I
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na
l J
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Art
if
icia
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t
ellig
ence
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I
J
-
AI
)
Vo
l.
6
,
No
.
3
,
Sep
tem
b
er
2017
,
p
p
.
1
39
~
1
4
2
I
SS
N:
2252
-
8938
,
DOI
: 1
0
.
1
1
5
9
1
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j
ai.
v
6
.
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.
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1
39
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a
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De
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rt
a
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In
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C
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A
uth
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:
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-
k
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m
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Un
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it
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T
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6
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s
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A
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r
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m
ail:
a
m
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k
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ab
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r
@
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m
a
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o
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
t
h
e
r
ec
en
t
d
ec
ad
es,
d
y
n
a
m
ic
o
p
ti
m
is
a
tio
n
p
r
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b
le
m
s
(
DOP
s
)
h
av
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b
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n
o
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f
th
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m
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r
in
ter
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ea
l
w
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ld
o
p
ti
m
is
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s
ce
n
ar
io
s
[
1
]
.
T
h
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p
o
s
s
ib
ilit
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o
f
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p
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b
le
m
ch
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n
d
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o
f
an
o
p
ti
m
a
l
s
o
lu
tio
n
.
T
h
er
ef
o
r
e,
th
er
e
is
a
n
ee
d
to
d
esig
n
an
ef
f
ec
ti
v
e
E
v
o
lu
tio
n
ar
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Alg
o
r
it
h
m
(
E
A)
to
h
an
d
le
DOP
s
.
I
n
d
ee
d
,
th
e
n
atu
r
e
o
f
E
A
in
g
en
er
atin
g
d
i
f
f
er
en
t
s
o
lu
tio
n
s
i
n
e
v
er
y
s
i
n
g
le
ev
o
l
u
tio
n
h
e
lp
s
E
A
to
ad
ap
t
w
it
h
ch
an
g
es
o
f
DOP
s
.
B
y
e
m
p
lo
y
in
g
an
E
A
s
u
c
h
a
s
a
g
e
n
etic
alg
o
r
ith
m
(
G
A
)
,
th
e
DOP
s
w
i
ll
b
e
s
o
l
v
ed
[
2
,
3
]
.
E
x
is
ti
n
g
s
t
u
d
ies
s
h
o
w
th
at
a
d
ap
tiv
e
alg
o
r
it
h
m
s
t
h
at
u
s
e
d
iv
er
s
it
y
m
ain
tain
i
n
g
m
et
h
o
d
s
h
a
v
e
b
ee
n
w
id
el
y
d
ev
elo
p
ed
to
ad
d
r
ess
DOP
s
[
4
]
.
T
h
is
p
ap
er
aim
s
to
d
ev
elo
p
a
cr
o
s
s
o
v
er
o
p
er
ato
r
f
o
r
GA
in
o
r
d
er
to
ef
f
ec
tiv
el
y
ad
d
r
ess
DOP
s
.
E
s
s
en
tiall
y
,
t
h
e
d
ep
en
d
e
n
c
y
o
f
G
A
o
n
g
e
n
etic
o
p
er
ato
r
s
g
e
n
er
all
y
an
d
cr
o
s
s
o
v
er
o
p
er
ato
r
s
p
r
ac
ticall
y
ef
f
ec
t
its
p
er
f
o
r
m
an
ce
[
4
]
.
Yet,
th
e
ch
an
ce
o
f
r
ep
r
o
d
u
ctio
n
a
n
e
w
o
f
f
s
p
r
in
g
w
ill
b
e
lo
s
t
in
ca
s
e
o
f
h
av
i
n
g
id
e
n
tic
al
ch
r
o
m
o
s
o
m
e
s
(
p
ar
en
t
s
)
t
h
at
h
av
e
b
ee
n
s
elec
ted
f
o
r
t
h
e
cr
o
s
s
o
v
er
o
p
er
a
to
r
d
u
r
in
g
t
h
e
ev
o
l
u
tio
n
s
ta
g
e.
Hen
ce
,
th
e
d
iv
er
s
i
f
y
i
n
g
t
h
e
s
el
ec
tin
g
cu
t
-
p
o
in
t
r
ath
er
th
a
n
u
s
in
g
f
i
x
ed
o
n
es
co
u
ld
o
v
er
co
m
e
th
is
id
en
tica
l
ca
s
e
o
f
f
ail
u
r
e.
T
h
is
p
ap
er
in
tr
o
d
u
ce
s
a
h
y
b
r
id
ad
ap
ti
v
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cr
o
s
s
o
v
er
o
p
er
ato
r
b
ased
o
n
p
r
e
-
ev
al
u
ated
c
h
r
o
m
o
s
o
m
e
s
b
ef
o
r
e
p
ass
in
g
i
n
d
iv
id
u
als
to
t
h
e
n
e
x
t
s
tag
e.
T
h
e
id
ea
o
f
t
h
is
w
o
r
k
i
s
to
:
r
ed
u
ce
co
m
p
u
tatio
n
ti
m
e,
r
ed
u
ce
s
t
h
e
r
an
d
o
m
ch
a
n
ce
o
f
co
m
b
i
n
e
’
s
g
en
s
o
f
t
w
o
ch
r
o
m
o
s
o
m
e
s
an
d
en
h
a
n
ce
th
e
r
es
u
lt
s
to
w
ar
d
b
etter
s
o
lu
tio
n
.
T
o
ac
co
m
p
lis
h
th
i
s
ai
m
an
d
t
o
r
esp
o
n
d
t
o
a
r
ec
en
t
ca
ll
f
o
r
r
esear
ch
to
ad
d
r
ess
DOP
s
,
w
e
h
a
v
e
to
r
ec
all
th
e
w
ell
-
k
n
o
w
n
d
y
n
a
m
i
c
o
p
ti
m
is
at
io
n
f
u
n
ct
io
n
s
s
u
ch
as,
On
e
-
m
a
n
,
P
latea
u
,
R
o
y
al
R
o
ad
an
d
Dec
ep
tiv
e,
in
o
r
d
er
to
ex
a
m
i
n
e
t
h
e
e
f
f
ec
t
iv
e
n
e
s
s
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
.
E
x
p
er
im
e
n
tal
r
es
u
lt
s
s
h
o
w
t
h
at
t
h
e
p
r
o
p
o
s
e
d
alg
o
r
ith
m
i
s
ab
le
to
ac
h
iev
e
c
o
m
p
eti
tiv
e
r
es
u
lt
s
w
h
en
co
m
p
ar
ed
to
o
th
er
av
ailab
le
m
eth
o
d
s
.
T
h
e
r
est
o
f
th
is
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
w
s
.
I
n
s
ec
tio
n
2
,
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
in
th
i
s
s
t
u
d
y
i
s
g
i
v
e
n
.
Nex
t
s
ec
tio
n
d
ea
l
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
IJ
-
AI
Vo
l.
6
,
No
.
3
,
Sep
tem
b
er
201
7
:
1
39
–
14
2
140
w
it
h
th
e
e
x
p
er
i
m
e
n
tal
r
e
s
u
l
ts
an
d
r
ele
v
a
n
t
d
is
c
u
s
s
io
n
.
Fi
n
all
y
,
s
ec
tio
n
4
co
n
c
lu
d
es
t
h
e
r
esu
l
ts
w
it
h
s
o
m
e
r
ec
o
m
m
e
n
d
atio
n
s
o
n
th
e
f
u
tu
r
e
w
o
r
k
.
2.
P
RO
P
O
SE
D
M
E
T
H
O
D
I
n
th
i
s
p
ap
er
,
w
e
p
r
o
p
o
s
e
a
h
y
b
r
id
cr
o
s
s
o
v
er
o
p
er
ato
r
f
o
r
GA
to
ef
f
ec
ti
v
el
y
s
o
l
v
e
DOP
s
.
T
h
e
d
e
p
en
d
en
c
y
o
f
G
A
o
n
g
en
et
ic
o
p
er
ato
r
s
g
en
er
all
y
an
d
cr
o
s
s
o
v
er
o
p
er
ato
r
s
p
r
ac
ti
ca
ll
y
ef
f
ec
t
o
n
its
p
er
f
o
r
m
a
n
ce
[
1
]
.
Ho
w
e
v
er
,
th
e
ch
an
ce
o
f
r
ep
r
o
d
u
ctio
n
a
n
e
w
o
f
f
s
p
r
in
g
w
ill
b
e
lo
s
t
i
n
ca
s
e
o
f
h
a
v
in
g
id
en
tical
ch
r
o
m
o
s
o
m
e
s
(
p
ar
en
t
s
)
th
at
h
av
e
b
ee
n
s
elec
ted
f
o
r
cr
o
s
s
o
v
er
o
p
e
r
ato
r
d
u
r
in
g
t
h
e
ev
o
lu
ti
o
n
s
tag
e.
He
n
ce
,
th
e
d
iv
er
s
i
f
y
i
n
g
t
h
e
cu
t
-
p
o
in
t
s
ele
ctio
n
in
s
tead
o
f
u
s
i
n
g
f
i
x
ed
o
n
es c
o
u
ld
o
v
er
co
m
e
t
h
is
id
en
tic
al
ca
s
e
o
f
f
ail
u
r
e
as
w
ell
as
a
v
o
id
in
g
th
e
r
a
n
d
o
m
c
o
m
b
i
n
atio
n
o
f
t
h
e
g
en
s
o
f
t
h
e
s
elec
ted
t
w
o
c
h
r
o
m
o
s
o
m
es.
T
h
is
p
ap
er
p
r
esen
ts
a
h
y
b
r
id
ad
ap
tiv
e
cr
o
s
s
o
v
er
o
p
er
ato
r
b
ased
o
n
p
r
e
-
ev
alu
a
ted
ch
r
o
m
o
s
o
m
e
s
b
ef
o
r
e
p
ass
in
g
in
d
iv
id
u
als
to
th
e
n
ex
t
s
ta
g
e.
B
asicall
y
,
it
u
s
e
s
t
w
o
t
y
p
e
s
o
f
cr
o
s
s
o
v
er
as
w
i
ll
b
e
ex
p
lain
ed
b
elo
w
:
2
.
1
.
H
euristic
cr
o
s
s
o
v
er
o
pera
t
o
r
(
H
CO
)
HC
O
s
h
i
f
t
s
m
ar
g
i
n
all
y
a
c
h
i
ld
f
r
o
m
w
o
r
s
t
f
it
n
es
s
v
alu
e
to
th
e
b
e
s
t
f
it
n
es
s
v
a
lu
e
o
f
p
ar
en
t
[
2
]
.
T
h
is
s
h
i
f
ti
n
g
i
s
b
ased
o
n
R
atio
n
v
alu
e
w
h
ic
h
is
a
r
an
d
o
m
v
alu
e
b
et
w
ee
n
0
’
s
an
d
1
’
s
.
I
n
d
ee
d
,
th
e
v
alu
e
o
f
R
atio
n
co
u
ld
b
e
s
etti
n
g
i
n
b
y
d
ef
au
lt.
I
f
b
o
th
P
1
an
d
P2
ar
e
p
ar
en
ts
an
d
P
1
h
as
a
b
etter
f
itn
es
s
v
al
u
e
th
a
n
P
2
,
th
en
1
.
2
w
ill
b
e
s
etti
n
g
as
a
R
atio
n
v
al
u
e
[
1
]
.
T
h
e
n
e
w
o
f
f
s
p
r
in
g
w
ill
b
e
g
e
n
er
ated
b
as
ed
o
n
th
e
f
o
llo
w
in
g
eq
u
atio
n
:
Of
f
s
p
r
in
g
’
s
=B
est P
ar
en
t +
β
∗
(
B
est P
ar
en
t
–
W
o
r
s
t P
a
r
e
n
t)
.
2
.
2
.
Arit
h
m
et
ic
Cro
s
s
o
v
er
(
ACO
)
AC
O
r
et
u
r
n
s
a
n
o
f
f
s
p
r
in
g
t
h
a
t
ar
e
h
o
ld
m
ea
n
f
it
n
es
s
o
f
t
wo
in
d
iv
id
u
als
[
1
]
.
Alp
h
a
i
s
a
tin
y
v
al
u
e
b
et
w
ee
n
[
0
,
1
]
g
en
er
ated
r
an
d
o
m
l
y
.
I
f
C
h
r
o
m
o
s
o
m
e1
an
d
C
h
r
o
m
o
s
o
m
e2
ar
e
p
ar
en
ts
,
an
d
C
h
r
o
m
o
s
o
m
e1
h
a
s
th
e
b
est f
itn
e
s
s
,
t
h
e
o
f
f
s
p
r
in
g
w
it
h
b
e
g
e
n
er
ate
as
f
o
llo
w
s
:
Offs
p
r
in
g
=α
*
B
est P
a
r
en
t +
(
1
-
α
)
*
W
o
r
s
t P
a
r
en
t.
2
.
3
.
H
y
brid Cr
o
s
s
o
v
er
O
pera
t
o
r
(
H
YCO
)
Un
d
o
u
b
ted
l
y
,
t
h
e
e
f
f
ec
t
iv
e
n
es
s
o
f
cr
o
s
s
o
v
er
i
s
d
ep
en
d
s
o
n
t
h
e
r
esu
lts
o
f
s
elec
ted
p
ar
en
t
[
1
]
.
Du
e
to
th
e
n
at
u
r
e
o
f
ev
o
l
u
tio
n
t
h
e
n
ec
ess
it
y
to
p
r
o
d
u
ce
b
etter
s
o
lu
tio
n
i
s
r
ep
r
esen
ted
in
th
i
s
s
t
ag
e.
Ou
r
p
r
o
p
o
s
e
d
o
p
er
ato
r
in
v
esti
g
ates
t
h
e
ad
v
an
tag
e
s
o
f
H
C
O
w
it
h
AC
O
cr
o
s
s
o
v
er
.
B
o
th
o
f
t
h
e
m
e
x
a
m
i
n
e
t
h
e
f
it
n
es
s
o
f
ch
r
o
m
o
s
o
m
e
b
ef
o
r
e
co
m
b
i
n
i
n
g
t
h
e
m
.
T
h
e
r
an
d
o
m
s
elec
tio
n
to
cu
t
-
p
o
in
t
in
v
o
k
e
s
at
f
ir
s
t
s
tep
.
Ou
r
id
ea
i
s
to
en
h
a
n
ce
t
h
e
m
at
in
g
p
r
o
ce
s
s
.
T
h
e
co
m
p
lete
p
r
o
ce
d
u
r
e
is
p
r
esen
ted
in
Fi
g
u
r
e
1
.
Fig
u
r
e
1
.
P
s
eu
d
o
-
C
o
d
e
f
o
r
a
Mu
lti
-
C
r
o
s
s
o
v
er
-
B
ased
HC
&
AC
H
YCO
pa
ra
m
et
rize
:
1.
R
atio
n
i
s
f
i
x
ed
v
al
u
e:
=1
.
2
.
2.
A
lp
h
a
r
an
d
o
m
v
alu
e
b
et
w
ee
n
[
0
,
1
]
.
3.
CP
is
a
cr
o
s
s
o
v
er
p
o
s
s
ib
ilit
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
AI
I
SS
N:
2252
-
8938
Mu
lti
-
Op
era
to
r
Gen
etic
A
lg
o
r
ith
m
fo
r
Dyn
a
mic
Op
timiz
a
tio
n
P
r
o
b
lems
(
A
l
-
kh
a
fa
ji A
men
)
141
As
s
h
o
w
n
i
n
Fi
g
u
r
e
1
,
th
e
h
y
b
r
id
cr
o
s
s
o
v
er
b
ased
o
n
co
m
b
in
in
g
t
h
e
f
ea
t
u
r
es
o
f
t
w
o
c
h
r
o
m
o
s
o
m
e
s
b
y
:
1.
I
f
th
e
p
ar
en
t
X
i
s
m
o
r
e
w
o
r
t
h
th
a
n
p
ar
en
t
Y
t
h
e
n
t
h
e
o
f
f
s
p
r
in
g
w
ill
b
e
i
n
f
lu
e
n
ce
d
b
y
t
h
e
b
etter
o
n
ce
b
y
in
cl
u
d
in
g
its
f
ea
t
u
r
es i
n
s
id
e
t
h
eir
g
en
s
.
2.
I
f
b
o
th
o
f
ch
r
o
m
o
s
o
m
e
s
h
a
v
e
s
i
m
ilar
q
u
alit
y
,
th
e
n
th
e
n
e
w
o
n
e
w
il
l
h
as
a
co
m
b
in
atio
n
o
f
t
w
o
ch
r
o
m
o
s
o
m
e
s
b
y
e
m
p
lo
y
ar
i
t
h
m
e
tic
cr
o
s
s
o
v
er
w
h
ic
h
g
en
e
r
ates
a
h
y
b
r
id
s
o
lu
tio
n
s
th
at
ef
f
ec
ted
b
y
b
o
t
h
p
ar
en
ts
.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
I
n
t
h
is
s
ec
tio
n
,
t
h
e
p
er
f
o
r
m
an
ce
o
f
o
u
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
MCO
i
s
ev
a
lu
ated
u
s
in
g
f
o
u
r
b
in
ar
y
te
s
t
f
u
n
ctio
n
s
,
w
h
ich
ar
e
On
eM
a
x
,
P
latea
u
,
R
o
y
al
R
o
ad
an
d
Dec
ep
tiv
e
[
4
]
.
T
h
ese
f
u
n
ct
io
n
s
o
r
ig
i
n
all
y
ar
e
s
tatio
n
ar
y
a
n
d
h
a
v
e
b
ee
n
w
id
el
y
u
s
ed
b
y
m
a
n
y
r
esear
ch
er
s
to
ev
alu
ate
th
e
p
er
f
o
r
m
an
ce
o
f
th
eir
alg
o
r
it
h
m
s
.
I
n
th
is
p
ap
er
,
w
e
u
s
ed
a
d
y
n
a
m
ic
g
e
n
er
ato
r
p
r
o
p
o
s
ed
b
y
[
5
,
6
]
to
g
en
er
ate
d
y
n
a
m
ic
en
v
ir
o
n
m
e
n
t
s
.
T
h
e
p
ar
am
eter
v
alu
e
s
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
ar
e
p
r
esen
ted
in
T
ab
le
1
.
T
ab
le
1
.
P
ar
am
eter
s
s
e
tti
n
g
s
P
a
r
a
me
t
e
r
V
a
l
u
e
P
o
p
u
l
a
t
i
o
n
S
i
z
e
S
o
l
u
t
i
o
n
s
i
z
e
N
u
mb
e
r
o
f
i
t
e
r
a
t
i
o
n
s
T
P
50
1
0
0
1
0
0
1
0
0
0
.
9
T
o
ass
u
r
e
f
air
co
m
p
ar
is
o
n
w
i
th
t
h
e
s
tate
-
of
-
th
e
-
ar
t
ap
p
r
o
ac
h
es,
t
h
e
p
ar
a
m
eter
s
T
(
w
h
ic
h
r
ep
r
esen
ts
th
e
p
er
io
d
icall
y
o
f
ch
a
n
g
e
s
)
an
d
P
(
w
h
ic
h
r
ep
r
esen
ts
t
h
e
a
m
o
u
n
t
o
f
ch
a
n
g
e)
ar
e
s
et
b
ased
o
n
th
e
w
o
r
k
r
ep
o
r
ted
in
[
4
]
.
T
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
is
co
m
p
ar
ed
ag
ain
s
t
t
h
e
f
o
llo
w
i
n
g
al
g
o
r
ith
m
s
t
h
at
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
in
th
e
s
cien
t
if
ic
l
iter
atu
r
e:
T
ab
le
2
.
R
esu
lts
C
o
m
p
ar
is
o
n
F
u
n
c
t
i
o
n
n
a
me
M
O
C
P
o
p
-
HC
M
I
G
A
M
EG
A
A
H
M
A
M
R
I
G
A
O
n
e
M
a
x
9
9
.
4
8
6
.
3
5
9
4
.
0
7
9
.
3
9
5
.
8
9
8
0
.
8
P
l
e
a
t
e
a
u
9
9
.
5
7
4
.
2
1
-
-
6
2
.
8
8
-
R
o
y
a
l
R
o
a
d
9
9
.
7
5
1
.
1
1
-
-
5
2
.
5
2
-
D
e
c
e
p
t
i
v
e
9
7
.
9
7
2
.
5
6
7
1
.
1
8
3
.
1
8
5
.
7
5
6
8
.
6
N
o
t
e
:
v
a
l
u
e
s i
n
b
o
l
d
f
o
n
t
i
n
d
i
c
a
t
e
t
h
e
b
e
st
r
e
su
l
t
s.
“
-
“
:
n
o
r
e
su
l
t
s re
p
o
r
t
e
d
.
P
o
p
-
HC
: A
n
E
v
o
l
u
tio
n
ar
y
Hil
l Cl
i
m
b
in
g
A
l
g
o
r
ith
m
f
o
r
D
y
n
a
m
ic
Op
ti
m
is
a
tio
n
P
r
o
b
lem
s
[
7
]
.
MI
GA
: G
e
n
etic
al
g
o
r
ith
m
w
i
t
h
m
e
m
o
r
y
b
ased
i
m
m
i
g
r
a
n
ts
[
6
]
.
ME
GA:
m
e
m
o
r
y
-
e
n
h
a
n
ce
d
G
en
etic
al
g
o
r
ith
m
[
8
]
.
A
HM
A:
Me
m
etic
al
g
o
r
ith
m
with
t
h
e
A
HC
o
p
er
ato
r
[
1
]
.
MRIG
A
: G
e
n
etic
al
g
o
r
ith
m
with
m
e
m
o
r
y
a
n
d
r
an
d
o
m
i
m
m
i
g
r
an
t
s
s
c
h
e
m
e
s
[
6
]
T
ab
le
2
co
n
tain
s
th
e
r
es
u
lt
s
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
a
n
d
s
t
ate
-
of
-
t
h
e
ar
t a
lg
o
r
it
h
m
s
.
A
clo
s
e
s
cr
u
ti
n
y
o
f
T
ab
le
2
r
ev
ea
ls
th
at,
o
u
t
o
f
all
f
o
u
r
in
s
ta
n
ce
s
,
t
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
o
u
tp
er
f
o
r
m
s
t
h
e
o
th
er
alg
o
r
it
h
m
s
o
v
er
th
r
ee
in
s
tan
ce
s
.
No
te
th
at,
th
e
m
et
h
o
d
s
in
co
m
p
ar
is
o
n
h
er
e
d
id
n
o
t
atte
m
p
t
o
n
all
test
f
u
n
c
tio
n
s
.
MO
C
is
ab
le
to
p
r
o
d
u
ce
b
etter
r
esu
lts
th
a
n
all
alg
o
r
it
h
m
s
in
3
in
s
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