I
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io
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Adv
a
nces in Applie
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s
(
I
J
AAS)
Vo
l.
6
,
No
.
4
,
Dec
em
b
er
2
0
1
7
,
p
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.
3
1
3
~3
1
8
I
SS
N:
2252
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8814
313
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I
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8814
IJ
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4
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Dec
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3
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o
p
ti
m
izat
io
n
p
r
o
b
lem
[
4
]
.
T
h
is
alg
o
r
i
th
m
is
b
u
ilt
o
n
t
h
e
g
en
et
ic
p
r
o
ce
s
s
es
in
li
v
i
n
g
o
r
g
an
is
m
s
.
T
h
is
f
o
llo
w
i
n
g
f
i
g
u
r
e
ex
p
lai
n
s
t
h
e
s
tep
o
f
t
h
e
Ge
n
etic
al
g
o
r
ith
m
p
r
o
ce
s
s
.
Fig
u
r
e
2.
S
tep
o
f
Gen
etic
A
l
g
o
r
ith
m
T
h
er
e
ar
e
th
r
ee
m
a
in
s
tep
s
in
Ge
n
etic
al
g
o
r
ith
m
s
s
u
ch
as
s
elec
tio
n
,
cr
o
s
s
o
v
er
a
n
d
m
u
tatio
n
.
Selectio
n
i
s
u
s
ed
to
r
ec
o
m
b
i
n
e
th
e
p
o
p
u
latio
n
w
it
h
t
h
e
h
i
g
h
est
p
r
o
b
ab
ilit
y
.
T
h
e
r
an
d
o
m
n
u
m
b
er
g
e
n
er
ated
is
co
m
b
in
ed
w
it
h
th
e
c
u
m
u
la
tiv
e
p
r
o
b
a
b
ilit
y
.
T
h
e
n
ea
r
est
v
al
u
e
is
tak
e
n
in
o
r
d
er
to
r
ep
lace
t
h
e
o
r
ig
i
n
al
v
al
u
e
o
f
th
e
p
o
p
u
latio
n
.
Fig
u
r
e
3
s
h
o
w
s
o
n
e
o
f
th
e
s
elec
tio
n
m
et
h
o
d
s
.
T
h
e
m
et
h
o
d
ab
o
v
e
is
R
o
u
lette
W
h
ee
l
Selectio
n
.
I
n
d
iv
id
u
a
ls
ar
e
m
ap
p
ed
in
to
a
lin
e
s
e
g
m
e
n
t
i
n
a
s
eq
u
e
n
ce
s
u
c
h
t
h
at
ea
ch
in
d
i
v
id
u
al
s
e
g
m
e
n
t
h
as
th
e
e
x
ac
t
s
a
m
e
s
ize
a
s
it
s
f
it
n
es
s
.
A
r
a
n
d
o
m
n
u
m
b
er
g
e
n
er
ated
.
I
n
d
iv
i
d
u
als
w
h
o
h
av
e
a
s
e
g
m
en
t
w
it
h
in
t
h
e
s
e
g
m
en
t
i
n
th
e
r
eg
io
n
o
f
t
h
e
r
an
d
o
m
n
u
m
b
er
s
w
il
l
b
e
s
elec
ted
[
6
]
.
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
u
n
til
t
h
e
n
u
m
b
er
o
f
in
d
iv
id
u
als
is
o
b
tai
n
ed
.
C
r
o
s
s
o
v
er
is
a
g
e
n
etic
al
g
o
r
ith
m
o
p
er
ato
r
to
m
ix
th
e
c
h
r
o
m
o
s
o
m
e
w
it
h
t
h
e
e
x
tr
a
ch
r
o
m
o
s
o
m
e
c
h
o
s
e
n
to
p
r
o
d
u
ce
ch
ild
ch
r
o
m
o
s
o
m
e
f
r
o
m
o
n
e
g
e
n
er
atio
n
to
th
e
n
e
x
t.
I
t
u
s
u
all
y
s
elec
t
s
s
o
m
e
q
u
alif
ied
p
ar
en
ts
[
5
]
.
T
h
e
q
u
alif
icatio
n
is
t
h
e
cr
o
s
s
o
v
er
r
ate
v
al
u
e.
T
h
is
v
al
u
e
r
elate
s
t
o
s
elec
t
th
e
p
ar
en
t
ch
r
o
m
o
s
o
m
e.
Fig
u
r
e
4
in
d
icate
s
t
h
e
cr
o
s
s
o
v
er
b
ased
o
n
o
n
e
cu
t
p
o
in
t
d
iv
is
io
n
.
M
u
tatio
n
is
a
g
e
n
etic
o
p
er
ato
r
e
m
p
lo
y
ed
to
m
ai
n
tai
n
g
e
n
e
tic
d
iv
er
s
it
y
f
r
o
m
o
n
e
g
en
er
atio
n
o
f
a
p
o
p
u
latio
n
o
f
g
en
et
ic
alg
o
r
it
h
m
ch
r
o
m
o
s
o
m
e
s
to
t
h
e
n
ex
t.
T
h
is
o
p
er
ato
r
r
ep
o
s
itio
n
s
t
h
e
ch
r
o
m
o
s
o
m
e
s
b
y
ex
c
h
a
n
g
i
n
g
th
e
v
al
u
e
o
f
th
e
ch
r
o
m
o
s
o
m
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Dyn
a
mic
K
ey
Ma
tr
ix
o
f H
ill C
ip
h
er Usin
g
Gen
etic
A
lg
o
r
ith
m
(
A
n
d
ysa
h
P
u
tera
Uta
ma
S
i
a
h
a
a
n
)
315
Fig
u
r
e
3.
R
o
u
lette
W
h
ee
l
Sele
ctio
n
Fig
u
r
e
4
.
On
e
C
u
t P
o
in
t Cro
s
s
o
v
er
Fig
u
r
e
5
.
S
w
ap
M
u
tatio
n
Fig
u
r
e
5
s
h
o
w
s
t
h
e
e
x
a
m
p
le
o
f
s
w
ap
m
u
tatio
n
.
W
e
ca
n
n
o
te
th
at
t
h
e
R
4
an
d
R
6
ar
e
s
wap
p
ed
.
T
h
e
ch
r
o
m
o
s
o
m
e
i
n
d
ex
d
o
es
n
o
t
c
h
an
g
e,
b
u
t
t
h
e
v
alu
e
o
f
t
h
e
in
d
ex
is
s
u
b
s
tit
u
ted
f
o
r
th
e
o
t
h
e
r
v
alu
e
i
n
t
h
e
o
th
er
in
d
ex
.
M
u
tatio
n
ca
u
s
e
s
m
o
v
e
m
en
t in
t
h
e
s
ea
r
c
h
s
p
ac
e
an
d
m
a
y
p
r
o
d
u
ce
s
tr
o
n
g
er
ch
r
o
m
o
s
o
m
e.
3.
RE
L
AT
E
D
WO
RK
T
h
e
p
r
ev
io
u
s
r
esear
ch
e
s
o
f
Hi
ll
C
ip
h
er
d
o
n
o
t
s
a
y
a
n
y
th
i
n
g
h
o
w
to
o
p
ti
m
ize
t
h
e
k
e
y
s
ea
r
ch
.
T
h
e
k
e
y
is
al
w
a
y
s
o
b
tain
ed
b
y
tr
ial
an
d
er
r
o
r
m
et
h
o
d
.
T
h
is
is
n
o
t
t
h
e
clev
er
id
ea
to
g
et
th
e
co
r
r
ec
t
k
e
y
i
n
Hill
C
ip
h
er
.
I
t
n
ee
d
s
th
e
p
r
o
p
er
d
eter
m
in
a
n
t
to
h
a
v
e
th
e
cip
h
er
te
x
t
r
etu
r
n
its
o
r
ig
i
n
al
m
es
s
ag
e.
I
t
s
ti
ll
r
eq
u
ir
es
m
o
r
e
ti
m
e
s
t
o
p
r
o
d
u
ce
th
e
k
e
y
m
an
u
all
y
.
On
ce
t
h
e
d
eter
m
i
n
a
n
t
g
ets
w
r
o
n
g
,
it
h
a
s
to
b
e
r
ec
alcu
lated
f
r
o
m
th
e
b
e
g
i
n
n
i
n
g
.
T
h
er
e
ar
e
n
in
e
n
u
m
b
er
s
co
m
p
o
s
ed
as th
e
k
e
y
f
o
r
t
h
e
en
cr
y
p
t
io
n
an
d
d
ec
r
y
p
tio
n
.
4.
M
E
T
H
O
DO
L
O
G
Y
E
v
er
y
c
h
r
o
m
o
s
o
m
e
in
Hill
C
i
p
h
er
co
n
s
i
s
ts
o
f
n
in
e
n
u
m
b
er
s
.
E
ac
h
g
e
n
e
h
as
a
v
al
u
e
b
et
w
ee
n
0
to
2
5
5
w
h
ic
h
r
ep
r
esen
ts
t
h
e
n
u
m
b
er
o
f
a
b
y
te.
Sin
ce
t
h
e
A
S
C
I
I
v
al
u
e
d
o
es
n
o
t
ex
ce
ed
2
5
5
,
w
e
d
o
n
o
t
tak
e
an
i
n
teg
er
as th
e
m
o
d
u
lar
ex
p
r
ess
io
n
K1
1
K
1
2
K
1
3
K
2
1
K
2
2
K
2
3
K
3
1
K
3
2
K
3
3
K
1
1
K
1
2
K
1
3
K
21
K
2
2
K
2
3
K
3
1
K
3
2
K
3
3
x
x
x
x
x
x
x
x
x
Fig
u
r
e
6.
Hill
C
ip
h
er
C
h
r
o
m
o
s
o
m
e
Fig
u
r
e
6
s
h
o
w
s
t
h
e
f
o
r
m
o
f
th
e
Hill
C
ip
h
er
ch
r
o
m
o
s
o
m
e.
T
h
e
m
atr
i
x
is
tr
an
s
f
o
r
m
ed
in
to
o
n
e
-
d
i
m
e
n
s
io
n
v
ec
to
r
.
E
ac
h
ce
ll
is
f
illed
w
ith
a
r
an
d
o
m
in
te
g
er
n
u
m
b
er
(
x
)
.
T
h
e
f
i
tn
e
s
s
f
u
n
ctio
n
ev
al
u
ates
th
e
d
eter
m
i
n
a
n
t
o
f
th
e
ch
r
o
m
o
s
o
m
e
b
y
t
h
i
s
f
o
llo
w
i
n
g
f
o
r
m
u
la.
=
(
1
)
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
.
4
,
Dec
em
b
er
2
0
1
7
:
3
1
3
–
3
1
8
316
W
h
er
e
F
=
Fit
n
e
s
s
D
=
Dete
r
m
i
n
an
t
T
h
e
g
en
et
ic
al
g
o
r
ith
m
o
f
t
h
is
m
et
h
o
d
is
r
ath
er
s
tr
aig
h
t
f
o
r
w
ar
d
t
h
an
t
h
e
o
n
e
o
f
a
u
s
u
al
m
et
h
o
d
f
o
r
s
ch
ed
u
lin
g
b
ec
au
s
e
w
e
d
o
n
o
t
h
av
e
to
s
ea
r
ch
u
n
til
t
h
e
f
itn
e
s
s
v
al
u
e
r
ea
ch
es
n
o
er
r
o
r
.
W
e
ju
s
t
s
ea
r
ch
t
h
e
id
ea
l
f
it
n
es
s
w
h
ich
d
o
es
n
o
t
co
n
tai
n
eq
u
al
v
al
u
e.
Si
n
ce
th
e
d
eter
m
i
n
an
t
is
i
n
t
h
e
o
d
d
n
u
m
b
er
,
it
is
g
o
o
d
f
o
r
Hill
C
ip
h
er
.
B
u
t,
in
t
h
i
s
ca
s
e,
w
e
s
t
ill to
f
i
n
d
u
n
til t
h
e
d
eter
m
i
n
an
t r
ea
ch
es 1
.
5.
T
E
ST
I
N
G
AND
I
M
P
L
E
M
E
NT
A
T
I
O
N
B
ef
o
r
e
k
n
o
w
i
n
g
h
o
w
th
e
m
et
h
o
d
w
o
r
k
s
,
f
ir
s
t th
in
g
f
ir
s
t is to
p
r
ep
ar
e
th
e
d
ata.
T
h
e
f
ir
s
t step
is
to
g
en
er
ate
t
h
e
i
n
itial p
o
p
u
latio
n
.
C
o
n
s
id
er
w
e
s
et
to
Ge
n
er
atio
n
is
3
0
an
d
P
o
p
u
latio
n
Size
is
2
0
.
T
h
e
in
itial
r
an
d
o
m
p
o
p
u
latio
n
is
g
i
v
en
i
n
tab
le
1
.
E
ac
h
n
u
m
b
er
i
n
t
h
e
ce
ll is
a
r
an
d
o
m
i
n
te
g
er
.
T
ab
le
1
.
I
n
itial P
o
p
u
latio
n
K
1
1
K
1
2
K
1
3
K
2
1
K
2
2
K
2
3
K
3
1
K
3
2
K
3
3
1
0
8
85
1
6
5
89
69
1
8
5
97
1
8
5
54
65
86
1
3
5
47
2
2
4
1
1
6
2
1
3
1
1
2
6
2
2
7
29
41
44
1
1
4
1
1
0
1
2
1
8
32
1
7
4
1
9
5
1
3
6
1
9
6
2
2
0
37
1
0
8
1
4
4
43
31
2
3
2
46
1
4
5
1
2
0
2
3
4
1
9
6
2
4
2
63
1
9
0
54
1
4
0
1
2
8
11
8
1
7
9
1
5
1
1
0
8
43
90
64
85
24
2
4
2
1
0
6
1
5
4
1
7
8
2
4
4
1
7
2
1
2
4
1
2
1
98
1
9
4
81
73
1
8
3
1
3
5
2
1
5
82
1
6
3
62
1
0
3
13
79
1
6
5
1
6
4
1
4
7
47
77
2
1
2
45
1
1
2
2
4
9
18
80
2
1
3
7
2
4
4
1
9
5
2
4
6
1
9
7
2
4
4
25
1
1
9
1
9
6
92
1
1
5
59
55
1
9
0
44
1
9
1
27
1
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E
v
er
y
c
h
r
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m
o
s
o
m
e
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s
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lc
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la
t
ed
to
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et
t
h
e
f
i
tn
e
s
s
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r
o
b
ab
ilit
y
a
n
d
cu
m
u
lati
v
e
p
r
o
b
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ilit
y
.
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h
e
n
e
x
t
s
tep
is
to
co
n
d
u
ct
s
elec
tio
n
,
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r
o
s
s
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er
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d
m
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ta
tio
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.
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ab
l
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s
h
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ilit
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m
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ilit
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ab
le
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.
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n
ess
,
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r
o
b
ab
ilit
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a
n
d
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u
m
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P
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Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
AA
S
I
SS
N:
2252
-
8814
Dyn
a
mic
K
ey
Ma
tr
ix
o
f H
ill C
ip
h
er Usin
g
Gen
etic
A
lg
o
r
ith
m
(
A
n
d
ysa
h
P
u
tera
Uta
ma
S
i
a
h
a
a
n
)
317
T
h
e
p
r
o
ce
s
s
o
f
s
elec
tio
n
,
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
h
as
m
o
d
i
f
i
ed
th
e
p
o
p
u
latio
n
s
tr
u
ct
u
r
e.
T
h
e
o
r
d
er
o
f
th
e
k
e
y
ch
a
n
g
es
to
th
e
o
th
er
n
u
m
b
er
f
r
o
m
o
t
h
er
ch
r
o
m
o
s
o
m
es.
T
h
e
n
e
w
g
e
n
er
atio
n
r
e
s
u
lts
f
r
o
m
t
h
e
late
s
t
u
p
d
ated
ch
r
o
m
o
s
o
m
e
s
as sa
w
in
T
ab
le
2
.
T
ab
le
3
.
Nex
t G
en
er
atio
n
P
o
p
u
latio
n
K
1
1
K
1
2
K
1
3
K
2
1
K
2
2
K
2
3
K
3
1
K
3
2
K
3
3
1
3
4
47
2
1
6
1
1
2
2
1
3
90
18
7
1
3
1
85
47
2
4
4
1
9
5
85
2
1
2
2
4
4
1
9
6
2
4
9
1
1
9
63
77
78
1
4
5
72
2
4
9
18
1
3
5
1
0
8
47
1
9
7
1
7
9
47
2
3
9
1
1
9
2
3
4
65
1
6
7
89
7
1
4
2
1
7
9
1
0
8
2
0
0
1
1
6
89
78
64
1
1
6
24
2
4
2
1
1
2
27
1
9
1
80
80
44
1
8
5
7
1
1
4
1
62
2
4
2
32
2
5
4
29
1
0
6
1
9
6
2
0
0
50
13
29
1
8
5
31
2
3
2
46
1
4
5
1
2
0
2
1
6
1
5
4
1
7
8
2
4
4
1
3
9
85
2
2
7
2
2
6
2
1
2
1
6
5
1
6
8
1
3
7
2
2
8
2
1
8
2
4
4
41
1
6
3
1
6
8
1
4
7
1
1
2
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4
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2
4
4
2
2
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85
1
4
7
2
3
4
69
97
1
3
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4
1
54
1
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7
47
77
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79
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66
1
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45
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3
7
50
1
3
9
26
47
2
2
6
45
47
1
8
7
2
4
2
1
0
8
T
h
is
p
r
o
ce
s
s
co
n
tin
u
e
s
to
th
e
latest
g
en
er
at
io
n
.
I
t
is
th
e
la
s
t
r
esu
lt
w
h
er
e
th
e
Hill
C
ip
h
e
r
k
e
y
s
ar
e
g
en
er
ated
.
A
t
th
e
e
n
d
o
f
th
e
p
r
o
ce
s
s
to
th
e
to
tal
o
f
th
e
Hil
l
C
ip
h
er
k
e
y
is
v
ar
ian
t.
T
ab
le
4
s
h
o
w
s
th
e
f
i
n
al
r
esu
lt o
f
t
h
e
Ge
n
etic
al
g
o
r
ith
m
.
T
ab
le
4
.
T
h
e
Fin
al
R
es
u
lt
K
1
1
K
1
2
K
1
3
K
2
1
K
2
2
K
2
3
K
3
1
K
3
2
K
3
3
1
4
7
69
62
1
4
7
2
3
2
82
29
1
4
7
1
4
7
1
4
7
62
1
4
7
2
3
2
2
4
6
29
82
1
4
7
2
4
6
82
1
4
7
2
3
2
69
2
4
6
82
2
4
6
72
1
4
7
Af
ter
g
e
tti
n
g
t
h
e
r
es
u
lt,
t
h
e
k
e
y
co
m
b
i
n
at
io
n
i
s
n
o
w
f
o
r
m
e
d
as
s
h
o
w
ed
in
T
ab
le
5
.
T
h
e
n
u
m
b
er
s
s
h
o
w
ed
in
t
h
e
b
lo
ck
s
ar
e
g
en
e
r
ated
b
y
th
e
g
e
n
etic
al
g
o
r
ith
m
.
W
e
ca
n
n
o
t
d
o
th
e
s
a
m
e
w
a
y
m
an
u
all
y
b
ec
au
s
e
it tak
es
m
u
ch
t
i
m
e
to
ca
lc
u
late
th
e
d
eter
m
i
n
an
t
m
a
n
u
a
ll
y
.
T
ab
le
5
.
T
h
e
Key
C
o
m
b
i
n
atio
n
K
e
y
1
K
e
y
2
K
e
y
3
1
4
7
69
62
1
4
7
62
1
4
7
82
1
4
7
2
3
2
1
4
7
2
3
2
82
2
3
2
2
4
6
29
69
2
4
6
82
29
1
4
7
1
4
7
82
1
4
7
2
4
6
2
4
6
72
1
4
7
T
h
e
k
e
y
in
t
h
e
b
lo
c
k
s
ec
t
io
n
is
u
s
ed
to
en
cr
y
p
t t
h
e
p
lain
te
x
t i
n
Hill
C
ip
h
er
alg
o
r
it
h
m
.
P
lain
tex
t
:
A
N
DYS
A
H
XX
(
65
78
68
89
83
65
72
88
88
)
Ke
y
:
(
147
69
62
147
232
82
29
147
147
)
C
ip
h
er
te
x
t
:
Ñ
Ë3
8
%`
H
8
(
209
203
51
56
37
17
96
72
56
)
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
.
4
,
Dec
em
b
er
2
0
1
7
:
3
1
3
–
3
1
8
318
Ke
y
I
n
v
er
s
e
:
(
82
131
218
249
17
1
228
57
40
241
)
P
lain
tex
t
:
A
N
DYS
A
H
XX
(
65
78
68
89
83
65
72
88
88
)
W
e
s
ee
th
er
e
ar
e
t
h
r
ee
k
e
y
s
p
r
o
d
u
ce
d
b
y
t
h
e
g
en
e
tic
al
g
o
r
ith
m
.
W
e
h
a
v
e
tes
ted
th
e
f
ir
s
t
k
e
y
ab
o
v
e
.
T
h
e
d
eter
m
i
n
an
t
h
as
v
alu
e
1
an
d
it
is
s
u
itab
le
f
o
r
th
e
Hill
C
ip
h
er
p
r
o
ce
s
s
.
W
h
en
t
h
e
d
eter
m
in
a
n
t
i
s
1
,
it
ca
n
b
r
in
g
t
h
e
cip
h
er
te
x
t b
ac
k
to
th
e
p
lain
tex
t a
n
d
v
i
s
e
v
er
s
a.
6.
CO
NCLU
SI
O
N
On
t
h
e
Hill
C
ip
h
er
al
g
o
r
ith
m
th
at
u
s
es
a
3
x
3
m
atr
i
x
,
s
ea
r
c
h
in
g
k
e
y
t
h
at
h
a
s
t
h
e
p
r
o
p
er
d
e
ter
m
i
n
an
t
tak
es
ti
m
e.
I
f
w
e
p
er
f
o
r
m
i
n
t
h
at
w
a
y
,
it
s
lo
w
s
d
o
w
n
th
e
p
r
o
ce
s
s
o
f
cr
y
p
to
g
r
ap
h
y
.
Ge
n
eti
c
alg
o
r
it
h
m
s
g
r
ea
tl
y
ass
is
t
t
h
e
p
r
o
ce
s
s
o
f
t
h
e
en
cr
y
p
t
io
n
a
n
d
t
h
e
d
ec
r
y
p
tio
n
o
n
th
e
Hi
ll
C
ip
h
er
.
I
t
p
r
o
d
u
ce
s
a
s
er
ies
o
f
n
u
m
b
er
s
q
u
ick
l
y
.
T
h
is
tech
n
iq
u
e
g
e
n
er
ates
s
e
v
er
al
alter
n
ati
v
es
th
at
c
an
b
e
u
s
ed
o
n
th
e
Hill
C
ip
h
er
alg
o
r
ith
m
.
I
n
t
h
is
s
tu
d
y
,
w
e
co
n
clu
d
e
t
h
at
th
e
g
en
et
ic
al
g
o
r
ith
m
h
as
a
v
alu
ab
le
co
n
tr
ib
u
tio
n
w
h
en
co
m
b
in
ed
w
it
h
t
h
e
Hill
C
ip
h
er
m
e
th
o
d
.
RER
EREN
CES
[1
]
A
b
d
u
ll
a
h
,
A
.
A
.
,
Kh
a
laf
,
R.
,
&
Riza
,
M
.
(2
0
1
5
).
A
Re
a
li
z
a
b
le Qu
a
n
tu
m
T
h
re
e
-
P
a
ss
P
ro
to
c
o
l
A
u
th
e
n
ti
c
a
ti
o
n
.
M
a
th
e
m
a
ti
c
a
l
P
r
o
b
lem
s in
En
g
i
n
e
e
rin
g
.
[2
]
Ch
a
se
,
J.,
&
Da
v
is,
M
.
(2
0
1
0
).
Ex
ten
d
i
n
g
th
e
Hill
C
ip
h
e
r.
[3
]
Ch
o
w
d
h
u
ry
,
S
.
I.
,
S
h
o
h
a
g
,
S
.
A
.
,
&
S
a
h
id
,
H.
(2
0
1
1
).
A
S
e
c
u
re
d
M
e
ss
a
g
e
T
ra
n
sa
c
ti
o
n
A
p
p
ro
a
c
h
b
y
D
y
n
a
m
ic
Hil
l
Cip
h
e
r
G
e
n
e
ra
ti
o
n
a
n
d
Dig
e
st Co
n
c
a
ten
a
ti
o
n
.
In
ter
n
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
Co
m
p
u
ter A
p
p
li
c
a
ti
o
n
s,
2
3
(
9
),
2
5
-
3
1
.
[4
]
G
h
a
n
b
a
ri,
A
.
A
.
,
Bro
u
m
a
n
d
n
ia,
A
.
,
Na
v
id
i,
H.,
&
A
h
m
a
d
i,
A
.
(2
0
1
2
)
.
Bra
in
C
o
m
p
u
ter
In
terf
a
c
e
w
it
h
G
e
n
e
ti
c
A
l
g
o
rit
h
m
.
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
In
f
o
r
m
a
ti
o
n
a
n
d
Co
m
m
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
y
Re
s
e
a
rc
h
,
2
(1
),
7
9
-
86.
[5
]
L
in
,
C.
H.,
Yu
,
J.
L
.
,
L
iu
,
J.
C.
,
L
a
i,
W
.
S
.
,
&
Ho
,
C.
H.
(2
0
0
9
).
G
e
n
e
ti
c
A
lg
o
rit
h
m
f
o
r
S
h
o
rtes
t
Driv
in
g
T
i
m
e
in
In
telli
g
e
n
t
T
ra
n
sp
o
rtati
o
n
S
y
ste
m
s.
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Hy
b
rid
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
,
2
(1
),
2
1
-
30.
[6
]
S
z
é
n
á
si,
S
.
,
&
V
á
m
o
ss
y
,
Z.
(2
0
1
3
).
Im
p
le
m
e
n
tatio
n
o
f
a
Distrib
u
t
e
d
G
e
n
e
ti
c
A
lg
o
rit
h
m
f
o
r
P
a
ra
m
e
ter
Op
ti
m
iza
ti
o
n
in
a
Ce
ll
Nu
c
lei
De
tec
ti
o
n
P
r
o
jec
t
.
A
c
ta P
o
ly
tec
h
n
ica
Hu
n
g
a
rica
,
1
0
(4
),
5
9
-
86
.
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