I
AE
S In
t
er
na
t
io
na
l J
o
urna
l o
f
Art
if
icia
l In
t
ellig
ence
(
I
J
-
AI
)
Vo
l.
13
,
No
.
4
,
Dec
em
b
er
2
0
2
4
,
p
p
.
4
2
1
7
~
4
2
2
8
I
SS
N:
2
2
5
2
-
8
9
3
8
,
DOI
: 1
0
.
1
1
5
9
1
/ijai.v
13
.i
4
.
p
p
4
2
1
7
-
4
2
2
8
4217
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
i
.
ia
esco
r
e.
co
m
G
uided
imitatio
n
o
ptimizer:
a meta
heuristic
com
bini
ng
guided
sea
rch and imi
tat
io
n sea
rch
P
urba
Da
ru
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us
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M
et
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T
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B
a
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g
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I
n
d
o
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si
a
Art
icle
I
nfo
AB
S
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RAC
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r
ticle
his
to
r
y:
R
ec
eiv
ed
Dec
3
1
,
2
0
2
3
R
ev
is
ed
Feb
1
3
,
2
0
2
4
Acc
ep
ted
Ma
r
2
1
,
2
0
2
4
Th
is
p
a
p
e
r
p
r
o
p
o
se
s
a
n
o
v
e
l
m
e
tap
h
o
r
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fre
e
m
e
tah
e
u
risti
c
,
n
a
m
e
ly
t
h
e
g
u
id
e
d
imitatio
n
o
p
ti
m
ize
r
(G
IO).
Th
is
m
e
tah
e
u
risti
c
c
o
m
b
in
e
s
th
e
g
u
i
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d
s
e
a
rc
h
a
n
d
imitatio
n
-
b
a
se
d
se
a
rc
h
.
Th
e
re
a
re
fiv
e
g
u
id
e
d
se
a
rc
h
e
s
a
n
d
th
re
e
imitatio
n
-
b
a
se
d
se
a
rc
h
e
s.
M
e
a
n
wh
il
e
,
th
e
re
a
re
th
re
e
re
fe
re
n
c
e
s
u
se
d
in
t
h
i
s
m
e
tah
e
u
risti
c
:
g
lo
b
a
l
fi
n
e
st,
a
ra
n
d
o
m
l
y
p
ick
e
d
so
lu
ti
o
n
a
m
o
n
g
t
h
e
sw
a
rm
,
a
n
d
a
ra
n
d
o
m
ize
d
s
o
lu
t
io
n
wit
h
i
n
th
e
se
a
rc
h
sp
a
c
e
.
G
IO
is
t
h
e
n
e
v
a
lu
a
ted
b
y
u
sin
g
2
3
c
las
sic
fu
n
c
ti
o
n
s
th
a
t
c
o
n
sist
o
f
se
v
e
n
h
i
g
h
d
ime
n
si
o
n
u
n
imo
d
a
l
fu
n
c
ti
o
n
s
(HD
UF),
six
h
i
g
h
d
ime
n
sio
n
m
u
lt
imo
d
a
l
f
u
n
c
ti
o
n
s
(HD
M
F
),
a
n
d
ten
fix
e
d
d
ime
n
sio
n
m
u
lt
im
o
d
a
l
f
u
n
c
ti
o
n
s
(F
D
M
F
).
Th
r
o
u
g
h
sim
u
l
a
ti
o
n
,
G
IO
is
su
p
e
ri
o
r
t
o
g
o
ld
e
n
se
a
rc
h
o
p
ti
m
ize
r
(G
S
O),
g
re
y
wo
lf
o
p
ti
m
iz
e
r
(G
WO),
p
u
z
z
le
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
(
P
OA
),
a
n
d
c
o
a
ti
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
(COA
)
in
h
a
n
d
li
n
g
m
o
st
o
f
th
e
se
fu
n
c
ti
o
n
s.
G
IO
is
th
e
first
fin
e
st
i
n
tac
k
l
in
g
se
v
e
n
te
e
n
fu
n
c
ti
o
n
s
a
n
d
se
c
o
n
d
fi
n
e
st
in
tac
k
li
n
g
si
x
f
u
n
c
ti
o
n
s.
Ti
g
h
t
c
o
m
p
e
ti
ti
o
n
o
c
c
u
rs
b
e
twe
e
n
G
IO
a
n
d
COA
d
u
e
to
t
h
e
p
e
rfo
rm
a
n
c
e
o
f
COA
wh
ich
b
e
c
o
m
e
s th
e
se
c
o
n
d
f
in
e
st
in
h
a
n
d
li
n
g
m
o
st
o
f
th
e
se
fu
n
c
ti
o
n
s.
K
ey
w
o
r
d
s
:
E
x
p
lo
itatio
n
E
x
p
lo
r
atio
n
Me
tah
eu
r
is
tic
Op
tim
izatio
n
Swar
m
in
tellig
en
ce
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Pu
r
b
a
Dar
u
Ku
s
u
m
a
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
E
n
g
i
n
ee
r
in
g
,
T
elk
o
m
U
n
iv
er
s
ity
B
u
ah
b
atu
Stre
et,
B
an
d
u
n
g
,
I
n
d
o
n
esia
E
m
ail: p
u
r
b
o
d
ar
u
@
telk
o
m
u
n
i
v
er
s
ity
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
Op
tim
izatio
n
wo
r
k
is
a
s
u
b
ject
in
ap
p
lied
m
at
h
em
atics
th
at
h
a
s
b
ee
n
e
x
ten
s
iv
ely
u
s
ed
in
v
ar
i
o
u
s
ar
ea
s
,
in
clu
d
in
g
e
n
g
in
ee
r
i
n
g
,
in
d
u
s
t
r
y
,
an
d
f
in
an
ce
.
Fo
r
ex
a
m
p
l
e,
p
o
wer
f
l
o
w
o
p
tim
izatio
n
i
s
n
ec
ess
ar
y
in
th
e
o
p
er
atio
n
o
f
th
e
elec
tr
ical
p
o
w
er
s
y
s
tem
[
1
]
.
Op
tim
izatio
n
p
l
ay
s
im
p
o
r
tan
t
r
o
le
in
o
t
h
er
en
e
r
g
y
r
elate
d
s
y
s
tem
,
s
u
ch
as
elec
tr
icity
d
is
tr
ib
u
te
d
s
y
s
tem
[
2
]
a
n
d
p
o
wer
s
y
s
t
em
s
tab
ilizer
[
3
]
.
I
n
t
h
e
m
a
n
u
f
ac
tu
r
i
n
g
s
y
s
tem
,
o
p
tim
izatio
n
p
lay
s
a
s
ig
n
if
ican
t
r
o
le
in
s
ch
ed
u
lin
g
th
e
ar
r
iv
in
g
jo
b
in
th
e
d
is
tr
ib
u
ted
f
lo
w
-
s
h
o
p
s
y
s
tem
[
4
]
o
r
ass
em
b
ly
jo
b
-
s
h
o
p
s
y
s
tem
[
5
]
.
I
n
s
u
p
p
ly
c
h
ain
m
a
n
ag
em
e
n
t,
v
eh
icle
r
o
u
tin
g
p
r
o
b
lem
s
b
ec
o
m
e
a
co
m
m
o
n
is
s
u
e
to
o
p
tim
ize,
f
o
r
e
x
am
p
le
in
t
h
e
co
n
tex
t
o
f
ca
p
ac
itated
v
eh
icl
e
r
o
u
tin
g
p
r
o
b
lem
s
wh
er
e
t
h
er
e
is
a
lim
itatio
n
o
n
th
e
f
leet
ca
p
ac
ity
[
6
]
.
I
n
r
ec
e
n
t
y
ea
r
s
,
m
an
y
s
tu
d
ies
o
n
th
e
v
eh
i
cle
r
o
u
tin
g
p
r
o
b
lem
h
av
e
u
s
ed
th
e
elec
tr
ic
v
eh
icle
as
th
e
u
s
e
ca
s
e,
f
o
r
ex
am
p
le
i
n
its
r
elatio
n
s
h
ip
with
ch
ar
g
in
g
an
d
d
is
ch
ar
g
in
g
f
u
n
ctio
n
s
[
7
]
.
I
n
th
e
f
in
an
cial
s
ec
to
r
,
p
o
r
tf
o
lio
o
p
tim
izatio
n
is
a
cr
u
cial
is
s
u
e
in
ar
r
an
g
i
n
g
th
e
ass
ets
h
eld
b
y
in
d
i
v
id
u
al
s
o
r
in
s
titu
tio
n
s
to
m
ax
im
ize
th
e
in
v
estme
n
t
r
etu
r
n
an
d
m
in
im
ize
th
e
in
v
estme
n
t
r
is
k
[
8
]
.
Op
tim
izatio
n
d
ea
ls
with
p
r
o
b
lem
s
wit
h
m
u
ltip
le
p
o
s
s
ib
le
s
o
lu
tio
n
s
.
I
n
f
in
d
i
n
g
th
e
f
i
n
est s
o
lu
tio
n
,
o
p
tim
izatio
n
f
ac
es th
r
ee
k
ey
is
s
u
es: d
ec
is
io
n
v
ar
iab
les,
co
n
s
tr
ain
ts
,
an
d
o
b
jectiv
e
f
u
n
ctio
n
.
I
n
s
o
m
e
wo
r
k
s
,
co
n
s
tr
ain
ts
ar
e
ca
lled
h
ar
d
c
o
n
s
tr
ain
ts
wh
ile
o
b
jecti
v
es
ar
e
ca
lled
s
o
f
t
co
n
s
tr
ain
ts
.
B
o
th
co
n
s
tr
ain
ts
an
d
o
b
jectiv
es
ar
e
co
n
s
tr
u
cte
d
f
r
o
m
d
ec
is
io
n
v
a
r
iab
les.
C
o
n
s
tr
ain
ts
o
r
h
ar
d
co
n
s
tr
ain
ts
ar
e
d
esig
n
ed
to
lim
it
th
e
p
o
s
s
ib
le
s
o
lu
tio
n
s
an
d
b
ec
o
m
e
th
e
b
o
u
n
d
ar
ies
o
f
th
e
s
o
lu
tio
n
s
p
ac
e.
Ob
jectiv
es o
r
s
o
f
t c
o
n
s
tr
ain
ts
ar
e
s
o
m
e
en
titi
es th
at
b
ec
o
m
e
th
e
f
o
cu
s
o
f
o
p
tim
izatio
n
.
I
t m
ay
b
e
m
in
im
izatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
13
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
4
2
1
7
-
4
2
2
8
4218
o
r
m
ax
im
izatio
n
.
T
h
e
ex
am
p
le
s
o
f
m
in
im
izatio
n
o
b
jectiv
es
ar
e
m
in
im
izin
g
to
tal
tar
d
in
ess
[
4
]
,
to
tal
co
m
p
letio
n
tim
e
[
5
]
,
to
tal
in
v
en
t
o
r
y
tim
e
[
5
]
,
an
d
waitin
g
tim
e
[
9
]
.
On
t
h
e
o
th
er
h
a
n
d
,
m
a
x
im
izatio
n
-
b
ased
o
b
jectiv
es
ar
e
o
f
ten
r
elate
d
t
o
r
ev
e
n
u
e
[
1
0
]
,
p
r
o
f
it
[
1
1
]
,
an
d
s
er
v
ice
lev
el
[
6
]
.
I
n
g
en
er
al,
o
p
tim
izatio
n
ca
n
b
e
s
o
lv
ed
u
s
in
g
two
ap
p
r
o
ac
h
es:
d
eter
m
in
is
tic
an
d
s
to
ch
asti
c.
Dete
r
m
in
is
tic
o
r
ex
ac
t
m
eth
o
d
is
p
o
wer
f
u
l
in
g
u
ar
an
teein
g
th
e
g
l
o
b
al
o
p
tim
al
s
o
lu
tio
n
.
B
u
t
d
eter
m
in
is
tic
m
eth
o
d
s
h
av
e
d
is
ad
v
an
tag
es
in
tack
lin
g
co
m
p
lex
o
r
co
m
p
licate
d
p
r
o
b
lem
s
with
h
ig
h
d
im
en
s
io
n
s
o
r
h
u
g
e
n
u
m
b
er
o
f
d
ec
is
io
n
v
ar
ia
b
les.
T
h
e
d
eter
m
i
n
is
tic
m
eth
o
d
n
ee
d
s
ex
ce
s
s
iv
e
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
,
s
o
it
is
d
if
f
icu
lt
to
im
p
lem
en
t
in
h
an
d
l
in
g
v
ar
io
u
s
p
r
ac
tical
o
p
tim
izat
io
n
p
r
o
b
lem
s
[
1
2
]
.
Me
an
w
h
ile,
s
to
ch
asti
c
m
eth
o
d
i
s
m
o
r
e
f
lex
ib
le
an
d
f
ea
s
ib
le
t
o
b
e
im
p
lem
en
ted
f
o
r
h
a
n
d
lin
g
v
ar
io
u
s
an
d
co
m
p
lex
p
r
o
b
lem
s
[
1
2
]
.
I
ts
r
an
d
o
m
s
ea
r
ch
s
tr
ateg
y
ca
n
r
ed
u
ce
th
e
co
m
p
u
tatio
n
al
r
eso
u
r
ce
,
b
u
t
with
th
e
co
n
s
eq
u
en
ce
t
h
at
th
e
r
ea
l
o
p
tim
al
is
n
o
t
en
s
u
r
ed
to
b
e
f
o
u
n
d
[
1
2
]
.
Me
tah
eu
r
is
tics
is
a
p
o
p
u
lar
s
t
o
ch
asti
c
b
ased
o
p
tim
izatio
n
m
eth
o
d
.
As
a
s
to
ch
asti
c
to
o
l,
it
d
o
es
n
o
t
s
ea
r
ch
f
o
r
all
p
o
s
s
ib
le
o
r
a
v
ailab
le
s
o
lu
tio
n
s
.
I
n
g
en
er
al,
it
s
tar
ts
with
a
f
u
ll
r
an
d
o
m
s
ea
r
ch
in
s
id
e
th
e
s
ea
r
ch
s
p
ac
e.
T
h
en
,
th
e
cu
r
r
e
n
t
s
o
lu
tio
n
is
im
p
r
o
v
ed
as
th
e
iter
atio
n
g
o
es.
B
ec
au
s
e
o
f
its
f
lex
ib
ilit
y
an
d
f
ea
s
ib
ilit
y
[
1
3
]
,
m
etah
eu
r
is
tic
h
as b
ee
n
wid
ely
u
s
ed
in
v
ar
i
o
u
s
o
p
tim
izatio
n
p
r
o
jects.
T
h
e
p
o
p
u
lar
ity
o
f
m
etah
e
u
r
is
tic
is
f
o
llo
wed
b
y
t
h
e
m
ass
iv
e
d
ev
elo
p
m
en
t
o
f
v
ar
io
u
s
m
eta
h
eu
r
is
tics
.
T
h
is
m
ass
iv
e
d
ev
elo
p
m
en
t c
o
m
es f
r
o
m
s
ev
er
al
r
ea
s
o
n
s
.
First,
th
er
e
ar
e
v
ar
io
u
s
s
to
ch
asti
c
m
eth
o
d
s
th
at
ca
n
b
e
ex
p
lo
r
ed
,
m
o
d
if
ied
,
an
d
im
p
le
m
en
ted
to
d
ev
el
o
p
a
n
ew
m
etah
eu
r
is
tic.
Seco
n
d
,
a
n
ew
m
eta
h
eu
r
is
tic
ca
n
also
b
e
b
u
ilt
b
y
m
o
d
if
y
in
g
t
h
e
ex
is
tin
g
m
etah
eu
r
is
tic
o
r
co
m
b
in
in
g
s
o
m
e
ex
is
tin
g
m
etah
eu
r
is
tics
,
s
u
ch
as
h
y
b
r
id
p
elica
n
Ko
m
o
d
o
alg
o
r
ith
m
(
HPKA)
[
1
4
]
o
r
g
u
id
ed
p
elica
n
alg
o
r
ith
m
(
GPA)
[
1
5
]
.
T
h
ir
d
,
as
s
tated
in
n
o
-
f
r
ee
lu
n
ch
(
NFL)
th
eo
r
y
,
t
h
er
e
is
n
o
o
n
e
to
o
l
th
at
is
m
o
s
t
s
u
itab
le
to
s
o
lv
e
all
p
r
o
b
lem
s
[
1
2
]
.
An
y
o
p
tim
izatio
n
m
eth
o
d
m
a
y
b
e
s
u
p
er
io
r
i
n
h
a
n
d
lin
g
s
o
m
e
p
r
o
b
lem
s
b
u
t m
e
d
io
cr
e
o
r
in
f
er
i
o
r
in
h
an
d
lin
g
o
th
er
p
r
o
b
lem
s
[
1
2
]
.
I
n
r
ec
en
t
d
ec
ad
es,
n
atu
r
e
b
ec
o
m
es
th
e
m
ain
s
o
u
r
ce
o
f
in
s
p
ir
atio
n
in
p
r
o
p
o
s
in
g
a
n
ew
m
et
ah
eu
r
is
tic.
Ma
n
y
m
etah
e
u
r
is
tics
ar
e
in
s
p
ir
ed
b
y
th
e
a
n
im
al
b
e
h
av
io
r
d
u
r
in
g
m
atin
g
o
r
s
ea
r
ch
in
g
f
o
r
f
o
o
d
,
s
u
ch
as:
g
r
e
y
wo
lf
o
p
tim
izer
(
GW
O)
[
1
6
]
,
Ko
m
o
d
o
m
lip
ir
al
g
o
r
ith
m
(
K
MA
)
[
1
7
]
,
p
u
zz
le
o
p
tim
izatio
n
alg
o
r
ith
m
(
POA)
[
1
8
]
,
co
ati
o
p
tim
izatio
n
alg
o
r
ith
m
(
C
OA)
[
1
9
]
,
n
o
r
th
er
n
g
o
s
h
awk
o
p
tim
izer
(
NGO)
[
2
0
]
,
n
a
k
ed
m
o
le
-
r
at
alg
o
r
ith
m
(
NM
R
)
[
2
1
]
,
m
ar
in
e
p
r
e
d
ato
r
alg
o
r
ith
m
(
MPA)
[
2
2
]
,
b
u
tter
f
ly
o
p
tim
izatio
n
alg
o
r
ith
m
(
B
OA)
[
2
3
]
,
c
h
ee
tah
o
p
tim
izer
(
C
O)
[
2
4
]
,
c
lo
u
d
ed
leo
p
ar
d
o
p
tim
izer
(
C
L
O)
[
2
5
]
,
s
q
u
i
r
r
el
s
ea
r
ch
o
p
tim
i
ze
r
(
SS
O)
[
2
6
]
,
an
d
wh
ite
s
h
ar
k
o
p
tim
izer
(
W
SO)
[
2
7
]
.
Sev
er
al
m
etah
eu
r
is
tics
ar
e
also
b
u
ilt b
y
m
im
ick
in
g
th
e
h
u
m
an
o
r
s
o
cial
b
eh
av
io
r
o
r
g
am
e
m
ec
h
an
ics.
So
m
e
m
etah
eu
r
is
tics
th
at
ar
e
b
u
ilt
b
ased
o
n
th
e
h
u
m
a
n
o
r
s
o
c
ial
b
eh
av
io
r
ar
e
p
ain
t
o
p
tim
ize
r
(
PO)
[
2
8
]
,
s
ewin
g
tr
ain
in
g
-
b
ased
o
p
tim
izer
(
STBO)
[
2
9
]
,
teac
h
in
g
lear
n
in
g
-
b
as
ed
o
p
tim
izer
(
T
L
B
O)
[
3
0
]
,
d
r
i
v
in
g
tr
ai
n
in
g
-
b
ased
o
p
tim
izer
(
DT
B
O)
[
3
1
]
,
c
h
ef
-
b
ased
o
p
tim
izatio
n
alg
o
r
ith
m
(
C
B
OA)
[
3
2
]
,
an
d
elec
tio
n
-
b
ased
o
p
tim
izatio
n
alg
o
r
ith
m
(
E
B
OA)
[
3
3
]
.
Sev
e
r
al
m
etah
eu
r
is
tics
th
at
ar
e
b
u
i
lt
b
ased
o
n
th
e
g
a
m
e
m
ec
h
a
n
ics
ar
e
d
ar
ts
g
am
e
o
p
tim
izer
(
DGO)
[
3
4
]
,
f
o
o
tb
al
l g
am
e
-
b
ased
o
p
tim
izer
(
FB
GO)
[
3
5
]
,
an
d
POA
[
3
6
]
.
Un
f
o
r
tu
n
atel
y
,
th
e
r
e
e
x
is
ts
cr
itiq
u
es
b
ec
au
s
e
o
f
th
e
ex
p
l
o
s
iv
e
n
u
m
b
er
o
f
m
etah
e
u
r
is
tics
.
Ma
n
y
m
etap
h
o
r
-
b
ased
m
etah
eu
r
is
tics
ar
e
claim
ed
to
h
av
e
p
o
o
r
o
r
lim
ited
n
o
v
elty
an
d
h
id
e
b
eh
in
d
th
eir
m
etap
h
o
r
[
1
2
]
.
I
n
th
eir
f
ir
s
t in
tr
o
d
u
ctio
n
,
th
ese
m
etah
eu
r
is
tics
s
h
o
wn
th
eir
ad
o
p
tio
n
o
f
th
e
m
etap
h
o
r
as th
e
n
o
v
elty
[
1
2
]
.
B
u
t,
th
r
o
u
g
h
d
ee
p
er
a
n
aly
s
is
,
esp
ec
ially
b
ased
o
n
th
e
m
ath
e
m
atica
l
m
o
d
el
u
s
ed
in
th
em
,
s
o
m
e
m
etah
eu
r
is
tics
h
av
e
h
ig
h
s
im
ilar
ity
[
1
2
]
.
Stu
d
ies
in
p
r
o
p
o
s
in
g
n
ew
m
etah
e
u
r
is
tics
ar
e
al
s
o
o
f
ten
tr
ap
p
ed
in
b
ea
tin
g
ea
ch
o
th
e
r
r
ath
er
th
an
f
o
cu
s
in
g
o
n
f
in
d
i
n
g
o
r
ex
p
lo
r
in
g
n
ew
s
tr
ateg
ies.
Fo
r
tu
n
ately
,
n
o
t
all
n
ew
m
etah
eu
r
is
tics
ar
e
m
etap
h
o
r
-
b
ased
m
etah
e
u
r
is
tics
.
So
m
e
o
th
er
s
,
s
u
ch
as
g
o
ld
e
n
s
ea
r
ch
o
p
tim
izer
(
GSO)
[
3
7
]
,
to
tal
in
ter
ac
tio
n
alg
o
r
ith
m
(
T
I
A)
[
3
8
]
,
an
d
av
e
r
ag
e
s
u
b
tr
ac
tio
n
-
b
ased
o
p
tim
iz
er
(
ASB
O)
[
3
9
]
ar
e
m
etap
h
o
r
-
f
r
ee
m
etah
e
u
r
is
tics
.
T
h
ey
u
s
e
th
eir
m
ain
s
tr
ateg
y
f
o
r
th
eir
n
am
e.
B
y
ab
s
tr
ac
tin
g
th
e
m
etap
h
o
r
,
v
ar
io
u
s
n
ew
m
etah
e
u
r
is
tics
ar
e
b
u
ilt
b
ased
o
n
s
war
m
in
tellig
en
ce
o
r
s
war
m
m
o
v
em
en
t.
I
n
th
ese
s
war
m
-
b
ased
m
etah
eu
r
is
tics
,
s
o
m
e
r
ef
er
en
ce
s
ar
e
o
f
ten
u
s
ed
to
g
u
id
e
th
e
m
o
v
em
en
t,
s
u
ch
as
g
l
o
b
al
f
in
e
s
t,
lo
ca
l
f
in
est,
r
an
d
o
m
ly
p
ick
e
d
s
o
lu
tio
n
,
r
a
n
d
o
m
ized
s
o
lu
ti
o
n
with
in
th
e
s
p
ac
e,
o
r
co
m
b
in
atio
n
am
o
n
g
t
h
em
.
Fo
r
ex
am
p
le,
t
h
e
s
lim
e
m
o
l
d
alg
o
r
ith
m
u
s
es
g
lo
b
al
f
in
es
t
an
d
two
r
an
d
o
m
ly
p
ick
ed
s
o
lu
tio
n
s
as
r
ef
er
en
ce
s
[
4
0
]
.
Me
an
wh
ile,
cr
o
s
s
o
v
er
o
r
im
itatio
n
s
tr
ateg
y
th
at
b
ec
o
m
es
th
e
m
ain
s
tr
ateg
y
in
th
e
p
o
p
u
la
r
g
en
etic
a
lg
o
r
ith
m
(
GA)
[
4
1
]
b
ec
o
m
es
less
p
o
p
u
lar
.
New
m
etah
eu
r
is
tics
th
at
ad
o
p
t
cr
o
s
s
o
v
er
o
r
im
itatio
n
ap
p
r
o
ac
h
ar
e
m
o
r
e
d
if
f
icu
lt
to
f
i
n
d
.
C
o
r
o
n
a
v
ir
u
s
o
p
tim
izatio
n
alg
o
r
ith
m
(
C
OVI
DOA)
is
an
ex
am
p
le
o
f
n
ew
m
etah
e
u
r
is
tic
th
at
ad
o
p
ts
im
itatio
n
b
ased
s
ea
r
ch
th
r
o
u
g
h
f
r
am
esh
if
tin
g
o
f
t
h
e
p
ar
en
t
[
4
2
]
.
L
ik
e
GA
,
C
OVI
DOA
d
ep
lo
y
s
cr
o
s
s
o
v
er
an
d
m
u
tatio
n
in
a
d
if
f
er
en
t
way
co
m
p
ar
ed
with
GA
[
4
2
]
.
T
h
is
cir
cu
m
s
tan
ce
m
ak
es th
e
d
ev
elo
p
m
en
t
o
f
a
n
ew
m
etah
eu
r
is
tic
b
y
co
m
b
in
in
g
s
war
m
m
o
v
em
en
t a
n
d
im
itatio
n
ch
allen
g
i
n
g
.
B
ased
o
n
th
ese
p
r
o
b
lem
s
an
d
o
p
p
o
r
tu
n
ities
,
th
is
wo
r
k
is
ca
r
r
ied
o
u
t
to
p
r
esen
t
a
n
ew
m
et
ah
eu
r
is
tic
ca
lled
a
g
u
id
ed
-
im
itatio
n
o
p
t
im
izer
(
GI
O)
.
GI
O
is
a
m
etah
eu
r
is
tic
th
at
co
m
b
in
es
th
e
g
u
id
ed
s
ea
r
ch
an
d
im
itatio
n
-
b
ased
s
ea
r
ch
.
I
t
co
n
s
is
t
s
o
f
f
iv
e
g
u
id
ed
s
ea
r
ch
es
an
d
th
r
ee
im
itatio
n
-
b
ased
s
ea
r
ch
es.
I
t
u
s
es
th
r
ee
r
ef
er
en
ce
s
f
o
r
its
s
ea
r
ch
es:
th
e
g
lo
b
al
f
in
est,
a
r
an
d
o
m
ly
p
i
ck
ed
s
o
lu
tio
n
,
an
d
a
r
an
d
o
m
i
ze
d
s
o
lu
tio
n
with
in
s
p
ac
e.
T
h
e
m
ain
s
cien
tific
co
n
tr
ib
u
tio
n
s
to
th
is
p
ap
er
:
i)
t
h
is
wo
r
k
p
r
esen
ts
a
n
o
v
el
m
etah
e
u
r
is
tic
th
at
co
m
b
in
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
Gu
id
ed
imita
tio
n
o
p
timiz
er:
a
meta
h
eu
r
is
tic
co
mb
in
in
g
g
u
id
ed
s
ea
r
ch
…
(
P
u
r
b
a
Da
r
u
K
u
s
u
ma
)
4219
m
u
ltip
le
g
u
id
e
d
s
ea
r
ch
es
an
d
m
u
ltip
le
im
itatio
n
-
b
ased
s
ea
r
ch
es
,
ii)
t
h
is
wo
r
k
ex
h
i
b
its
th
e
m
ain
co
n
ce
p
t,
s
tr
ateg
y
,
an
d
f
o
r
m
u
latio
n
o
f
t
h
e
GI
O
,
iii)
t
h
e
e
f
f
ec
tiv
ity
an
d
ef
f
icien
c
y
o
f
GI
O
ar
e
test
ed
th
r
o
u
g
h
2
3
class
ic
f
u
n
ctio
n
s
th
at
ca
n
b
e
s
p
lit
i
n
to
s
ev
en
h
ig
h
d
im
e
n
s
io
n
u
n
im
o
d
al
f
u
n
ctio
n
s
(
HDUF)
,
s
ix
h
ig
h
d
im
en
s
io
n
m
u
ltimo
d
al
f
u
n
ctio
n
s
(
HDM
F)
,
an
d
ten
f
ix
ed
d
im
en
s
io
n
m
u
ltimo
d
al
f
u
n
ctio
n
s
(
FDMF)
,
an
d
iv
)
t
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
s
h
o
w
n
GI
O
is
also
co
m
p
eted
with
f
o
u
r
n
ew
s
war
m
-
b
ased
m
etah
e
u
r
is
tics
.
T
h
e
r
em
ain
d
er
o
f
th
is
p
ap
er
is
ar
r
an
g
e
d
as
f
o
llo
ws.
Sectio
n
2
p
r
esen
ts
a
r
ev
iew
o
f
s
ev
er
al
n
ew
s
tu
d
ies
p
r
o
p
o
s
in
g
n
ew
m
etah
e
u
r
is
tics
.
Sectio
n
3
p
r
esen
ts
th
e
c
o
n
ce
p
t,
d
etailed
d
escr
ip
tio
n
,
an
d
f
o
r
m
aliza
tio
n
o
f
GI
O.
Sectio
n
3
also
p
r
esen
ts
th
e
test
in
g
s
ce
n
ar
i
o
t
o
ass
ess
th
e
p
er
f
o
r
m
an
ce
o
f
GI
O.
Sectio
n
4
p
r
e
s
en
ts
th
e
ev
alu
atio
n
r
esu
lt
o
f
GI
O,
th
at
co
n
s
is
ts
o
f
th
e
co
m
p
a
r
is
o
n
an
d
d
ata;
an
d
p
er
f
o
r
m
s
th
e
in
-
d
ep
th
a
n
aly
s
is
b
ased
o
n
th
e
test
d
ata,
f
in
d
in
g
s
,
an
d
co
m
p
lex
ity
o
f
GI
O.
I
n
th
e
en
d
,
th
e
co
n
cl
u
s
io
n
an
d
th
e
f
u
tu
r
e
wo
r
k
p
o
t
en
tial
r
eg
ar
d
in
g
t
h
is
wo
r
k
ar
e
p
r
esen
ted
in
s
ec
tio
n
5
.
2.
RE
L
AT
E
D
WO
RK
S
I
n
g
en
e
r
al,
all
m
etah
eu
r
is
tics
ar
e
s
to
ch
asti
c
b
ased
m
eth
o
d
s
.
I
t
m
ea
n
s
th
at
m
etah
eu
r
is
tic
is
id
en
tical
to
th
e
u
s
e
o
f
r
an
d
o
m
n
u
m
b
e
r
s
[
2
5
]
.
As
a
s
ea
r
c
h
in
g
m
eth
o
d
,
m
etah
eu
r
is
tic
d
ep
lo
y
s
r
an
d
o
m
s
ea
r
ch
t
o
o
[
2
5
]
.
Me
tah
eu
r
is
tics
ca
n
also
b
e
s
ee
n
as a
tr
ial
-
an
d
-
er
r
o
r
t
o
o
l.
I
t m
ea
n
s
th
er
e
is
n
o
ass
u
r
an
ce
th
at
th
e
n
ex
t
m
o
v
e
will
p
r
o
d
u
ce
a
b
etter
s
o
lu
tio
n
th
an
th
e
cu
r
r
en
t
s
o
l
u
tio
n
.
Me
tah
e
u
r
is
tic
is
al
s
o
k
n
o
wn
as
iter
ativ
e
m
eth
o
d
[
1
2
]
w
h
er
e
th
e
im
p
r
o
v
em
en
t is p
er
f
o
r
m
e
d
th
r
o
u
g
h
iter
atio
n
.
T
h
er
e
ar
e
v
ar
io
u
s
m
eth
o
d
s
i
n
th
e
s
ea
r
ch
in
g
p
r
o
ce
d
u
r
e
p
e
r
f
o
r
m
e
d
b
y
th
e
m
etah
e
u
r
is
tic.
Un
if
o
r
m
r
an
d
o
m
s
ea
r
ch
is
c
o
m
m
o
n
in
th
e
in
itializatio
n
p
h
ase
[
2
5
]
.
I
t
m
ea
n
s
th
e
in
itial so
lu
tio
n
ca
n
b
e
an
y
w
h
er
e
with
in
th
e
s
ea
r
ch
s
p
ac
e.
I
n
d
if
f
er
en
t
p
o
in
t
o
f
v
iew,
an
y
lo
ca
tio
n
with
in
th
e
s
ea
r
ch
s
p
ac
e
h
as
e
q
u
al
o
p
p
o
r
tu
n
ity
to
b
ec
o
m
e
th
e
i
n
itial so
lu
tio
n
.
Du
r
in
g
th
e
iter
atio
n
p
h
ase,
th
er
e
ar
e
s
ev
er
al
k
in
d
s
o
f
s
ea
r
ch
es:
im
itatio
n
o
r
cr
o
s
s
o
v
er
,
f
u
ll
r
an
d
o
m
s
ea
r
ch
,
n
eig
h
b
o
r
h
o
o
d
s
ea
r
ch
,
an
d
g
u
id
e
d
s
ea
r
ch
.
I
m
itatio
n
i
s
th
e
b
ac
k
b
o
n
e
o
f
ev
o
l
u
tio
n
-
b
ased
m
etah
eu
r
is
tics
,
s
u
ch
as
GA.
I
m
itatio
n
m
ea
n
s
th
e
co
p
y
p
r
o
ce
d
u
r
e
o
f
th
e
v
al
u
e
o
f
s
o
m
e
d
ec
is
io
n
v
a
r
iab
les
to
p
r
o
d
u
ce
th
e
n
ex
t
s
o
lu
tio
n
.
Neig
h
b
o
r
h
o
o
d
s
ea
r
c
h
m
ea
n
s
a
n
ew
s
o
lu
tio
n
is
g
en
er
ated
clo
s
e
to
th
e
cu
r
r
en
t so
lu
tio
n
.
Neig
h
b
o
r
h
o
o
d
s
ea
r
ch
ca
n
b
e
f
o
u
n
d
in
s
ev
er
a
l
m
etah
eu
r
is
tics
,
s
u
ch
as
tab
u
s
ea
r
ch
(
T
S)
[
4
3
]
,
s
im
u
lated
a
n
n
ea
lin
g
(
SA)
[
4
4
]
,
in
v
asiv
e
wee
d
o
p
tim
izer
(
I
W
O)
[
4
5
]
,
a
n
d
ar
tific
ial
b
ee
co
l
o
n
y
(
AB
C
)
[
4
6
]
.
A
f
u
ll
r
a
n
d
o
m
s
ea
r
ch
m
ea
n
s
th
e
n
ew
s
o
lu
tio
n
is
g
e
n
er
ated
with
in
th
e
s
ea
r
ch
s
p
ac
e.
T
h
is
m
et
h
o
d
is
p
er
f
o
r
m
e
d
in
s
o
m
e
m
etah
eu
r
is
tics
,
esp
ec
ially
wh
en
th
e
n
eig
h
b
o
r
h
o
o
d
s
ea
r
ch
f
ac
es
s
tag
n
atio
n
o
r
in
o
th
e
r
wo
r
d
s
,
th
e
ag
en
t
is
s
t
r
u
ctin
g
in
th
e
lo
ca
l
o
p
tim
al.
T
h
e
g
u
id
e
d
s
ea
r
ch
m
ea
n
s
th
e
n
ex
t
s
o
lu
tio
n
is
g
e
n
er
ated
alo
n
g
th
e
way
f
r
o
m
th
e
c
u
r
r
en
t
s
o
lu
tio
n
to
o
r
awa
y
f
r
o
m
t
h
e
r
e
f
er
en
ce
.
T
h
e
g
u
id
ed
s
ea
r
ch
is
th
e
b
ac
k
b
o
n
e
s
tr
a
teg
y
in
th
e
s
war
m
-
b
ased
m
e
tah
eu
r
is
tic.
Par
ticle
s
war
m
o
p
tim
izer
(
PS
O)
is
an
e
x
am
p
le
o
f
th
e
ea
r
ly
b
u
ilt
s
war
m
-
b
ased
m
etah
e
u
r
is
tic
wh
er
e
ea
ch
ag
en
t
p
er
f
o
r
m
s
g
u
id
ed
s
ea
r
c
h
to
war
d
t
h
e
m
ix
t
u
r
e
o
f
t
h
e
g
lo
b
al
f
in
est an
d
its
lo
ca
l f
in
est [
4
7
]
.
A
s
u
m
m
ar
y
o
f
s
o
m
e
n
ew
m
etah
eu
r
is
tics
is
s
h
o
wn
in
T
ab
le
1
.
T
h
e
in
f
o
r
m
atio
n
in
T
ab
le
1
in
clu
d
es
th
e
n
u
m
b
er
o
f
s
tr
ateg
ies,
th
e
ex
is
ten
ce
o
f
th
e
g
u
id
ed
s
ea
r
c
h
,
th
e
ex
is
ten
ce
o
f
th
e
r
an
d
o
m
/n
ei
g
h
b
o
r
h
o
o
d
s
ea
r
ch
,
th
e
ex
is
ten
ce
o
f
im
itatio
n
-
b
ased
s
ea
r
ch
,
r
ef
er
e
n
ce
s
u
s
ed
in
th
e
g
u
id
ed
s
ea
r
ch
,
th
e
ex
is
ten
ce
o
f
s
o
r
tin
g
p
r
o
ce
d
u
r
e
at
th
e
b
eg
in
n
in
g
o
f
ev
e
r
y
iter
atio
n
,
an
d
t
h
e
u
s
e
o
f
m
etap
h
o
r
.
T
a
b
l
e
1
.
S
u
m
m
a
r
y
o
f
s
o
m
e
n
ew
m
e
t
a
h
e
u
r
is
t
i
cs
No
M
e
t
a
h
e
ur
i
s
ti
c
N
u
mb
e
r
o
f
s
t
r
a
t
e
g
i
e
s
G
u
i
d
e
d
s
e
a
r
c
h
R
a
n
d
om
o
r
n
e
i
g
hb
or
h
oo
d
s
e
a
r
c
h
I
mi
t
a
ti
o
n
b
a
s
e
d
s
e
a
r
c
h
R
e
f
e
r
e
n
c
e
s
S
or
t
in
g
d
u
r
i
n
g
i
t
e
r
a
t
io
n
U
s
e
o
f
m
e
t
a
ph
or
1
K
M
A
[
17
]
4
y
e
s
y
e
s
no
S
o
me
f
in
e
s
t
s
o
lu
t
io
n
s
,
f
in
e
s
t
s
o
lu
t
io
n
y
e
s
y
e
s
2
P
O
A
[
1
8]
2
y
e
s
y
e
s
no
R
a
n
d
om
i
z
e
d
s
o
l
ut
i
on
no
y
e
s
3
P
O
A
[
3
6]
2
y
e
s
no
y
e
s
R
a
n
d
om
l
y
pi
c
k
e
d
s
o
l
ut
i
on
no
y
e
s
4
G
S
O
[
3
7]
1
y
e
s
y
e
s
no
L
o
c
a
l
f
in
e
s
t
,
g
lo
b
a
l
f
i
n
e
s
t
no
no
5
NG
O
[
2
0
]
2
y
e
s
y
e
s
no
R
a
n
d
om
l
y
pi
c
k
e
d
s
o
l
ut
i
on
no
y
e
s
6
G
W
O
[
16
]
1
y
e
s
no
no
S
o
me
f
in
e
s
t
s
o
lu
t
io
n
s
y
e
s
y
e
s
7
M
P
A
[
2
2]
5
y
e
s
y
e
s
no
L
o
c
a
l
f
in
e
s
t
no
y
e
s
8
S
M
A
[
4
0]
3
y
e
s
y
e
s
no
G
l
o
b
a
l
f
in
e
s
t
,
t
wo
r
a
nd
om
l
y
pi
c
k
e
d
s
o
l
ut
i
on
s
no
y
e
s
9
T
I
A
[
38
]
1
y
e
s
no
no
A
l
l
ot
h
e
r
s
ol
ut
i
on
s
no
no
10
A
S
B
O
[
3
9]
3
y
e
s
no
no
F
i
n
e
s
t
s
o
l
ut
i
on
,
w
o
r
s
t
s
o
l
ut
i
on
no
no
11
C
O
V
I
D
O
A
[
4
2]
2
no
y
e
s
y
e
s
A
l
l
s
o
lu
t
io
n
s
(
r
ou
l
e
tt
e
w
h
e
e
l
s
)
y
e
s
y
e
s
12
E
B
O
A
[
3
3]
2
y
e
s
y
e
s
no
M
o
s
t
p
o
pu
l
a
r
s
o
l
ut
i
on
no
y
e
s
13
D
T
B
O
[
3
1]
3
y
e
s
y
e
s
no
A
r
a
n
do
ml
y
p
i
c
k
e
d
s
ol
u
ti
o
n
f
r
o
m
s
om
e
f
i
n
e
s
t
s
o
l
ut
i
on
s
y
e
s
y
e
s
14
S
T
B
O
[
29
]
3
y
e
s
y
e
s
y
e
s
A
r
a
n
do
ml
y
p
i
c
k
e
d
s
ol
u
ti
o
n
f
r
o
m
a
ll
b
e
tt
e
r
s
o
l
u
ti
o
n
s
or
i
t
s
e
l
f
no
y
e
s
15
C
B
O
A
[
32
]
3
y
e
s
y
e
s
y
e
s
F
i
n
e
s
t
s
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4220
T
ab
le
1
in
d
icate
s
th
at
m
o
s
t
o
f
th
e
n
ews
o
f
m
eta
h
eu
r
is
tics
ar
e
m
etap
h
o
r
-
b
ased
m
etah
e
u
r
is
tics
.
On
ly
a
f
ew
o
f
th
em
a
r
e
m
eta
p
h
o
r
-
f
r
e
e
m
etah
eu
r
is
tics
.
Mo
s
t
o
f
th
e
s
e
n
ew
m
etah
eu
r
is
tics
ad
o
p
t
s
war
m
in
tellig
en
ce
wh
ich
is
k
n
o
wn
as
th
e
g
u
id
ed
s
ea
r
ch
.
So
m
e
o
f
th
ese
s
war
m
-
b
ased
m
etah
eu
r
is
tics
ar
e
en
r
i
ch
ed
with
r
a
n
d
o
m
s
ea
r
ch
o
r
n
ei
g
h
b
o
r
h
o
o
d
s
ea
r
ch
.
Mo
s
t
o
f
th
ese
m
etah
eu
r
is
tics
also
d
ep
lo
y
m
u
ltip
le
s
tr
ateg
ies
r
ath
er
th
an
s
in
g
le
s
tr
ateg
y
o
n
ly
.
Un
f
o
r
tu
n
ately
,
m
etah
eu
r
is
tic
th
at
u
s
e
im
itatio
n
o
r
c
r
o
s
s
o
v
er
as
its
b
ac
k
b
o
n
e
s
tr
ateg
y
is
v
er
y
r
ar
e.
T
h
e
im
itatio
n
s
tr
ateg
y
b
ec
o
m
e
s
th
e
ad
d
itio
n
al
s
tr
ateg
y
e
m
b
e
d
d
ed
in
th
e
s
war
m
-
b
ased
m
etah
eu
r
is
ti
cs.
B
ased
o
n
th
is
r
e
v
iew,
th
e
o
p
p
o
r
tu
n
ity
to
p
r
o
p
o
s
e
a
n
ew
m
etap
h
o
r
-
f
r
ee
m
etah
eu
r
is
tic
i
s
s
till
o
p
en
.
Mo
r
eo
v
er
,
th
is
o
p
p
o
r
tu
n
ity
al
s
o
co
m
es
f
r
o
m
an
ap
p
r
o
ac
h
in
em
b
ed
d
in
g
s
war
m
in
tellig
en
ce
an
d
im
itatio
n
s
tr
ateg
ies.
As
f
o
u
n
d
in
th
e
n
e
w
m
etah
eu
r
is
tics
,
d
ep
lo
y
in
g
m
u
ltip
le
s
tr
ateg
ies
b
ec
o
m
es
t
h
e
r
atio
n
al
ch
o
ice
s
o
th
at
th
e
p
r
o
p
o
s
ed
m
eta
h
eu
r
is
tic
is
co
m
p
etitiv
e
with
th
e
ex
is
tin
g
m
etah
e
u
r
is
tics
.
3.
M
E
T
H
O
D
3
.
1
.
P
r
o
p
o
s
e
d
mo
d
el
GI
O
is
co
n
s
tr
u
cted
b
y
co
m
b
in
in
g
g
u
id
ed
s
ea
r
ch
es
a
n
d
i
m
itatio
n
b
ased
s
ea
r
ch
es.
I
n
t
h
e
g
u
id
ed
s
ea
r
ch
es,
a
s
o
lu
tio
n
m
o
v
es
r
elativ
e
to
a
r
ef
er
en
ce
.
I
n
th
e
im
it
atio
n
-
b
ased
s
ea
r
ch
,
a
s
o
lu
tio
n
co
p
ies
s
o
m
e
v
alu
es
o
f
th
e
r
ef
e
r
en
ce
.
T
h
er
e
ar
e
th
r
e
e
r
ef
er
en
ce
s
u
s
ed
in
th
is
GI
O:
th
e
g
lo
b
al
f
in
est,
a
r
a
n
d
o
m
l
y
p
ick
ed
s
o
l
u
tio
n
,
a
n
d
a
r
an
d
o
m
ized
s
o
lu
tio
n
with
in
t
h
e
s
ea
r
ch
s
p
ac
e.
T
h
er
e
ar
e
f
iv
e
g
u
id
ed
s
ea
r
ch
e
s
.
T
h
e
f
ir
s
t
g
u
id
ed
s
ea
r
ch
is
s
ea
r
ch
in
g
to
war
d
th
e
g
lo
b
al
f
in
est.
T
h
e
s
ec
o
n
d
g
u
id
ed
s
ea
r
ch
is
s
ea
r
c
h
in
g
t
o
war
d
th
e
r
an
d
o
m
ly
p
ic
k
ed
s
o
lu
tio
n
.
T
h
e
th
ir
d
g
u
id
ed
s
ea
r
ch
is
s
ea
r
ch
in
g
awa
y
f
r
o
m
th
e
r
an
d
o
m
ly
p
ick
e
d
s
o
lu
tio
n
.
T
h
e
f
o
u
r
t
h
g
u
id
e
d
s
ea
r
ch
is
s
ea
r
ch
in
g
to
war
d
th
e
r
an
d
o
m
ized
s
o
lu
tio
n
with
in
th
e
s
p
ac
e.
T
h
e
f
if
th
g
u
id
ed
s
ea
r
ch
is
s
ea
r
ch
in
g
awa
y
f
r
o
m
th
e
r
an
d
o
m
ized
s
o
lu
tio
n
with
in
th
e
s
ea
r
ch
s
p
ac
e.
T
h
e
r
ea
s
o
n
f
o
r
s
ea
r
c
h
in
g
to
war
d
a
n
d
s
ea
r
ch
in
g
awa
y
r
elativ
e
to
th
e
s
ec
o
n
d
an
d
th
ir
d
r
ef
e
r
en
ce
s
is
t
h
at
th
er
e
is
a
p
o
s
s
ib
ili
ty
th
at
th
ese
r
ef
er
en
ce
s
ar
e
b
etter
o
r
wo
r
s
e
th
an
th
e
r
elate
d
s
o
lu
tio
n
.
T
h
e
illu
s
tr
atio
n
o
f
th
ese
g
u
id
ed
s
ea
r
c
h
es is
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
er
e
a
r
e
th
r
ee
im
itatio
n
b
ase
d
s
ea
r
ch
es.
T
h
e
f
ir
s
t
o
n
e
is
im
itatin
g
s
o
m
e
v
alu
es
o
f
th
e
g
lo
b
al
f
in
est.
T
h
e
s
ec
o
n
d
o
n
e
is
im
itatin
g
s
o
m
e
v
alu
es
o
f
th
e
r
an
d
o
m
ly
p
ick
ed
s
o
lu
tio
n
.
T
h
e
th
ir
d
o
n
e
is
im
itatin
g
s
o
m
e
v
alu
es
o
f
th
e
r
an
d
o
m
ized
s
o
lu
t
io
n
with
in
th
e
s
p
a
ce
.
T
h
e
im
itatio
n
-
b
ased
s
ea
r
ch
es
ar
e
p
er
f
o
r
m
ed
s
to
ch
asti
ca
lly
wh
er
e
th
e
p
r
o
b
a
b
ilit
y
o
f
t
h
e
im
itatio
n
-
b
ased
s
ea
r
ch
in
c
r
ea
s
es
as
th
e
iter
atio
n
in
cr
ea
s
es
to
o
.
T
h
is
im
itatio
n
-
b
ased
s
ea
r
ch
is
illu
s
tr
ated
in
Fig
u
r
e
2
.
Fig
u
r
e
1
.
T
h
e
f
iv
e
g
u
id
e
d
s
ea
r
ch
es
Fig
u
r
e
2
.
I
m
itatio
n
b
ased
s
ea
r
ch
E
ac
h
s
ea
r
ch
g
en
e
r
ates
an
o
f
f
s
p
r
in
g
.
I
t
m
ea
n
s
th
er
e
ar
e
ei
g
h
t
o
f
f
-
s
p
r
in
g
s
f
o
r
a
r
elate
d
s
o
lu
tio
n
in
ev
e
r
y
iter
atio
n
.
T
h
e
f
in
est
o
f
f
s
p
r
in
g
is
th
en
ch
o
s
en
f
r
o
m
am
o
n
g
th
ese
eig
h
t
o
n
es
f
o
r
p
o
s
s
ib
le
r
ep
lace
m
en
t
o
f
th
e
cu
r
r
en
t
v
al
u
e
o
f
th
e
r
elate
d
s
o
lu
tio
n
.
T
h
e
p
o
p
u
latio
n
is
co
n
s
tr
u
cted
as
X
={
x
1
,
x
2
,
x
3
,
…,
x
n
}
wh
er
e
x
is
a
s
o
lu
tio
n
,
X
is
a
s
et
o
f
s
o
lu
tio
n
s
,
an
d
n
is
th
e
s
war
m
s
ize.
E
ac
h
s
o
lu
tio
n
also
co
n
s
is
ts
o
f
m
u
ltip
le
en
titi
es so
th
at
x
i
ca
n
b
e
s
h
o
wn
as
{
x
i,
1
,
x
i,
2
,
x
i,
3
,
…,
x
i
,
m
}
wh
er
e
i
is
th
e
s
o
lu
tio
n
in
d
ex
an
d
m
is
d
im
e
n
s
io
n
.
T
h
e
f
o
r
m
aliza
tio
n
o
f
GI
O
is
s
h
o
wn
in
alg
o
r
ith
m
1
.
T
h
is
al
g
o
r
ith
m
ca
n
b
e
s
p
lit
in
to
two
p
ar
ts
:
in
itializatio
n
an
d
iter
atio
n
.
T
h
e
in
itializatio
n
is
s
h
o
wn
f
r
o
m
lin
e
2
to
lin
e
5
wh
ile
th
e
iter
atio
n
is
s
h
o
wn
f
r
o
m
lin
e
6
t
o
lin
e
1
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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tell
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2252
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8
9
3
8
Gu
id
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timiz
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a
meta
h
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is
tic
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in
g
g
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s
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r
ch
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(
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Da
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4221
A
l
g
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r
i
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h
m
1
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d
i
m
it
a
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egin
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o
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ti
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z
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i
us
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n
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4
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p
d
at
e
x
b
e
s
t
u
s
in
g
(
2)
5
e
n
d
f
or
6
for
t
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t
o
t
max
7
s
e
l
ec
t
x
r
e
f
1
u
s
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(
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8
g
e
n
er
a
t
e
x
ref2
us
i
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(
4)
9
for
i
=
1
t
o
n
10
f
or
j
=
1
t
o
m
11
g
e
n
e
r
at
e
r
1
u
s
i
n
g
(
5
)
12
g
e
n
e
r
at
e
c
an
d
i
d
a
te
s
u
s
i
n
g
(
6
)
t
o
(
1
3
)
13
e
nd
f
o
r
14
s
el
e
c
t
c
best,i
u
s
i
ng
(1
4
)
15
u
pd
a
t
e
x
i
u
s
in
g
(
1
5)
16
u
pd
a
t
e
x
best
us
i
n
g
(
2)
17
e
n
d
f
o
r
18
e
n
d
f
or
19
end
Du
r
in
g
in
itializatio
n
,
th
e
in
iti
al
s
o
lu
tio
n
is
d
is
tr
ib
u
ted
r
an
d
o
m
ly
with
in
th
e
s
p
ac
e.
T
h
is
p
r
o
ce
d
u
r
e
is
f
o
r
m
u
lated
b
y
u
s
in
g
(
1
)
.
Me
a
n
wh
ile,
th
e
g
lo
b
al
f
in
est
is
u
p
d
ated
ev
er
y
tim
e
a
n
ew
s
o
lu
tio
n
is
in
itialized
.
T
h
e
u
p
d
atin
g
p
r
o
ce
d
u
r
e
o
f
th
e
g
l
o
b
al
f
in
est
is
f
o
r
m
u
lated
b
y
u
s
in
g
(
2
)
.
I
n
(
1
)
,
x
i
,
j
is
s
o
lu
tio
n
i
in
d
im
en
s
io
n
j
,
r
2
is
th
e
r
ea
l
r
an
d
o
m
n
u
m
b
e
r
f
r
o
m
0
to
1
,
x
l,
j
is
th
e
lo
wer
b
o
r
d
e
r
o
f
d
im
en
s
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n
j
,
an
d
x
u,
j
is
th
e
u
p
p
er
b
o
r
d
e
r
o
f
d
im
en
s
io
n
j
.
I
n
(
2
)
,
x
best
is
th
e
g
lo
b
al
f
in
est
an
d
f
is
th
e
o
b
ject
iv
e
f
u
n
ctio
n
.
T
h
e
r
elate
d
s
o
lu
ti
o
n
alter
s
th
e
cu
r
r
e
n
t
v
alu
e
o
f
t
h
e
g
lo
b
al
f
in
est o
n
ly
if
th
e
r
elate
d
s
o
lu
tio
n
is
b
etter
th
an
th
e
g
l
o
b
al
f
in
est o
n
e.
,
=
,
+
2
(
,
−
,
)
(
1
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′
=
{
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(
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(
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1
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G
W
O
[
1
6
]
G
S
O
[
3
7
]
P
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A
[
3
6
]
C
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[
1
9
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G
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14
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T
h
e
d
ata
in
T
ab
le
4
in
d
icate
s
th
at
GI
O
is
s
u
p
er
io
r
in
h
an
d
lin
g
th
e
FDMFs
.
B
u
t
it
s
s
u
p
er
io
r
ity
is
n
o
t
s
o
h
ig
h
as
in
th
e
f
ir
s
t
an
d
s
ec
o
n
d
g
r
o
u
p
s
o
f
f
u
n
ctio
n
s
.
GI
O
is
th
e
f
in
est
o
n
ly
in
h
an
d
lin
g
f
iv
e
f
u
n
ctio
n
s
(
F1
4
,
F1
5
,
F1
8
,
F2
0
,
a
n
d
F2
1
)
.
Me
an
wh
ile,
GI
O
b
ec
o
m
es
th
e
s
ec
o
n
d
f
in
est
at
h
a
n
d
lin
g
f
iv
e
f
u
n
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s
(
F1
6
,
F1
7
,
F1
9
,
F2
2
,
an
d
F2
3
)
.
O
n
th
e
o
t
h
er
h
an
d
,
C
OA
is
th
e
f
in
est at
h
an
d
lin
g
f
o
u
r
f
u
n
ctio
n
s
(
F1
6
,
F1
7
,
F2
2
,
an
d
F2
3
)
.
T
h
e
s
ce
n
ar
io
o
f
th
e
s
ec
o
n
d
as
s
ess
m
en
ts
f
o
r
b
o
th
p
ar
ts
is
as
f
o
llo
ws.
I
n
th
e
f
ir
s
t
p
ar
t,
th
er
e
ar
e
two
v
alu
es
f
o
r
s
war
m
s
ize:
1
0
an
d
3
0
.
I
n
th
e
s
ec
o
n
d
p
ar
t,
t
h
er
e
a
r
e
also
two
v
alu
es
f
o
r
th
e
m
ax
im
u
m
iter
atio
n
:
4
0
an
d
8
0
.
I
n
th
e
f
ir
s
t
p
ar
t,
t
h
e
m
ax
im
u
m
iter
a
tio
n
is
s
et
3
0
wh
ile
in
th
e
s
ec
o
n
d
p
ar
t,
th
e
s
war
m
s
ize
is
s
et
5
,
co
lu
m
n
s
2
a
n
d
3
.
T
h
e
d
ata
o
f
t
h
e
f
ir
s
t p
ar
t a
n
d
th
e
s
ec
o
n
d
p
a
r
t is sh
o
wn
in
T
ab
le
5
,
co
lu
m
n
s
4
an
d
5
.
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at
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ize
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ig
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ican
tly
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t
o
f
f
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ir
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ata
in
co
lu
m
n
4
an
d
4
in
T
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b
le
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also
in
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icate
s
th
at
th
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two
cir
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etwe
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o
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ax
im
u
m
iter
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ag
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ir
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th
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th
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in
cr
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i
n
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ax
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m
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m
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r
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th
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v
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tly
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3
T
h
e
d
ata
in
T
ab
le
6
in
d
icate
s
th
at
th
er
e
is
n
o
t
an
y
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
t
o
f
th
e
av
er
ag
e
f
it
n
ess
s
co
r
e
d
u
e
to
th
e
i
n
cr
ea
s
in
g
o
f
s
war
m
s
ize
in
m
o
s
t f
u
n
ctio
n
s
.
T
h
er
e
ar
e
o
n
ly
two
f
u
n
ctio
n
s
in
th
e
f
ir
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r
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p
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an
d
o
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e
f
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n
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in
th
e
s
ec
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n
d
g
r
o
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p
,
wh
er
e
its
av
er
a
g
e
f
itn
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o
r
e
is
im
p
r
o
v
ed
s
ig
n
if
ican
tly
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o
r
tu
n
ately
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s
o
m
e
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ctio
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s
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t
h
e
s
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o
n
d
cir
cu
m
s
tan
ce
o
cc
u
r
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b
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a
u
s
e
th
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lo
b
al
o
p
tim
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lu
tio
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h
as
b
e
en
f
o
u
n
d
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th
e
e
n
d
s
o
lu
t
io
n
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n
ea
r
th
e
g
l
o
b
al
o
p
t
im
al
s
o
lu
tio
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.
T
h
ese
f
u
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n
s
ar
e
(
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,
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0
,
F1
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1
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,
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6
,
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7
,
F2
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,
F2
1
,
F2
2
,
F2
3
)
.
T
h
e
d
ata
in
T
ab
le
6
also
in
d
icate
s
th
at
th
er
e
ar
e
o
n
ly
th
r
ee
f
u
n
ctio
n
s
wh
o
s
e
av
er
ag
e
f
itn
ess
s
co
r
e
is
im
p
r
o
v
ed
b
y
in
cr
ea
s
i
n
g
th
e
m
ax
im
u
m
iter
atio
n
f
r
o
m
4
0
to
8
0
.
I
t
m
ea
n
s
th
at
co
n
v
er
g
en
ce
h
as
b
ee
n
ac
h
iev
ed
i
n
th
e
lo
w
m
a
x
im
u
m
iter
atio
n
f
o
r
m
o
s
t
f
u
n
ctio
n
s
.
T
h
is
co
n
v
e
r
g
en
ce
o
cc
u
r
s
wh
et
h
er
th
e
en
d
s
o
lu
tio
n
is
th
e
g
lo
b
al
o
p
tim
al
s
o
lu
tio
n
,
n
ea
r
to
th
e
g
lo
b
al
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p
tim
al
s
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lu
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,
o
r
s
till
f
ar
f
r
o
m
t
h
e
g
lo
b
a
l o
p
tim
al
s
o
lu
tio
n
.
4
.
2
.
Dis
cus
s
io
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I
n
th
is
s
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tio
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,
th
e
d
is
cu
s
s
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f
o
cu
s
es
o
n
th
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im
p
r
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v
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e
n
t
o
f
th
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p
r
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p
o
s
ed
GI
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i
n
r
elat
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n
to
th
e
r
ec
en
t
d
e
v
elo
p
m
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n
t
o
f
m
eta
h
e
u
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is
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.
Dif
f
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en
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f
r
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m
s
ev
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r
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en
t
s
tu
d
ies
th
at
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till
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s
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ld
m
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eu
r
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lik
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GA
an
d
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ap
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m
p
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th
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p
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m
an
ce
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f
GI
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o
n
ly
with
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t
m
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eu
r
is
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Mo
r
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v
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th
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cu
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also
in
clu
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es th
e
tech
n
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co
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p
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s
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an
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d
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c
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m
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an
d
th
e
p
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ten
tial f
o
r
f
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th
e
r
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tu
d
y
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T
h
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m
ain
f
in
d
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g
o
f
th
is
p
ap
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r
is
th
r
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h
ev
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,
GI
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p
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r
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an
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all
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f
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an
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T
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s
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p
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r
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o
f
GI
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m
o
s
tly
co
m
es
f
r
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m
th
e
h
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h
d
im
en
s
i
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n
f
u
n
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n
s
.
Me
a
n
wh
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its
s
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p
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r
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is
n
o
t
s
o
h
ig
h
wh
en
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an
d
lin
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th
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f
ix
ed
d
im
en
s
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m
u
ltim
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d
al
f
u
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o
n
s
.
Sin
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th
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test
u
s
in
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o
d
al
f
u
n
ctio
n
s
is
d
esig
n
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to
ev
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th
e
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GI
O
to
GW
O,
GS
O,
POA,
an
d
C
OA
in
m
o
s
t
o
f
f
u
n
ctio
n
s
in
2
3
class
ic
f
u
n
ctio
n
s
ca
n
b
e
s
ee
n
as
t
h
e
s
u
p
e
r
io
r
ity
o
f
m
u
ltip
le
s
tr
ateg
ies
to
lim
ited
s
tr
ateg
ies.
As
s
ee
n
i
n
T
a
b
le
1
,
GW
O
an
d
GSO
d
ep
lo
y
o
n
ly
a
s
in
g
le
s
tr
ateg
y
.
Me
an
wh
ile,
POA
d
ep
lo
y
s
o
n
ly
two
s
tr
ateg
ies
wh
er
e
th
e
f
ir
s
t
s
tr
ateg
y
is
g
u
id
ed
s
ea
r
ch
,
an
d
t
h
e
s
ec
o
n
d
s
tr
ateg
y
is
im
itatio
n
-
b
ased
s
ea
r
ch
[
3
4
]
.
T
h
is
s
u
p
er
io
r
ity
also
m
ea
n
s
th
e
n
ec
ess
ity
in
v
ar
iety
o
f
t
h
e
r
ef
e
r
en
ce
s
.
GI
O
u
s
es
th
r
ee
r
ef
er
en
ce
s
:
g
lo
b
al
f
in
est,
a
r
an
d
o
m
ly
p
ick
ed
s
o
lu
tio
n
,
an
d
a
r
a
n
d
o
m
ize
d
s
o
lu
tio
n
.
GW
O
u
s
es
s
in
g
le
r
ef
er
en
ce
:
r
esu
ltan
t
o
f
s
o
m
e
f
in
est
s
o
lu
tio
n
s
[
1
6
]
.
GSO
u
s
es
two
r
ef
er
e
n
ce
s
:
g
lo
b
al
f
in
e
s
t
an
d
lo
ca
l
f
in
est
[
3
7
]
.
POA
u
s
es
a
r
ef
er
en
ce
:
a
r
an
d
o
m
ize
d
s
elec
ted
s
o
lu
tio
n
[
3
6
]
.
C
OA
u
s
es
two
r
ef
er
en
ce
s
:
th
e
f
in
est
s
o
lu
tio
n
in
e
v
er
y
iter
atio
n
a
n
d
a
r
an
d
o
m
ize
d
s
o
lu
tio
n
with
in
th
e
s
ea
r
ch
s
p
ac
e
[
1
9
]
.
T
h
e
co
m
p
lex
ity
an
al
y
s
is
in
th
e
iter
atio
n
p
h
ase
o
f
GI
O
is
s
h
o
wn
as
O
(8
n
.
m
.
t
max
)
w
h
er
e
n
is
th
e
s
war
m
s
ize,
m
is
d
im
en
s
io
n
o
r
d
ec
is
i
o
n
v
ar
ia
b
le,
an
d
t
max
is
th
e
m
ax
im
u
m
iter
atio
n
.
T
h
is
m
ea
n
s
th
e
co
m
p
u
tatio
n
al
co
m
p
lex
ity
o
f
GI
O
is
p
r
o
p
o
r
ti
o
n
al
to
t
h
e
s
war
m
s
ize,
d
ec
is
io
n
v
a
r
iab
les,
o
r
th
e
m
a
x
im
u
m
iter
atio
n
.
T
er
m
8
in
th
is
b
ig
-
O
n
o
tatio
n
is
ap
p
lied
d
u
e
to
th
er
e
ar
e
eig
h
t
s
ea
r
ch
es
i
n
ev
er
y
iter
atio
n
f
o
r
e
v
er
y
ag
e
n
t.
As
th
e
d
im
en
s
io
n
o
r
d
ec
is
io
n
v
ar
iab
les
ca
n
n
o
t
b
e
ad
ju
s
ted
,
u
s
er
s
h
o
u
ld
f
o
cu
s
o
n
th
e
s
war
m
s
ize
a
n
d
m
ax
im
u
m
iter
atio
n
as
th
e
h
y
p
er
p
ar
am
eter
s
etu
p
.
T
h
e
m
a
in
co
n
s
id
er
atio
n
is
w
h
eth
er
ad
j
u
s
tin
g
th
e
s
war
m
s
ize
o
r
m
a
x
i
m
u
m
iter
atio
n
m
a
y
im
p
r
o
v
e
t
h
e
p
er
f
o
r
m
a
n
ce
.
Alth
o
u
g
h
GI
O
is
p
r
o
v
en
in
p
r
o
d
u
cin
g
s
u
p
er
io
r
p
er
f
o
r
m
a
n
ce
,
i
t
s
till
h
as
lim
itatio
n
s
.
T
h
e
f
ir
s
t
lim
itatio
n
is
th
is
s
u
p
er
io
r
p
er
f
o
r
m
a
n
ce
c
o
m
es
f
r
o
m
m
u
ltip
le
s
ee
d
s
wh
er
e
ea
ch
s
ee
d
r
ep
r
esen
ts
a
d
is
tin
ct
s
ea
r
ch
m
eth
o
d
.
I
n
o
t
h
er
w
o
r
d
s
,
GI
O
p
e
r
f
o
r
m
s
m
ass
iv
e
m
u
ltip
le
s
ea
r
c
h
es
alth
o
u
g
h
o
n
ly
s
in
g
le
f
i
n
est
s
ee
d
r
ep
lace
s
th
e
c
u
r
r
e
n
t
s
o
lu
tio
n
.
I
t
is
d
if
f
er
en
t
f
r
o
m
m
an
y
o
th
er
m
etah
eu
r
is
tics
th
at
em
p
lo
y
o
n
ly
o
n
e
s
ea
r
ch
m
eth
o
d
o
r
f
ew
s
ea
r
ch
m
eth
o
d
s
.
T
h
e
s
ec
o
n
d
lim
itatio
n
o
f
th
is
wo
r
k
is
th
at
th
er
e
ar
e
a
lo
t
o
f
u
s
e
ca
s
es
th
a
t
ca
n
b
e
u
s
ed
to
in
v
esti
g
ate
GI
O
in
a
m
o
r
e
co
m
p
r
eh
e
n
s
iv
e
m
an
n
er
.
T
h
ese
u
s
e
ca
s
es
ca
n
b
e
th
eo
r
etica
l
o
r
p
r
ac
tical.
B
u
t
th
er
e
is
n
o
s
in
g
le
p
ap
er
th
at
ca
n
ac
c
o
m
m
o
d
ate
a
ll
th
ese
u
s
e
ca
s
es.
T
h
e
p
r
ac
tical
u
s
e
ca
s
es
ca
n
also
b
e
f
o
u
n
d
in
b
r
o
a
d
er
f
ield
s
o
f
en
g
in
ee
r
in
g
with
v
ar
i
o
u
s
ch
ar
ac
ter
is
tics
,
s
u
ch
as wh
eth
er
th
ey
ar
e
n
u
m
er
ical
o
r
co
m
b
i
n
ato
r
ial
p
r
o
b
lem
s
.
Fu
tu
r
e
d
ev
elo
p
m
en
t
ca
n
b
e
p
er
f
o
r
m
ed
in
v
ar
io
u
s
way
s
.
First,
b
o
th
GI
O
an
d
C
OA
o
u
tp
er
f
o
r
m
th
e
o
th
er
th
r
ee
m
etah
eu
r
is
tic
.
I
t
will
b
e
in
ter
esti
n
g
to
h
y
b
r
id
ize
th
ese
two
m
etah
eu
r
is
tics
to
m
ak
e
m
o
r
e
p
o
we
r
f
u
l
an
d
co
m
p
r
eh
e
n
s
iv
e
m
etah
e
u
r
is
tic.
Seco
n
d
,
th
e
im
itatio
n
-
b
ased
s
ea
r
ch
s
h
o
u
ld
b
e
m
o
r
e
p
r
o
m
o
t
ed
as
it
is
n
o
w
less
p
o
p
u
lar
t
h
an
th
e
s
war
m
m
o
v
e
m
en
t.
I
t
is
b
ec
au
s
e
GA
is
s
till
im
p
lem
en
ted
in
m
a
n
y
o
p
tim
izatio
n
s
tu
d
ies
d
u
e
to
its
f
lex
ib
ilit
y
an
d
o
p
en
n
ess
to
im
p
r
o
v
em
e
n
t.
T
h
ir
d
,
th
e
u
s
e
o
f
m
u
ltip
le
s
tr
ateg
ies
an
d
m
u
ltip
le
r
ef
er
en
ce
s
will
b
ec
o
m
e
m
o
r
e
p
o
p
u
lar
in
th
e
f
u
t
u
r
e.
Fo
u
r
t
h
,
r
a
n
d
o
m
s
ea
r
ch
is
s
till
im
p
o
r
tan
t
to
b
e
im
p
lem
en
te
d
in
ev
er
y
iter
atio
n
to
o
v
er
c
o
m
e
th
e
lo
ca
l
o
p
tim
al
p
r
o
b
lem
.
Fu
tu
r
e
s
tu
d
ies
ca
n
also
b
e
tak
en
b
y
em
p
lo
y
in
g
G
I
O
to
s
o
lv
e
v
ar
io
u
s
o
p
tim
izatio
n
p
r
o
b
l
em
s
.
T
h
e
r
e
ar
e
also
v
ar
i
o
u
s
s
ets
o
f
s
tan
d
ar
d
ass
ess
m
en
ts
,
s
u
ch
as
C
E
C
s
ets
in
wh
ich
t
h
e
p
r
o
b
lem
s
ar
e
m
o
r
e
c
o
m
p
lex
d
u
e
to
th
e
e
x
is
ten
ce
o
f
eq
u
ality
an
d
in
eq
u
ality
b
o
u
n
d
a
r
ies.
5.
CO
NCLU
SI
O
N
T
h
is
wo
r
k
h
as
b
u
ilt
an
d
s
h
o
w
n
a
n
ew
m
etap
h
o
r
-
f
r
ee
m
etah
eu
r
is
tic
ca
lled
GI
O.
As
its
n
a
m
e
im
p
lies
,
GI
O
d
ep
lo
y
s
b
o
t
h
g
u
id
e
d
s
ea
r
ch
wh
ich
is
th
e
b
ac
k
b
o
n
e
o
f
s
war
m
-
b
ased
m
etah
eu
r
is
tic
an
d
im
itatio
n
-
b
ase
d
s
ea
r
ch
wh
ich
is
th
e
b
ac
k
b
o
n
e
o
f
e
v
o
lu
tio
n
-
b
ased
m
etah
e
u
r
i
s
tic.
T
h
is
ap
p
r
o
ac
h
is
tr
a
n
s
f
o
r
m
ed
in
t
o
eig
h
t
s
ea
r
ch
es
(
f
iv
e
g
u
id
e
d
s
ea
r
ch
e
s
an
d
th
r
ee
im
itatio
n
-
b
ased
s
ea
r
ch
es).
T
h
r
o
u
g
h
s
im
u
latio
n
,
GI
O
o
u
tp
er
f
o
r
m
s
GW
O,
G
SO,
POA,
an
d
C
OA
in
h
an
d
lin
g
m
o
s
t
u
n
im
o
d
al
an
d
m
u
ltimo
d
al
f
u
n
ctio
n
s
.
I
t
in
d
icate
s
th
at
GI
O
h
as
ex
ce
l
len
t
ex
p
lo
r
atio
n
an
d
e
x
p
l
o
itatio
n
ca
p
ab
ilit
ies.
T
h
r
o
u
g
h
h
y
p
er
p
ar
am
eter
test
,
GI
O
ca
n
f
in
d
an
ac
ce
p
ta
b
le
s
o
lu
tio
n
in
th
e
lo
w
s
war
m
s
ize
an
d
lo
w
m
ax
im
u
m
iter
atio
n
cir
cu
m
s
tan
ce
s
.
I
n
th
e
f
u
tu
r
e
,
th
e
co
n
s
tr
u
cti
o
n
o
f
n
ew
m
etah
eu
r
is
tic
is
s
til
l
av
ailab
le.
T
h
is
d
e
v
elo
p
m
en
t
ca
n
b
e
p
er
f
o
r
m
ed
b
y
h
y
b
r
id
izi
n
g
GI
O
an
d
C
OA.
Mo
r
eo
v
er
,
u
p
co
m
i
n
g
s
tu
d
ies
c
an
b
e
ca
r
r
ie
d
o
u
t
b
y
im
p
lem
en
tin
g
GI
O
t
o
h
an
d
le
v
ar
io
u
s
o
p
tim
izatio
n
p
r
o
b
lem
s
in
a
b
r
o
a
d
er
ar
ea
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
f
u
n
d
in
g
f
o
r
p
u
b
licatio
n
o
f
th
is
p
ap
er
is
p
r
o
v
id
ed
b
y
T
el
k
o
m
Un
iv
er
s
ity
,
I
n
d
o
n
esia.
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