l
g
o
r
ith
m
E
x
p
er
i
m
e
n
tal
r
esu
lt
w
ill
s
h
o
w
t
h
e
ad
v
an
ta
g
e
o
f
Mu
l
tip
le
Mito
s
is
Ge
n
etic
A
lg
o
r
it
h
m
i
n
p
r
o
d
u
cin
g
m
o
r
e
q
u
alit
y
g
e
n
es
f
r
o
m
t
h
e
s
elec
ted
p
ar
en
ts
to
m
ai
n
tai
n
t
h
e
d
iv
er
s
it
y
a
n
d
p
r
ev
en
t
p
r
em
at
u
r
e
co
n
v
er
g
e
n
ce
.
T
o
test
th
e
p
er
f
o
r
m
a
n
ce
o
f
Mu
ltip
le
Mito
s
is
Ge
n
etic
A
l
g
o
r
ith
m
i
n
g
e
n
er
atin
g
g
r
ea
t
d
iv
er
s
it
y
a
n
d
f
ast
co
n
v
er
g
en
ce
,
De
J
o
n
g
’
s
s
p
h
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258
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(
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,
Ma
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s
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RE
F
E
R
E
NC
E
S
[1
]
M
it
su
h
iro
Ya
n
a
g
id
a
,
“
T
h
e
Ro
le
o
f
M
o
d
e
l
Org
a
n
ism
s
in
th
e
Hi
sto
ry
o
f
M
it
o
sis
Re
se
a
rc
h
”
,
Co
l
d
S
p
rin
g
H
a
rb
Per
sp
e
c
t
Bi
o
l
d
o
i:
1
0
.
1
1
0
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/cs
h
p
e
rsp
e
c
t.
a
0
1
5
7
6
8
,
2
0
1
6
.
[2
]
Clo
ti
l
d
e
Ca
d
a
rt
e
t.
a
l,
“
Ex
p
lo
rin
g
th
e
F
u
n
c
ti
o
n
o
f
Ce
ll
S
h
a
p
e
a
n
d
S
ize
d
u
ri
n
g
M
it
o
sis”
,
Ce
ll
Pre
ss
,
v
o
l.
2
9
(2
),
p
p
.
159
-
1
6
9
,
2
0
1
4
.
[3
]
Ra
d
h
ik
a
M
Ba
v
le
a
n
d
Ra
d
h
ik
a
,
“
M
it
o
sis
a
t
a
G
lan
c
e
”
,
J
o
u
rn
a
l
o
f
Or
a
l
a
n
d
M
a
x
il
l
o
fa
c
i
a
l
P
a
th
o
lo
g
y
:
JO
M
F
P
.
1
8
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S2
-
5
.
1
0
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4
1
0
3
/
0
9
7
3
-
0
2
9
X
.
1
4
1
1
7
5
,
2
0
1
4
.
[4
]
He
r
m
in
P
a
n
c
a
sa
k
ti
e
t.
a
l,
“
Ch
ro
m
o
so
m
e
s
a
n
d
M
it
o
ti
c
Ce
ll
Div
isio
n
P
h
a
se
in
On
io
n
R
o
o
ts
a
f
ter
2
4
Ho
u
rs
A
c
e
to
o
rc
e
in
S
o
a
k
in
g
T
i
m
e
”
,
J
o
u
rn
a
l
(
BIOM
A)
,
v
o
l.
1
4
(
2
)
p
p
.
4
6
-
4
8
,
2
0
1
2
.
[5
]
Ad
è
l
e
L.
M
a
r
s
t
o
n
a
n
d
An
g
e
l
i
k
a
A
m
o
n
,
“
E
r
r
a
t
u
m
:
M
e
i
o
s
i
s
:
C
e
l
l
-
c
y
c
l
e
C
o
n
t
r
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l
s
S
h
u
f
f
l
e
a
n
d
D
e
a
l
”
,
J
o
u
r
n
a
l
o
f
N
a
t
u
r
e
R
e
v
i
e
w
s
M
o
l
e
c
u
l
a
r
C
e
l
l
B
i
o
l
o
g
y
,
p
p
.
9
8
3
-
9
9
7
,
2
0
0
5
.
[6
]
N.
Ch
a
k
ra
b
o
rti
,
“
G
e
n
e
ti
c
A
l
g
o
rit
h
m
s
in
M
a
teria
ls
De
sig
n
a
n
d
P
r
o
c
e
ss
in
g
”
,
J
o
u
rn
a
l
o
f
In
ter
n
a
t
io
n
a
l
M
a
ter
i
a
l
Rev
iews
,
v
o
l.
4
9
,
p
p
.
2
4
6
-
2
6
0
,
2
0
1
3
.
[7
]
R.
Kira
n
Ku
m
a
r
e
t.
a
l,
“
Di
m
e
n
s
io
n
a
li
ty
Re
d
u
c
ti
o
n
a
n
d
Clas
sif
ica
ti
o
n
o
f
H
y
p
e
rsp
e
c
tral
I
m
a
g
e
s
u
sin
g
G
e
n
e
ti
c
A
l
g
o
rit
h
m
”
,
In
d
o
n
e
sia
n
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
,
v
o
l
.
3
,
n
o
.
3
,
p
p
.
5
0
3
-
5
1
1
,
2
0
1
6
.
[8
]
T
i
m
m
y
M
a
n
n
in
g
e
t.
a
l,
“
Na
tu
ra
ll
y
S
e
lec
ti
n
g
S
o
lu
ti
o
n
s
T
h
e
Us
e
o
f
G
e
n
e
ti
c
A
l
g
o
rit
h
m
s
In
Bio
in
f
o
r
m
a
ti
c
s”
,
J
o
u
rn
a
l
o
f
Bi
o
e
n
g
in
e
e
re
d
,
p
p
.
2
6
6
-
2
7
8
,
2
0
1
3
.
[9
]
Hs
in
-
P
in
F
u
e
t.
a
l,
“
A
De
c
isio
n
S
u
p
p
o
rt
S
y
ste
m
Ba
s
e
d
o
n
A
G
e
n
e
ti
c
A
l
g
o
rit
h
m
f
o
r
T
h
e
Util
iza
ti
o
n
o
f
Le
f
to
v
e
rs”
,
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ta
ti
o
n
a
l
I
n
telli
g
e
n
c
e
,
v
o
l.
9
,
p
p
.
4
8
3
-
4
9
6
,
2
0
1
6
.
[1
0
]
Jo
sé
A
lb
e
rto
S
a
li
n
a
s
-
P
é
re
z
e
t.
a
l,
“
Ev
o
lu
ti
o
n
a
ry
A
l
g
o
rit
h
m
f
o
r
th
e
A
n
a
l
y
sis
o
f
M
e
n
tal
Diso
rd
e
rs
in
M
a
c
ro
-
u
r
b
a
n
A
re
a
s: T
h
e
Ca
s
e
o
f
Ba
rc
e
lo
n
a
”
,
S
p
a
ti
a
l
Ec
o
n
o
mic
An
a
lys
is,
p
p
.
2
7
0
-
2
8
8
,
2
0
1
5
.
[1
1
]
M
in
-
Yu
a
n
Ch
e
n
g
e
t.
a
l,
“
Op
ti
m
iz
in
g
M
ix
tu
re
P
ro
p
e
rti
e
s
o
f
Bio
d
i
e
se
l
P
ro
d
u
c
ti
o
n
Us
in
g
Ge
n
e
ti
c
A
l
g
o
rit
h
m
-
Ba
se
d
Ev
o
lu
ti
o
n
a
ry
S
u
p
p
o
rt
V
e
c
to
r
M
a
c
h
in
e
”
,
I
n
ten
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Gr
e
e
n
En
e
rg
y
,
p
p
.
1
5
9
9
-
1
6
0
7
,
2
0
1
6
.
[1
2
]
M
u
h
a
m
m
a
d
A
ri
f
e
t.
a
l,
“
Co
u
n
ti
n
g
o
f
P
e
o
p
le
in
th
e
Ex
trem
e
l
y
D
e
n
se
Cro
w
d
u
sin
g
G
e
n
e
ti
c
A
lg
o
ri
th
m
a
n
d
Blo
b
s
Co
u
n
ti
n
g
”
,
I
n
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Arti
f
ica
l
I
n
telli
g
e
n
c
e
,
v
o
l.
2
,
2
0
1
3
.
[1
3
]
A
h
m
a
d
Ya
n
i
e
t.
a
l,
“
Op
ti
m
u
m
R
e
a
c
ti
v
e
P
o
w
e
r
to
I
m
p
ro
v
e
P
o
w
e
r
F
a
c
to
r
in
I
n
d
u
stry
Us
in
g
Ge
n
e
ti
c
A
lg
o
ri
th
m
”
,
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
2
0
1
9
.
[1
4
]
Am
in
a
B
e
d
b
o
u
d
i
e
t.
a
l,
“
A
He
ter
o
g
e
n
e
o
u
s
P
o
p
u
lati
o
n
-
Ba
se
d
G
e
n
e
ti
c
A
lg
o
rit
h
m
f
o
r
D
a
ta
Clu
ste
ri
n
g
”
,
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
I
n
fo
rm
a
t
ics
(
IJ
EE
I),
v
o
l.
5
,
n
o
.
3
,
p
p
.
2
7
5
-
2
8
4
,
2
0
1
7
.
[1
5
]
L
.
Ha
ld
u
ra
i
e
t.
a
l,
“
A
S
tu
d
y
o
n
G
e
n
e
ti
c
A
lg
o
rit
h
m
a
n
d
Its
A
p
p
li
c
a
ti
o
n
”
,
I
n
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
En
g
i
n
e
e
rin
g
,
v
o
l.
4
,
p
p
.
1
3
9
-
1
4
3
,
2
0
1
6
.
[1
6
]
P
a
tri
c
k
Kw
a
k
u
Ku
d
jo
e
t.
a
l,
”
Re
v
iew
o
f
G
e
n
e
ti
c
A
l
g
o
rit
h
m
a
n
d
A
p
p
li
c
a
ti
o
n
in
S
o
f
tw
a
re
Tes
ti
n
g
”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
m
p
u
ter
A
p
p
l
ica
ti
o
n
s
,
p
p
.
1
-
6
,
v
o
l
.
1
6
0
(
2
),
2
0
1
7
.
[1
7
]
A
.
J.
U
m
b
a
rk
a
r1
a
n
d
P
.
D.
S
h
e
th
2
,
“
Cro
ss
o
v
e
r
Op
e
ra
to
rs
in
G
e
n
e
ti
c
A
lg
o
rit
h
m
s:
A
Re
v
ie
w”
,
J
o
u
rn
a
l
o
n
S
o
f
t
Co
mp
u
t
in
g
,
p
p
.
1
0
8
3
-
1
0
9
2
,
2
0
1
5
.
[1
8
]
S
iew
M
o
o
i
L
i
m
e
t.
a
l,
“
Cro
ss
o
v
e
r
a
n
d
M
u
tati
o
n
O
p
e
ra
to
rs
Of
G
e
n
e
ti
c
A
l
g
o
rit
h
m
s”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
c
h
in
e
L
e
a
r
n
in
g
a
n
d
Co
m
p
u
ti
n
g
,
V
o
l
.
7
,
No
.
1
,
p
p
.
9
-
1
2
,
2
0
1
7
.
[1
9
]
A
ja
y
S
h
re
sth
a
a
n
d
A
u
sif
M
a
h
m
o
o
d
,
“
Im
p
ro
v
in
g
Ge
n
e
ti
c
A
l
g
o
rit
h
m
w
it
h
F
in
e
-
T
u
n
e
d
Cr
o
ss
o
v
e
r
a
n
d
S
c
a
led
A
rc
h
it
e
c
tu
re
”
,
J
o
u
rn
a
l
o
f
M
a
t
h
e
ma
ti
c
s
,
p
p
.
1
-
1
0
,
2
0
1
6
.
[2
0
]
Du
c
-
Cu
o
n
g
Da
n
g
e
t.
a
l,
“
Em
e
r
g
e
n
c
e
o
f
Div
e
rsi
t
y
a
n
d
Its
Be
n
e
f
it
s
f
o
r
Cro
ss
o
v
e
r
in
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