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d
itio
n
,
a
co
m
p
ar
is
io
n
is
m
a
d
e
w
it
h
th
e
w
ei
g
h
ted
-
s
u
m
b
as
ed
b
i
-
o
b
j
ec
tiv
e
ap
p
r
o
ac
h
.
Ou
r
w
o
r
k
co
n
ce
r
n
s
b
i
-
o
b
j
ec
tiv
e
s
ch
ed
u
li
n
g
in
d
is
tr
ib
u
te
d
r
ea
l
ti
m
e
e
m
b
ed
d
ed
s
y
s
te
m
s
w
h
ile
m
ak
e
s
p
an
an
d
r
eliab
ili
t
y
ar
e
th
e
co
n
s
id
er
ed
o
b
j
ec
tiv
es.
T
w
o
h
eu
r
i
s
tic
s
co
o
p
er
ate
in
a
h
ier
ar
ch
ical
w
a
y
to
g
en
er
ate
s
o
l
u
tio
n
s
,
w
h
ile
an
a
d
ap
tatio
n
m
o
d
u
le
is
u
s
ed
to
ac
h
iev
e
a
b
est
s
p
ac
e
ex
p
lo
r
atio
n
.
T
h
e
p
ap
er
o
r
g
an
izatio
n
i
s
as
f
o
llo
w
s
:
I
n
s
ec
t
io
n
2
,
s
o
m
e
as
s
u
p
tio
n
s
co
n
ce
r
n
in
g
s
y
s
te
m
m
o
d
el
s
an
d
o
b
j
ec
tiv
es
ar
e
p
r
esen
ted
.
Sectio
n
3
,
r
ec
alls
th
e
m
u
lti
-
o
b
j
ec
tiv
e
o
ti
m
izatio
n
an
d
p
r
esen
ts
b
i
cr
iter
ia
s
ch
ed
u
li
n
g
as
a
b
i
-
o
b
j
ec
tiv
e
p
r
o
b
le
m
.
I
n
s
ec
tio
n
4
,
t
h
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
is
d
escr
ib
ed
.
B
ef
o
r
e
co
n
clu
d
i
n
g
,
s
ec
tio
n
5
d
ep
icts
s
o
m
e
ex
p
er
i
m
en
tal
r
es
u
lts
a
s
s
e
s
s
i
n
g
o
u
r
ap
p
r
o
ac
h
.
2.
I
NP
UT
A
SS
UM
P
T
I
O
NS
I
n
o
u
r
w
o
r
k
,
s
o
m
e
as
s
u
m
p
tio
n
s
ar
e
co
n
s
id
er
ed
(
Sectio
n
2
.
1
a
n
d
Sectio
n
2
.
2
)
.
2
.
1
.
Sy
s
t
em
De
s
cr
iptio
n
Dis
tr
ib
u
ted
r
ea
l
-
ti
m
e
e
m
b
ed
d
ed
s
y
s
te
m
s
ar
e
co
m
p
o
s
ed
o
f
t
wo
p
r
in
cip
al
p
ar
ts
,
w
h
ich
ar
e
t
h
e
s
o
f
t
w
ar
e
p
ar
t (
th
e
ap
p
licatio
n
alg
o
r
it
h
m
)
an
d
th
e
h
ar
d
w
ar
e
p
ar
t (
th
e
d
is
tr
ib
u
ted
ar
ch
itec
tu
r
e)
.
T
h
e
s
p
ec
if
icatio
n
o
f
t
h
e
s
e
s
y
s
te
m
s
in
v
o
l
v
e
d
escr
ib
in
g
th
e
alg
o
r
it
h
m
co
m
p
o
n
en
t
s
(
alg
o
r
ith
m
m
o
d
el)
,
th
e
ar
ch
it
ec
tu
r
e
co
m
p
o
n
en
t
s
(
ar
ch
itectu
r
e
m
o
d
el)
,
an
d
th
e
ex
ec
u
tio
n
ch
ar
ac
ter
is
t
ic
s
o
f
th
e
al
g
o
r
ith
m
o
n
to
th
e
ar
ch
itect
u
r
e
(
ex
ec
u
tio
n
m
o
d
el)
.
T
h
e
ap
p
licatio
n
is
m
o
d
eled
b
y
a
d
ata
f
lo
w
g
r
ap
h
,
ca
lled
a
lg
o
r
ith
m
g
r
ap
h
a
n
d
n
o
ted
Alg
.
E
ac
h
v
er
te
x
is
a
task
a
n
d
ea
ch
ed
g
e
i
s
a
d
ata
d
ep
en
d
en
c
y
.
Fig
u
r
e
1
A
.
A
l
g
o
r
ith
m
Gr
ap
h
A
l
g
Fig
u
r
e
1
B
.
A
r
ch
itect
u
r
e
Gr
ap
h
A
r
c
A
ta
s
k
o
f
A
l
g
ca
n
b
e
eit
h
er
an
ex
ter
n
al
i
n
p
u
t
/o
u
tp
u
t
tas
k
o
r
a
co
m
p
u
tatio
n
ta
s
k
.
T
ask
s
w
it
h
n
o
p
r
ed
ec
ess
o
r
(
r
esp
.
n
o
s
u
cc
ess
o
r
)
ar
e
th
e
in
p
u
t
i
n
ter
f
ac
es
(
r
esp
.
o
u
tp
u
t)
,
h
an
d
li
n
g
th
e
e
v
en
ts
p
r
o
d
u
ce
d
b
y
th
e
s
en
s
o
r
s
(
r
esp
.
ac
tu
ato
r
s
)
.
T
h
e
i
n
p
u
t
s
o
f
a
co
m
p
u
ta
tio
n
ta
s
k
m
u
s
t p
r
ec
ed
e
its
o
u
tp
u
ts
.
Fig
u
r
e
1
A
is
a
n
ex
a
m
p
le
o
f
a
n
al
g
o
r
ith
m
g
r
ap
h
,
w
it
h
s
i
x
ta
s
k
s
:
I
a
n
d
I
’
(
r
esp
.
O)
ar
e
i
n
p
u
ts
(
r
esp
.
o
u
tp
u
ts
)
ta
s
k
s
,
w
h
ile
A
,
B
,
an
d
C
ar
e
co
m
p
u
tatio
n
ta
s
k
s
.
T
h
e
d
ata
-
d
ep
en
d
en
c
ies
b
et
w
ee
n
tas
k
s
ar
e
d
ep
icted
b
y
ar
r
o
w
s
.
Fo
r
i
n
s
ta
n
ce
th
e
d
ata
-
d
ep
en
d
en
ce
A
C
ca
n
co
r
r
esp
o
n
d
t
o
th
e
s
e
n
d
in
g
o
f
s
o
m
e
ar
it
h
m
etic
r
e
s
u
l
t
co
m
p
u
ted
b
y
A
an
d
n
ee
d
ed
b
y
C
.
T
h
e
ar
ch
itectu
r
e
i
s
m
o
d
eled
b
y
a
g
r
ap
h
,
ca
lled
ar
ch
itect
u
r
e
g
r
ap
h
a
n
d
n
o
ted
A
r
c.
E
ac
h
v
er
tex
i
s
a
p
r
o
ce
s
s
o
r
,
an
d
ea
ch
ed
g
e
is
a
co
m
m
u
n
icatio
n
li
n
k
.
Fi
g
u
r
e
1
B
g
iv
e
s
a
n
e
x
a
m
p
le
o
f
a
n
ar
c
h
itectu
r
e
g
r
ap
h
,
w
it
h
th
r
ee
p
r
o
ce
s
s
o
r
s
P
1
,
P
2
an
d
P3
,
an
d
th
r
ee
co
m
m
u
n
icatio
n
li
n
k
s
.
An
ex
ec
u
tio
n
ti
m
e
E
x
e
i
s
d
ef
i
n
ed
f
o
r
ea
ch
p
air
(
ti,
p
j
)
;
it
r
e
p
r
esen
ts
t
h
e
w
o
r
s
t
ca
s
e
ex
ec
u
ti
o
n
ti
m
e
o
f
th
e
tas
k
ti
o
n
t
h
e
p
r
o
ce
s
s
o
r
p
j
,
ex
p
r
ess
ed
i
n
ti
m
e
u
n
it
s
.
A
s
s
u
m
i
n
g
th
at
p
r
o
ce
s
s
o
r
s
ar
e
h
eter
o
g
en
eo
u
s
,
o
n
e
ta
s
k
co
u
ld
h
a
v
e
d
if
f
er
en
t
e
x
ec
u
tio
n
ti
m
es
o
n
d
if
f
er
en
t
p
r
o
ce
s
s
o
r
s
.
W
h
en
a
g
i
v
en
ta
s
k
ca
n
n
o
t
b
e
ex
ec
u
ted
o
n
a
g
iv
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n
p
r
o
ce
s
s
o
r
,
th
e
ass
o
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i
o
n
is
e
x
p
r
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b
y
th
e
v
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e
”
”.
On
th
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o
t
h
er
h
a
n
d
,
to
e
ac
h
p
air
(
d
i,
lj
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,
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s
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2
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1
5
A
p
p
licatio
n
a
n
d
ar
ch
itect
u
r
e
m
o
d
elin
g
u
s
in
g
g
r
ap
h
s
,
is
u
s
e
f
u
l
f
o
r
o
b
j
ec
tiv
e
d
ef
in
i
tio
n
s
(
s
u
b
s
ec
tio
n
2
.
2
.
)
.
2
.
2
.
M
a
k
esp
a
n a
n
d Re
lia
bil
it
y
O
bje
ct
iv
es
T
h
e
m
a
k
esp
a
n
o
r
s
ch
ed
u
le
le
n
g
th
i
s
th
e
e
n
d
ex
ec
u
tio
n
ti
m
e
o
f
th
e
tas
k
t
h
at
is
co
m
p
leted
l
ast
a
m
o
n
g
all
task
s
.
I
t is d
ef
i
n
ed
as f
o
llo
w
s
:
(
1
)
w
h
er
e,
en
d
(
ti,
p
j
)
is
th
e
ti
m
e
a
t
w
h
ic
h
tas
k
ti ter
m
in
ate
s
its
e
x
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t
io
n
o
n
p
r
o
ce
s
s
o
r
p
j
.
A
f
u
n
ctio
n
ca
lled
s
ch
ed
u
le
p
r
ess
u
r
e
,
ca
lcu
lated
f
r
o
m
t
h
e
g
r
ap
h
alg
o
r
ith
m
,
is
p
r
o
p
o
s
ed
in
[
1
5
]
,
it
is
n
o
ted
(n)
an
d
is
d
ef
in
ed
f
o
r
ea
ch
tas
k
ti
T
(n)
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p
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n
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e
h
e
u
r
is
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an
d
co
m
p
to
th
e
s
et
o
f
co
m
p
eti
to
r
task
s
i.e
th
o
s
e
n
o
t
y
et
s
c
h
ed
u
led
an
d
w
h
o
s
e
p
r
ed
ec
ess
o
r
s
ar
e
alr
ea
d
y
s
ch
ed
u
led
)
an
d
ea
ch
p
r
o
ce
s
s
o
r
p
j
as f
o
llo
w
s
:
(
2
)
w
h
er
e:
S
(n)
best(ti,
pj
)
: th
e
ea
r
lies
t ti
m
e
a
t
w
h
ic
h
tas
k
ti c
an
s
tar
t e
x
ec
u
t
io
n
o
n
p
r
o
ce
s
s
o
r
p
j
;
S¯
(n)
ti
: th
e
lates
t star
t ti
m
e
f
r
o
m
en
d
o
f
ti [
1
5
]
;
Fu
r
t
h
er
m
o
r
e,
ex
ec
u
tio
n
a
n
d
tr
an
s
m
i
s
s
io
n
t
i
m
e
s
h
a
v
e
to
co
n
s
id
er
ed
,
h
en
ce
th
e
f
o
llo
w
i
n
g
ex
p
r
ess
io
n
:
(
3
)
Sch
ed
u
le
p
r
es
s
io
n
i
s
u
s
ed
to
s
elec
t
th
e
b
est
tas
k
w
h
ich
m
i
m
i
zises
t
h
e
le
n
g
t
h
o
f
th
e
cr
it
ical
p
ath
.
T
h
at
m
ea
n
s
t
h
at
s
c
h
ed
u
le
p
r
ess
io
n
m
i
m
izatio
n
i
m
p
lie
s
s
c
h
ed
u
le
le
n
g
th
o
n
e.
Ot
h
er
w
is
e,
b
o
th
p
r
o
ce
s
s
o
r
s
an
d
co
m
m
u
n
icatio
n
li
n
k
s
ar
e
s
u
b
ject
to
f
ailu
r
es.
A
cc
o
r
d
in
g
to
th
e
m
o
d
el
p
r
o
p
o
s
ed
in
[
1
2
]
a
n
d
c
o
n
s
id
er
in
g
th
e
o
cc
u
r
r
en
ce
o
f
f
ai
lu
r
es
f
o
llo
w
i
n
g
a
P
o
is
s
o
n
la
w
w
i
th
a
co
n
s
tan
t
p
ar
a
m
e
ter
λ
,
t
h
e
r
eliab
il
it
y
o
f
a
p
r
o
ce
s
s
o
r
P
(
r
esp
ec
tiv
el
y
,
a
co
m
m
u
n
icatio
n
lin
k
L
)
d
u
r
in
g
t
h
e
d
u
r
atio
n
d
is
:
(
4
)
T
h
e
r
eliab
ilit
y
o
f
t
h
e
ta
s
k
o
r
d
ata
d
ep
en
d
en
c
y
X
p
lace
d
o
n
to
th
e
h
ar
d
w
ar
e
co
m
p
o
n
e
n
t
C
,
w
it
h
a
n
ex
ec
u
t
io
n
ti
m
e
ex
e(
X,
C
)
,
is
t
h
en
d
e
f
in
ed
as
f
o
llo
w
s
:
(
5
)
B
ec
au
s
e
th
e
r
eliab
ilit
y
d
ep
en
d
s
in
tr
in
s
icall
y
o
n
th
e
d
u
r
atio
n
o
f
th
e
task
s
an
d
co
m
m
u
n
icati
o
n
s
,
s
o
m
e
tech
n
ical
d
if
f
ic
u
ltie
s
r
aise
w
h
e
n
u
s
in
g
b
o
th
r
eliab
ilit
y
an
d
m
a
k
esp
an
a
s
o
b
j
ec
tiv
es [
1
2
]
.
So
,
r
ath
er
th
a
n
u
s
in
g
t
h
e
u
s
u
al
m
o
d
el
o
f
t
h
e
r
eliab
ilit
y
[
1
6
]
,
w
e
u
s
e
t
h
e
co
n
ce
p
t
o
f
GS
F
R
(
Glo
b
al
S
y
s
te
m
Fail
u
r
e
R
ate)
d
ef
i
n
ed
in
[
1
2
]
,
an
d
n
o
ted
.
T
h
e
GSFR
o
f
a
s
tatic
s
ch
ed
u
le
S,
is
co
m
p
u
ted
as
f
o
llo
w
s
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
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n
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&
C
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l.
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3
,
Ma
r
ch
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1
8
:
7
8
9
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7
9
8
792
(
6
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w
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U(
S)
i
s
t
h
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tal
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io
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ar
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ce
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it
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h
e
G
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R
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ail
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r
e
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ate
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ti
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e
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le,
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ee
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a
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it
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ch
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led
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to
a
s
in
g
le
p
r
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ce
s
s
o
r
.
3.
SCH
E
DU
L
I
NG
A
S A
M
U
LTI
-
O
B
J
E
CT
I
VE
P
RO
B
L
E
M
A
m
u
lti
-
o
b
j
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e
p
r
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b
le
m
i
s
a
p
r
o
b
lem
w
h
o
s
e
r
eso
lu
t
io
n
i
m
p
lies
m
u
ltip
le
o
b
j
ec
tiv
es
co
n
s
id
er
atio
n
.
T
h
e
g
en
er
al
o
p
ti
m
izatio
n
p
r
o
b
le
m
is
d
e
f
in
ed
as
f
o
llo
w
s
[
1
7
]
:
w
h
er
e
m
i
s
t
h
e
n
u
m
b
er
o
f
o
b
j
ec
tiv
e
f
u
n
c
tio
n
s
,
k
is
t
h
e
n
u
m
b
er
o
f
i
n
eq
u
alit
y
co
n
s
tr
ai
n
ts
a
n
d
l
i
s
t
h
e
n
u
m
b
er
o
f
eq
u
alit
y
co
n
s
tr
ain
t
s
.
x
E
n
is
a
d
esi
g
n
v
ec
to
r
,
also
ca
lled
d
ec
is
io
n
v
ec
to
r
,
w
h
er
e
n
is
th
e
n
u
m
b
er
o
f
its
i
n
d
ep
en
d
en
t
v
ar
iab
les x
i
.
f
(
x
)
E
n
is
a
v
ec
to
r
o
f
o
b
j
ec
tiv
e
f
u
n
ctio
n
s
w
h
er
e:
\
f
i
(
x
)
ar
e
al
s
o
ca
lle
d
o
b
j
ec
tiv
e
o
r
cr
iter
ia.
E
ac
h
p
o
in
t
i
n
t
h
e
d
esig
n
s
p
ac
e
m
ap
s
to
a
p
o
in
t
i
n
t
h
e
o
b
j
ec
tiv
e
s
p
ac
e
b
u
t th
e
r
e
v
er
s
e
m
a
y
n
o
t to
b
e
tr
u
e.
E
v
alu
a
tio
n
o
f
s
o
l
u
tio
n
s
is
d
o
n
e
b
y
u
s
i
n
g
t
h
e
P
ar
eto
’
d
o
m
i
n
an
ce
’
(
P
ar
eto
1
9
0
6
)
.
A
p
o
ten
tiall
y
in
ter
esti
n
g
s
o
l
u
tio
n
i
s
a
s
o
lu
ti
o
n
s
u
c
h
as
i
m
p
r
o
v
i
n
g
o
n
e
o
b
j
ec
tiv
e
ca
n
’
t
b
e
d
o
n
e
w
it
h
o
u
t
d
eg
r
ad
in
g
at
leas
t
an
o
th
er
o
n
e.
S
u
c
h
s
o
l
u
tio
n
s
co
n
s
ti
tu
te
t
h
e
P
ar
eto
o
p
ti
m
al
s
et.
E
ac
h
s
o
lu
t
io
n
ca
n
b
e
r
ep
r
esen
ted
b
y
its
o
b
j
ec
tiv
e
v
ec
to
r
in
a
m
u
l
ti
-
di
m
en
s
io
n
a
l sp
ac
e
(
Fig
u
r
e
2
)
.
L
et
z
a
n
d
z’
b
e
t
w
o
p
o
in
ts
o
f
t
h
e
o
b
j
ec
tiv
e
s
p
ac
e.
Fo
r
m
al
l
y
,
th
e
P
ar
eto
d
o
m
in
a
n
ce
o
n
o
b
j
ec
tiv
e
v
ec
to
r
s
is
d
ef
i
n
ed
as:
A
p
o
in
t z is P
a
r
eto
d
o
min
a
ted
b
y
a
p
o
in
t z’
:
W
h
ile
th
e
co
n
ce
p
t
o
f
d
o
m
i
n
an
ce
i
s
r
elate
d
to
o
b
j
ec
tiv
e
s
p
ac
e,
th
e
o
p
ti
m
alit
y
co
n
ce
r
n
s
t
h
e
d
ec
is
io
n
s
p
ac
e.
Fig
u
r
e
2
.
Dec
is
io
n
a
n
d
Ob
j
ec
t
iv
e
Sp
ac
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
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m
p
Sci
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SS
N:
2502
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4752
Bi
-
o
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jective
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w
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tics
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mb
ed
d
ed
R
e
a
l
-
time
S
ystem
(
K
a
lla
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mo
u
d
i
)
793
P
ar
eto
o
p
tim
al
s
o
lu
tio
n
s
co
n
s
titu
te
w
h
at
i
s
ca
lled
th
e
P
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o
p
tim
al
s
et
w
h
ile
th
e
co
r
r
esp
o
n
d
in
g
o
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j
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ec
to
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s
i.e
t
h
o
s
e
o
n
es
n
o
t
d
o
m
in
ated
,
ar
e
s
aid
to
b
e
o
n
t
h
e
P
ar
eto
f
r
o
n
t.
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h
e
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g
h
b
o
r
h
o
o
d
is
a
n
o
th
er
i
m
p
o
r
ta
n
t c
o
n
ce
p
t in
c
o
m
b
i
n
ato
r
ial
o
p
ti
m
izat
io
n
.
I
t i
s
d
ef
i
n
ed
as f
o
llo
w
s
:
“T
h
e
n
eig
h
b
o
r
h
o
o
d
o
f
a
s
o
lu
tio
n
s
S
i
s
a
s
u
b
s
et
o
f
c
o
n
fig
u
r
a
tio
n
s
o
r
s
o
lu
tio
n
s
o
f
S
th
a
t
a
r
e
d
ir
ec
tly
r
ea
ch
a
b
le
b
y
a
g
iven
tr
a
n
s
fo
r
ma
tio
n
o
f
s
.
I
t
is
n
o
t
ed
V
(
s
)
a
n
d
a
s
o
l
u
tio
n
s
V
(
s
)
is
s
a
id
to
b
e
a
n
eig
h
b
o
r
o
f s.”
P
ar
ticu
lar
l
y
,
f
r
o
m
a
g
i
v
en
s
o
l
u
tio
n
,
v
ar
io
u
s
Nei
g
h
b
o
r
h
o
o
d
s
t
r
u
ctu
r
es
ca
n
b
e
e
s
tab
lis
h
ed
ac
co
r
d
in
g
to
v
ar
io
u
s
tr
a
n
s
f
o
r
m
atio
n
s
w
h
ile
a
tr
an
s
f
o
r
m
atio
n
i
s
d
ef
i
n
ed
as
an
ap
p
licatio
n
:
w
h
er
e
S
is
a
s
et
o
f
s
o
l
u
t
io
n
s
an
d
P
(
S)
is
a
s
u
b
s
et
o
f
S.
Su
ch
a
co
n
ce
p
t
is
u
s
e
f
u
l
i
n
s
e
ar
ch
s
p
ac
e
s
tr
u
ct
u
r
in
g
an
d
in
d
ef
in
i
n
g
th
e
s
et
o
f
s
o
lu
tio
n
s
th
at
ca
n
b
e
r
ea
ch
ed
f
r
o
m
a
g
iv
e
n
s
o
l
u
tio
n
th
r
o
u
g
h
a
s
er
ies
o
f
tr
an
s
f
o
r
m
atio
n
s
.
I
n
o
u
r
w
o
r
k
,
s
c
h
ed
u
li
n
g
is
b
i
-
o
b
j
ec
tiv
e
an
d
is
th
er
ef
o
r
e
co
n
s
id
er
ed
as
a
b
i
-
o
b
j
ec
tiv
e
o
p
t
i
m
izatio
n
p
r
o
b
lem
.
So
lu
t
io
n
s
i
n
d
ec
is
io
n
s
p
ac
e
ar
e
s
h
ed
u
les ea
c
h
o
f
t
h
e
m
ex
p
r
es
s
in
g
b
o
th
ta
s
k
a
s
s
i
g
n
m
en
t to
p
r
o
ce
s
s
o
r
s
an
d
a
g
iv
e
n
e
x
ec
u
tio
n
o
r
d
er
.
E
ac
h
s
c
h
ed
u
le
(
s
o
lu
tio
n
)
ca
n
b
e
ev
a
lu
ated
i
n
t
h
e
o
b
j
ec
tiv
e
s
p
ac
e
(
Fi
g
u
r
e
3
)
d
ef
in
ed
b
y
t
h
e
co
n
s
id
er
ed
o
b
jectiv
es
(
s
u
b
s
ec
tio
n
2
.
2
.
)
.
T
h
e
f
ir
s
t
o
b
j
ec
tiv
e
is
Ma
k
e
s
p
an
(
e
q
u
atio
n
(
1
)
)
th
at
is
d
ef
in
ed
u
s
in
g
th
e
co
s
t
f
u
n
ctio
n
n
a
m
ed
s
ch
ed
u
le
p
r
ess
u
r
e
(
eq
u
atio
n
(
3
)
)
w
h
ile
t
h
e
s
ec
o
n
d
o
b
j
ec
tiv
e
is
GSFR
(
eq
u
atio
n
(
6
)
)
.
R
ath
er
th
a
n
a
s
i
n
g
le
s
o
l
u
tio
n
,
a
s
et
o
f
s
o
l
u
tio
n
s
(
s
c
h
ed
u
l
es)
{s1
,
s
2
,
·
·
·
}
is
g
e
n
er
ated
.
E
ac
h
s
ch
ed
u
le
s
i
m
ak
e
s
a
co
m
p
r
o
m
i
s
e
b
et
w
ee
n
t
h
e
Ma
k
e
s
p
an
an
d
th
e
r
eliab
ilit
y
a
n
d
is
e
x
p
r
ess
ed
b
y
f
(
s
i)
.
4.
T
H
E
P
RO
P
O
SE
D
BI
-
O
B
J
E
CT
I
V
E
AP
P
RO
ACH
Giv
e
n
an
alg
o
r
it
h
m
a
n
d
a
tar
g
et
ar
ch
itectu
r
e,
w
e
ai
m
to
p
r
o
d
u
ce
s
ch
ed
u
les
r
ea
lizi
n
g
co
m
p
r
o
m
is
e
s
b
et
w
ee
n
t
w
o
o
b
j
ec
tiv
es b
y
m
i
n
i
m
izi
n
g
Ma
k
esp
a
n
an
d
m
a
x
i
m
izi
n
g
r
eliab
ili
t
y
.
Fig
u
r
e
3
.
O
b
j
ec
t
iv
e
Sp
ac
es
Fig
u
r
e
4
.
T
h
e
Pro
p
o
s
ed
A
p
p
r
o
ac
h
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
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n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
9
,
No
.
3
,
Ma
r
ch
2
0
1
8
:
7
8
9
–
7
9
8
794
4
.
1
.
Appro
a
ch
P
rinciples
Ou
r
ap
p
r
o
ac
h
is
b
ased
o
n
t
w
o
s
ch
ed
u
li
n
g
h
e
u
r
is
tic
s
w
i
th
a
n
ad
ap
tatio
n
m
o
d
u
le
to
i
m
p
r
o
v
e
s
o
lu
tio
n
ex
p
lo
r
atio
n
b
y
ex
te
n
d
i
n
g
th
e
s
ea
r
ch
s
p
ac
e.
T
h
e
t
w
o
h
e
u
r
is
t
ics
co
o
p
er
ate
w
h
ile
d
ea
lin
g
a
l
ter
n
ati
v
el
y
w
it
h
t
h
e
t
w
o
o
b
j
ec
tiv
es:
Ma
k
esp
an
a
n
d
r
eliab
ilit
y
.
W
e
u
s
e
h
ier
ar
ch
ical
s
c
h
ed
u
l
in
g
to
m
i
n
i
m
ize
Ma
k
esp
an
a
n
d
to
m
ax
i
m
ize
r
eliab
ilit
y
b
y
o
p
ti
m
izi
n
g
o
n
e
o
b
j
ec
tiv
e
at
a
ti
m
e,
i.e
,
w
e
tr
an
s
f
o
r
m
o
n
e
o
f
o
b
j
ec
tiv
es
in
to
a
co
n
s
tr
ain
t,
w
h
ich
a
llo
w
s
t
h
e
s
o
lv
in
g
o
f
th
e
p
r
o
b
lem
b
y
o
p
ti
m
izi
n
g
th
e
s
ec
o
n
d
o
b
j
ec
tiv
e
u
n
d
er
th
e
co
n
s
tr
ai
n
t
of
th
e
f
ir
s
t o
n
e.
As
s
h
o
w
n
i
n
Fi
g
u
r
e
4
,
th
e
f
ir
s
t
h
eu
r
i
s
tic
AR
B
(
A
d
ap
tiv
e
R
eli
ab
ilit
y
-
b
ased
B
i
-
o
b
j
ec
tiv
e
h
e
u
r
is
tic)
h
as
as
i
n
p
u
t
s
t
h
e
a
lg
o
r
it
h
m
A
l
g
,
t
h
e
ar
c
h
itect
u
r
e
A
r
c
a
n
d
a
GS
FR
(
r
eliab
ilit
y
o
b
j
ec
tiv
e)
v
al
u
e
0
as
a
co
n
s
tr
ai
n
t.
AR
B
h
e
u
r
is
tic
e
x
ec
u
tio
n
lead
s
to
a
s
o
lu
t
io
n
w
i
t
h
t
w
o
v
al
u
e
s
:
M
ARB
a
n
d
A
R
B
.
L
ik
e
AR
B
,
A
MB
(
A
d
ap
tiv
e
Ma
k
esp
a
n
-
b
ased
B
i
-
o
b
j
ec
tiv
e
h
eu
r
i
s
tic)
h
a
s
as
in
p
u
ts
t
h
e
al
g
o
r
ith
m
Alg
,
t
h
e
ar
ch
itect
u
r
e
Ar
c
an
d
th
e
s
o
l
u
tio
n
p
r
o
d
u
ce
d
b
y
A
R
B
h
eu
r
i
s
tic.
T
h
e
Ma
k
e
s
p
an
v
al
u
e
M
AR
B
,
p
r
o
d
u
ce
d
b
y
AR
B
,
is
co
n
s
id
er
ed
as
a
co
n
s
tr
ai
n
t
i
n
o
r
d
er
to
m
ax
i
m
ize
r
eliab
ilit
y
.
T
h
e
r
esu
lt
is
a
s
ch
ed
u
le
w
ith
t
w
o
v
al
u
es:
M
A
MB
an
d
A
MB
.
C
o
o
p
er
atio
n
b
et
w
ee
n
o
u
r
h
ier
ar
ch
ical
h
eu
r
is
tics
lead
s
to
a
s
et
o
f
s
o
l
u
tio
n
s
a
m
o
n
g
w
h
ic
h
t
h
e
o
p
ti
m
al
o
n
es
ac
co
r
d
in
g
to
P
ar
eto
o
p
tim
al
it
y
ar
e
s
elec
ted
.
I
n
th
e
ca
s
e
o
f
to
o
clo
s
est
co
m
p
r
o
m
is
e
v
alu
e
s
,
w
e
p
r
o
p
o
s
e
to
in
tr
o
d
u
ce
an
ad
ap
tatio
n
m
o
d
u
le
to
s
ea
r
ch
f
o
r
n
eig
h
b
o
r
s
.
No
te
th
a
t
th
e
f
u
ct
io
n
f
ass
o
ciati
n
g
d
ec
i
s
io
n
a
n
d
o
b
j
ec
tiv
e
s
p
ac
es
is
n
o
t
s
u
r
j
ec
tiv
e.
T
h
at
m
ea
n
s
t
h
er
e
ca
n
b
e
a
co
m
p
r
o
m
i
s
e
v
alu
e
in
o
b
j
ec
tiv
e
s
p
ac
e
w
h
ic
h
is
n
o
t
a
s
s
o
ciate
d
w
i
th
a
n
y
s
o
l
u
tio
n
(
s
ch
ed
u
li
n
g
)
i
n
d
ec
is
io
n
s
p
ac
e.
Fo
r
th
is
r
ea
s
o
n
,
t
h
e
ad
ap
ta
tio
n
m
u
s
t
o
p
er
ate
o
n
d
ec
is
io
n
s
p
ac
e
b
y
cr
ea
ti
n
g
n
eig
h
b
o
r
s
o
f
a
g
i
v
e
n
s
c
h
ed
u
le,
th
is
o
n
e
(
n
eig
h
b
o
r
)
h
av
i
n
g
n
e
ce
s
s
ar
el
y
a
co
m
p
r
o
m
is
e
v
alu
e
in
o
b
j
ec
tiv
e
s
p
a
ce.
Fig
u
r
e
5
.
A
d
ap
tatio
n
Mo
d
u
le
Fig
u
r
e
6
.
So
lu
tio
n
T
r
an
s
la
tio
n
T
o
ad
j
u
s
t
a
cu
r
r
en
t
s
o
lu
tio
n
,
th
e
ad
ap
tatio
n
m
o
d
u
le
(
Fo
g
u
r
e
5
)
is
b
ased
o
n
th
e
n
eig
h
b
o
r
h
o
o
d
s
tr
u
ct
u
r
e
co
n
ce
p
t
(
s
u
b
s
ec
tio
n
3
.
)
.
I
n
th
i
s
w
o
r
k
,
a
p
er
m
u
ta
tio
n
-
b
ased
n
ei
g
h
b
o
r
h
o
o
d
s
tr
u
c
tu
r
e
is
u
s
ed
;
it
is
d
ef
in
ed
b
y
t
h
e
f
o
llo
w
i
n
g
tr
an
s
f
o
r
m
atio
n
:
V
: S
P
(
S)
s
u
ch
t
h
at:
s
ch
ed
u
le
s
S
V
(
s
)
=
{
s
’
s
’
i
s
a
s
ch
ed
u
le
a
s
s
o
ciate
d
to
a
g
iv
e
n
p
er
m
u
tati
o
n
o
f
s
}
Fig
u
r
e
6
is
an
ex
a
m
p
le
o
f
to
o
clo
s
est
co
m
p
r
o
m
is
e
v
al
u
es
f
(
s
)
(
b
lu
e
co
lo
r
)
an
d
f
(
s
’
)
(
p
in
k
co
lo
r
)
in
th
e
o
b
j
ec
tiv
e
s
p
ac
e.
I
n
t
h
i
s
ca
s
e,
th
e
ad
ap
tatio
n
m
o
d
u
le
h
as
t
h
e
r
o
le
o
f
e
x
te
n
d
in
g
t
h
e
s
ea
r
c
h
s
p
ac
e
b
y
ap
p
l
y
in
g
p
er
m
u
tatio
n
s
o
n
s
.
T
h
is
o
n
e
c
o
u
ld
b
e
r
ep
lace
d
b
y
o
n
e
o
f
its
n
eig
h
b
o
r
s
.
B
y
ch
a
n
g
in
g
t
h
e
s
t
ar
tin
g
co
n
s
tr
ai
n
t
f
o
r
co
o
p
er
atin
g
h
e
u
r
is
tic
s
an
d
u
s
i
n
g
t
h
e
ad
ap
tatio
n
m
o
d
u
le,
a
r
an
g
e
o
f
s
o
lu
t
io
n
s
i
s
o
b
tain
ed
w
h
ile
t
h
e
o
n
es
t
h
at
s
u
it c
u
r
r
en
t
n
ee
d
s
ar
e
s
elec
ted
.
4
.
2
.
Schedu
lin
g
Alg
o
rit
h
m
s
T
h
e
h
eu
r
is
tic
s
A
R
B
an
d
A
MB
i
m
p
le
m
e
n
ti
n
g
th
e
p
r
o
p
o
s
ed
s
o
lu
tio
n
ar
e
g
r
ee
d
y
li
s
t sc
h
ed
u
l
in
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Bi
-
o
b
jective
S
ch
e
d
u
lin
g
w
ith
C
o
o
p
era
tin
g
Heu
r
is
tics
fo
r
E
mb
ed
d
ed
R
e
a
l
-
time
S
ystem
(
K
a
lla
Ha
mo
u
d
i
)
795
T
h
ey
co
o
p
er
ate
to
d
ea
l
alter
n
ati
v
el
y
w
it
h
t
h
e
m
a
k
e
s
p
an
an
d
th
e
r
eliab
ili
t
y
o
b
j
ec
tiv
es.
T
h
e
f
ir
s
t
h
eu
r
i
s
tic
is
b
ased
o
n
a
co
s
t
f
u
n
ct
io
n
ca
lled
s
c
h
ed
u
le
p
r
ess
u
r
e
(
eq
u
atio
n
(
3
)
in
s
u
b
s
ec
tio
n
2
.
2
.
)
to
s
elec
t
th
e
b
est
tas
k
w
h
ich
m
i
n
i
m
izes
th
e
len
g
th
o
f
t
h
e
cr
itical
p
ath
.
T
h
e
s
u
p
er
s
cr
ip
t
n
u
m
b
er
,
i
n
p
ar
en
th
e
s
es
i
n
b
o
t
h
A
l
g
o
r
ith
m
s
A
R
B
an
d
A
MB
,
r
ef
er
s
to
th
e
h
eu
r
i
s
tic
s
tep
.
C
o
n
s
tr
ain
ed
b
y
a
s
tar
ti
n
g
co
n
s
tr
ain
t
w
h
ich
i
s
a
GSF
R
v
a
lu
e,
AR
B
alg
o
r
ith
m
w
o
r
k
s
as
f
o
llo
w
s
:
• Ini
t
ia
liza
t
io
n:
t
w
o
li
s
ts
ar
e
u
s
ed
,
-
T
(0)
com
p
:
is
t
h
e
co
m
p
etito
r
tas
k
lis
t
k
n
o
w
i
n
g
t
h
at
a
task
i
s
s
a
id
to
b
e
co
m
p
etito
r
if
it
is
n
o
t
y
et
s
c
h
ed
u
led
an
d
all
its
p
r
ed
ec
ess
o
r
s
ar
e
alr
ea
d
y
s
ch
ed
u
led
;
-
T
(
0
)
sched
: sch
ed
u
led
task
li
s
t
w
h
ic
h
w
ill co
n
s
tit
u
te,
i
n
th
e
e
n
d
,
f
i
n
al
s
c
h
ed
u
le.
•
E
v
a
lua
t
io
n:
s
tep
(
1
)
ca
lcu
lates,
f
o
r
ea
ch
co
m
p
e
tito
r
tas
k
i
ts
s
c
h
ed
u
le
p
r
ess
u
r
e
o
n
ea
c
h
p
r
o
ce
s
s
o
r
s
u
ch
t
h
e
s
p
ec
if
ied
co
n
s
tr
ain
t (
)
is
s
ati
s
f
ied
.
•
Select
io
n:
th
is
s
tep
(
2
)
is
a
s
elec
tio
n
o
f
t
h
e
b
est
p
a
ir
(
task
,
p
r
o
ce
s
s
o
r
)
,
th
u
s
t
h
e
o
n
e
m
i
n
i
m
izi
n
g
s
ch
ed
u
le
p
r
ess
u
r
e.
•
Up
da
t
e:
s
tep
(
3
)
co
n
s
i
s
ts
in
o
n
e
h
a
n
d
to
ad
d
th
e
c
h
o
s
en
ta
s
k
to
s
ch
ed
u
led
tas
k
li
s
t
a
n
d
i
n
t
h
e
o
th
er
h
a
n
d
to
r
e
m
o
v
e
th
e
c
h
o
s
en
tas
k
f
r
o
m
co
m
p
eti
to
r
task
lis
t
as
w
ell
as
all
its
s
u
cc
es
s
o
r
s
s
u
c
h
th
at
p
r
ed
ec
ess
o
r
s
o
f
th
e
latter
s
ar
e
alr
ea
d
y
s
ch
ed
u
led
.
Step
s
1
,
2
an
d
3
o
f
A
R
B
alg
o
r
ith
m
ar
e
r
ep
ea
ted
u
n
til
th
er
e
ar
e
n
o
m
o
r
e
co
m
p
etito
r
tas
k
s
.
T
h
e
A
R
B
r
esu
lt
is
a
p
air
(
M
A
RB
,
A
RB
)
r
ep
r
esen
tin
g
Ma
k
e
s
p
an
an
d
G
SF
R
v
a
lu
e
s
.
D
u
r
in
g
its
ex
ec
u
t
io
n
,
AR
B
alg
o
r
it
h
m
m
a
y
r
ef
er
to
t
h
e
ad
ap
tatio
n
m
o
d
u
le.
I
n
a
s
i
m
ilar
m
a
n
n
er
b
u
t
co
n
s
tr
ain
ed
b
y
Ma
k
e
s
p
an
v
al
u
e
p
r
o
d
u
ce
d
b
y
AR
B
al
g
o
r
ith
m
,
A
MB
a
lg
o
r
it
h
m
ai
m
s
to
o
p
ti
m
ize
t
h
is
ti
m
e
r
eliab
ilit
y
o
b
j
ec
tiv
e.
A
MB
alg
o
r
ith
m
w
o
r
k
s
as
f
o
llo
w
s
:
L
i
k
e
AR
B
,
A
MB
m
a
y
a
ls
o
r
ef
er
to
a
d
ap
tatio
n
m
o
d
u
le
i
f
s
o
lu
tio
n
ad
j
u
s
t
m
en
t
is
n
ec
es
s
ar
y
.
A
R
B
an
d
A
MB
e
x
ec
u
t
io
n
ca
n
b
e
r
ep
ea
ted
as
m
a
n
y
ti
m
es
a
s
t
h
e
d
ec
is
io
n
m
a
k
er
d
ec
id
es.
I
n
ad
d
itio
n
,
th
e
s
tar
ti
n
g
co
n
s
tr
ain
t c
an
b
e
m
o
d
i
f
ied
to
cr
ea
te
a
n
e
w
p
r
o
ce
s
s
in
s
ta
n
ce
.
As
m
u
ch
f
o
r
AR
B
as
f
o
r
AM
B
,
in
th
e
ca
s
e
o
f
to
o
clo
s
est
s
o
lu
tio
n
s
(
in
o
b
j
ec
tiv
e
s
p
ac
e
)
,
th
e
ad
ap
tatio
n
p
r
o
ce
d
u
r
e
co
u
ld
r
ep
lace
th
e
cu
r
r
en
t
s
o
lu
tio
n
(
i
n
d
ec
is
io
n
s
p
ac
e)
b
y
o
n
e
o
f
i
ts
n
eig
h
b
o
r
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
9
,
No
.
3
,
Ma
r
ch
2
0
1
8
:
7
8
9
–
7
9
8
796
I
n
o
u
r
w
o
r
k
,
w
e
p
r
o
p
o
s
e
p
er
m
u
tatio
n
-
b
ased
ad
ap
tatio
n
.
I
t
co
n
s
is
ts
o
f
g
e
n
er
atin
g
s
ch
ed
u
les
a
m
o
n
g
w
h
ic
h
t
h
er
e
co
u
ld
b
e
a
s
c
h
e
d
u
le
f
r
o
m
w
h
ich
th
e
s
ea
r
ch
w
il
l
b
e
r
estar
ted
.
P
er
m
u
tatio
n
ap
p
licatio
n
o
n
s
g
en
er
ate
s
s
c
h
ed
u
les
t
h
at
ar
e
n
eig
h
b
o
r
s
o
f
s
.
Ho
w
ev
er
,
o
n
l
y
s
c
h
ed
u
les
s
atis
f
y
i
n
g
r
ea
l
ti
m
e
co
n
s
tr
ain
t
s
ar
e
co
n
s
id
er
ed
.
A
cu
r
r
en
t
s
c
h
ed
u
l
e
s
is
r
ep
lace
d
b
y
o
n
e
o
f
its
n
eig
h
b
o
r
s
i
f
(
i)
th
is
o
n
e
is
n
o
t
y
et
s
el
ec
ted
an
d
(
ii)
its
co
m
p
r
o
m
is
e
v
al
u
e
is
n
o
t
c
lo
s
est
to
th
o
s
e
o
f
alr
ea
d
y
s
ele
cted
s
ch
ed
u
les
a
n
d
(
iii)
a
m
o
n
g
s
n
ei
g
h
b
o
r
s
,
it
is
th
is
w
h
ic
h
co
r
r
esp
o
n
d
s
to
th
e
n
o
n
-
d
o
m
in
ated
co
m
p
r
o
m
i
s
e
v
al
u
e
in
o
b
j
ec
tiv
e
s
p
ac
e.
I
n
th
e
ca
s
e
o
f
n
o
n
eig
h
b
o
r
s
atis
f
ie
s
th
e
t
h
r
ee
co
n
d
itio
n
s
,
s
is
s
a
v
ed
as c
u
r
r
e
n
t
s
o
lu
tio
n
.
I
n
th
i
s
w
a
y
,
th
e
s
ea
r
ch
s
p
ac
e
is
ex
te
n
d
ed
to
th
e
Nei
g
h
b
o
r
h
o
o
d
s
tr
u
ctu
r
e
p
r
o
d
u
ce
d
b
y
p
er
m
u
tatio
n
s
.
A
s
s
o
o
s
as
a
s
o
lu
tio
n
(
s
c
h
ed
u
le)
s
at
is
f
y
in
g
t
h
e
th
r
ee
co
n
d
itio
n
s
ab
o
v
e
i
s
f
o
u
n
d
,
it
i
s
co
n
s
id
er
ed
as
th
e
cu
r
r
en
t
s
ch
ed
u
le.
No
te
th
at,
s
u
ch
a
s
c
h
ed
u
le
m
a
y
n
o
t b
e
f
o
u
n
d
,
in
w
h
ic
h
ca
s
e
cu
r
r
en
t sc
h
ed
u
le
i
s
s
a
v
ed
.
5.
SI
M
UL
AT
I
O
N
S
T
o
ev
alu
ate
o
u
r
ap
p
r
o
ac
h
,
w
e
h
a
v
e
ap
p
lied
th
e
A
MB
an
d
AR
B
h
eu
r
i
s
tics
to
a
s
et
o
f
r
an
d
o
m
alg
o
r
ith
m
g
r
ap
h
s
an
d
a
n
ar
ch
i
tectu
r
e
g
r
ap
h
co
m
p
o
s
ed
o
f
3
,
4
,
an
d
5
p
r
o
ce
s
s
o
r
s
.
W
e
u
s
e
S
y
n
DE
x
to
g
e
n
er
ate
th
e
co
m
p
lete
s
et
o
f
alg
o
r
it
h
m
g
r
ap
h
s
.
S
y
n
DE
x
is
a
C
AD
to
o
l
f
o
r
o
p
tim
izi
n
g
an
d
im
p
le
m
e
n
ti
n
g
r
ea
l
-
ti
m
e
e
m
b
ed
d
ed
s
y
s
te
m
s
(
h
ttp
://
www
.
s
y
n
d
ex
.
o
r
g
)
.
I
t
h
a
s
b
ee
n
d
esig
n
ed
an
d
d
ev
elo
p
ed
in
th
e
I
NR
I
A
P
a
r
is
-
R
o
cq
u
en
co
u
r
t Res
ea
r
c
h
C
e
n
te
r
Fra
n
ce
.
W
e
v
ar
y
t
w
o
p
ar
a
m
eter
s
:
t
h
e
n
u
m
b
er
o
f
tas
k
N=
2
0
,
4
0
,
6
0
,
8
0
,
1
0
0
,
an
d
th
e
co
m
m
u
n
i
ca
tio
n
-
to
-
co
m
p
u
tatio
n
r
atio
(
C
C
R
)
,
d
ef
in
ed
as
t
h
e
a
v
er
ag
e
co
m
m
u
n
i
ca
tio
n
ti
m
e
d
i
v
id
ed
b
y
th
e
av
er
ag
e
co
m
p
u
tatio
n
ti
m
e,
C
C
R
=0
.
1
,
1
,
1
0
.
Fo
r
ea
c
h
N,
1
0
0
g
r
ap
h
s
h
a
v
e
b
ee
n
g
e
n
er
ated
.
T
h
e
g
en
er
al
o
b
j
ec
tiv
e
o
f
o
u
r
s
i
m
u
latio
n
s
i
s
to
s
tu
d
y
t
h
e
i
m
p
ac
t
o
f
N,
P
,
a
n
d
C
C
R
o
n
r
elia
b
ilit
y
a
n
d
m
ak
e
s
p
an
i
n
tr
o
d
u
ce
d
b
y
AM
B
an
d
AR
B
.
W
e
co
m
p
ar
e
o
u
r
h
e
u
r
is
tic
s
w
i
th
th
e
h
eu
r
i
s
tic
p
r
o
p
o
s
ed
in
[
1
1
]
,
ca
lled
R
B
SA
(
R
eliab
le
B
i
-
C
r
it
er
ia
Sch
ed
u
li
n
g
A
l
g
o
r
ith
m
)
an
d
im
p
le
m
e
n
ted
in
S
y
n
DE
x
.
T
ab
le
2
s
h
o
w
s
th
e
m
a
k
esp
a
n
an
d
r
eliab
ilit
y
r
es
u
lt
s
o
f
e
x
ec
u
t
i
n
g
h
e
u
r
is
tic
s
o
n
an
Alg
co
m
p
o
s
ed
o
f
5
0
task
s
.
A
R
B
-
AM
B
*
is
t
h
e
h
eu
r
is
tics
AR
B
-
AM
B
w
it
h
o
u
t a
d
ap
tatio
n
m
o
d
u
le.
T
ab
le
2
.
Ma
k
esp
an
an
d
R
eliab
ilit
y
R
es
u
lt
s
f
o
r
N
=5
0
T
ask
s
h
e
u
r
i
s
t
i
c
s
R
B
S
A
A
R
B
-
A
M
B
*
A
RB
-
A
M
B
e
x
e
c
u
t
i
o
n
1
6
4
4
.
7
2
,
0
.
9
9
8
2
9
7
6
1
6
.
5
1
,
0
.
9
9
8
5
3
9
6
1
6
.
5
1
,
0
.
9
9
8
5
3
9
e
x
e
c
u
t
i
o
n
2
6
4
4
.
7
2
,
0
.
9
9
8
2
9
7
6
0
8
.
7
6
,
0
.
9
9
9
0
2
9
6
0
8
.
7
6
,
0
.
9
9
9
0
2
9
e
x
e
c
u
t
i
o
n
3
6
4
4
.
7
2
,
0
.
9
9
8
2
9
7
6
0
8
.
7
6
,
0
.
9
9
9
0
2
9
5
9
9
.
7
0
,
0
.
9
9
9
3
1
2
As
s
h
o
w
n
i
n
t
h
is
tab
le,
t
h
an
k
s
to
th
e
ad
ap
tatio
n
m
o
d
u
le,
A
R
B
-
AM
B
ap
p
r
o
ac
h
g
i
v
es
in
ter
esti
n
g
r
esu
lt
s
an
d
b
etter
th
a
n
R
B
S
A
an
d
AR
B
-
AM
B
*
.
Fig
u
r
es
7
A
,
7
B
,
8
A
,
8
B
,
9
A
an
d
9
B
s
h
o
w
s
m
ak
e
s
p
an
a
n
d
r
eliab
ilit
y
v
ar
iatio
n
s
.
W
e
ca
n
s
e
e
f
r
o
m
t
h
e
r
esu
lt
s
th
at
o
u
r
ap
p
r
o
ac
h
p
er
f
o
r
m
s
b
etter
th
a
n
R
B
S
A
f
o
r
all
t
h
e
d
atasets
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Bi
-
o
b
jective
S
ch
e
d
u
lin
g
w
ith
C
o
o
p
era
tin
g
Heu
r
is
tics
fo
r
E
mb
ed
d
ed
R
e
a
l
-
time
S
ystem
(
K
a
lla
Ha
mo
u
d
i
)
797
Fig
u
r
e
7A
.
I
m
p
ac
t
o
f
N
Ma
k
e
s
p
an
f
o
r
C
C
R
=1
an
d
P
=4
Fig
u
r
e
7B
.
I
m
p
ac
t
o
f
N
o
n
R
el
iab
ilit
y
f
o
r
C
C
R
=1
an
d
P
=4
Fig
u
r
e
8A
.
I
m
p
ac
t o
f
C
C
R
o
n
Ma
k
esp
a
n
f
o
r
N=
5
0
an
d
P
=
4
Fig
u
r
e
8B
.
I
m
p
ac
t o
f
C
C
R
o
n
R
eliab
ilit
y
f
o
r
N=
5
0
an
d
P
=4
Fig
u
r
e
9A
.
I
m
p
ac
t o
f
P
o
n
Ma
k
esp
an
f
o
r
N=
5
0
an
d
C
C
R
=1
Fig
u
r
e
9B
.
I
m
p
ac
t o
f
P
o
n
R
el
iab
ilit
y
f
o
r
N=
5
0
an
d
C
C
R
=1
6.
CO
NCLU
SI
O
N
W
e
h
av
e
p
r
o
p
o
s
ed
a
n
e
w
b
i
-
o
b
j
ec
tiv
e
s
ch
ed
u
lin
g
ap
p
r
o
ac
h
p
r
o
d
u
cin
g
a
u
to
m
a
ticall
y
a
s
tati
c
d
is
tr
ib
u
ted
s
c
h
ed
u
le
o
f
a
g
i
v
en
ap
p
licatio
n
A
l
g
o
n
a
g
iv
e
n
d
is
tr
ib
u
ted
ar
ch
itect
u
r
e
A
r
c.
T
h
e
aim
o
f
o
u
r
ap
p
r
o
ac
h
is
to
o
p
ti
m
ize
s
i
m
u
ltan
eo
u
s
l
y
t
w
o
an
ta
g
o
n
is
t
o
b
j
ec
tiv
es:
s
y
s
te
m
’
s
r
u
n
-
ti
m
e
(
Ma
k
e
s
p
an
)
an
d
r
eliab
ilit
y
.
O
u
r
ap
p
r
o
ac
h
is
b
a
s
ed
o
n
t
w
o
co
o
p
er
atin
g
h
e
u
r
i
s
tics
ea
c
h
o
f
t
h
e
m
d
ea
lin
g
w
i
th
a
n
o
b
j
ec
tiv
e.
T
o
allo
w
b
etter
s
p
ac
e
ex
p
lo
r
atio
n
,
w
e
i
n
teg
r
ate
a
n
ad
ap
tatio
n
m
o
d
u
le.
A
d
ap
tatio
n
is
b
ased
o
n
th
e
n
eig
h
b
o
r
h
o
o
d
co
n
ce
p
t
an
d
i
s
ac
h
iev
ed
b
y
s
o
l
u
tio
n
p
er
m
u
ta
tio
n
.
T
h
is
allo
w
s
,
in
t
h
e
ca
s
e
o
f
t
w
o
clo
s
est
co
m
p
r
o
m
i
s
e
v
al
u
es,
t
o
o
p
er
ate
o
n
th
e
d
ec
is
io
n
s
p
ac
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(
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b
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R
B
S
A
f
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r
all
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e
d
atasets
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
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2
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4752
I
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d
o
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esia
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9
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3
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Ma
r
ch
2
0
1
8
:
7
8
9
–
7
9
8
798
RE
F
E
R
E
NC
E
S
[1
]
L
.
Zh
a
n
g
,
K.
L
i,
C.
L
i,
a
n
d
K
.
L
i,
“
Bi
-
o
b
jec
ti
v
e
w
o
rk
f
lo
w
sc
h
e
d
u
l
in
g
o
f
th
e
e
n
e
rg
y
c
o
n
su
m
p
ti
o
n
a
n
d
re
l
iab
il
it
y
i
n
h
e
tero
g
e
n
e
o
u
s co
m
p
u
ti
n
g
sy
st
e
m
s,”
In
fo
rm
a
t
io
n
S
c
ien
c
e
s
,
v
o
l
.
3
7
9
,
p
p
.
2
4
1
–
2
5
6
,
2
0
1
7
.
[2
]
Y.
L
iu
,
H.
Do
n
g
,
N.
L
o
h
se
,
a
n
d
S
.
P
e
tro
v
ic,
“
A
m
u
lt
i
-
o
b
jec
ti
v
e
g
e
n
e
ti
c
a
l
g
o
rit
h
m
f
o
r
o
p
ti
m
iz
a
ti
o
n
o
f
e
n
e
rg
y
c
o
n
su
m
p
ti
o
n
a
n
d
sh
o
p
f
lo
o
r
p
r
o
d
u
c
ti
o
n
p
e
rf
o
rm
a
n
c
e
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Pro
d
u
c
ti
o
n
Ec
o
n
o
mic
s
,
v
o
l.
1
7
9
,
p
p
.
2
5
9
–
2
7
2
,
2
0
1
6
.
[3
]
S
.
K.
S
o
n
ia
S
a
b
rin
a
Be
n
d
i
b
,
H
a
m
o
u
d
i
Ka
ll
a
a
n
d
Ch
a
f
ik
A
ra
r,
“
A
t
w
o
-
ste
p
b
icriteria
sc
h
e
d
u
li
n
g
a
p
p
ro
a
c
h
f
o
r
d
istri
b
u
ted
re
a
l
t
im
e
s
y
ste
m
s,” in
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
E
lec
tro
n
ics
,
C
o
mp
u
ter
a
n
d
C
o
mp
u
ta
ti
o
n
,
2
0
1
3
.
[4
]
I.
S
.
C.
Bo
e
re
s
a
n
d
L
.
Dru
m
m
o
n
d
,
“
A
n
e
ff
icie
n
t
w
e
i
g
h
ted
b
io
b
jec
ti
v
e
sc
h
e
d
u
li
n
g
a
lg
o
rit
h
m
f
o
r
h
e
tero
g
e
n
e
o
u
s
s
y
ste
m
s,”
IEE
E
T
ra
n
sa
c
ti
o
n
s o
n
De
p
e
n
d
a
b
le a
n
d
S
e
c
u
re
Co
m
p
u
ti
n
g
,
v
o
l.
3
7
,
p
p
.
3
4
9
–
3
6
4
,
2
0
1
0
.
[5
]
E.
Je
a
n
n
o
t,
E
.
S
a
u
le,
a
n
d
D.
T
r
y
str
a
m
,
“
Bi
-
o
b
jec
ti
v
e
a
p
p
ro
x
i
m
a
ti
o
n
sc
h
e
m
e
f
o
r
m
a
k
e
sp
a
n
a
n
d
re
li
a
b
i
li
ty
o
p
ti
m
iza
ti
o
n
o
n
u
n
if
o
rm
p
a
ra
ll
e
l
m
a
c
h
in
e
s,”
in
Pro
c
e
e
d
in
g
s
o
f
t
h
e
1
4
t
h
i
n
ter
n
a
t
io
n
a
l
E
u
ro
-
P
a
r
c
o
n
fer
e
n
c
e
o
n
Pa
ra
ll
e
l
Pro
c
e
ss
in
g
,
se
r.
Eu
r
o
-
P
a
r
’0
8
.
Be
rli
n
,
He
id
e
lb
e
rg
:
S
p
rin
g
e
r
-
V
e
rlag
,
2
0
0
8
,
p
p
.
8
7
7
–
8
8
6
.
[6
]
I.
S
.
A
.
G
irau
lt
a
n
d
D.
T
r
y
stra
m
,
“
Re
li
a
b
il
it
y
v
e
rsu
s p
e
r
f
o
r
m
a
n
c
e
fo
r
c
rit
ica
l
a
p
p
li
c
a
ti
o
n
s,”
Pa
ra
ll
e
l
a
n
d
Distri
b
u
te
d
Co
mp
u
t
in
g
,
v
o
l
.
6
9
,
p
p
.
3
2
6
–
3
3
6
,
2
0
0
9
.
[7
]
X
.
Q
in
a
n
d
H.
Jia
n
g
,
“
A
n
o
v
e
l
f
a
u
lt
-
to
lera
n
t
sc
h
e
d
u
li
n
g
a
lg
o
rit
h
m
f
o
r
p
re
c
e
d
e
n
c
e
c
o
n
stra
in
e
d
tas
k
s
in
re
a
lt
i
m
e
h
e
tero
g
e
n
e
o
u
s sy
ste
m
s,
”
Pa
ra
ll
e
l
Co
mp
u
ti
n
g
,
v
o
l.
3
2
,
p
p
.
3
3
1
–
3
5
6
,
2
0
0
6
.
[8
]
J.
J.
Do
n
g
a
rra
,
E.
Je
a
n
n
o
t,
E.
S
a
u
le,
a
n
d
Z.
S
h
i
,
“
Bi
-
o
b
jec
ti
v
e
sc
h
e
d
u
li
n
g
a
l
g
o
rit
h
m
s
f
o
r
o
p
ti
m
izin
g
m
a
k
e
sp
a
n
a
n
d
re
li
a
b
il
it
y
o
n
h
e
tero
g
e
n
e
o
u
s
sy
s
tem
s,”
in
Pro
c
e
e
d
in
g
s
o
f
th
e
n
i
n
e
tee
n
th
a
n
n
u
a
l
ACM
sy
mp
o
si
u
m
o
n
P
a
ra
l
lel
a
lg
o
rith
ms
a
n
d
a
rc
h
it
e
c
tu
re
s
,
se
r.
S
P
AA
’0
7
.
Ne
w
Yo
rk
,
NY
,
USA:
A
CM
,
2
0
0
7
,
p
p
.
2
8
0
–
2
8
8
.
[9
]
S
.
H.
M
.
W
.
H.
T
o
p
c
u
o
u
g
lu
,
“
P
e
rf
o
rm
a
n
c
e
-
e
ff
e
c
ti
v
e
a
n
d
lo
w
-
c
o
m
p
lex
it
y
t
a
sk
sc
h
e
d
u
li
n
g
f
o
r
h
e
tero
g
e
n
e
o
u
s
c
o
m
p
u
ti
n
g
,
”
IEE
E
T
r
a
n
s
a
c
ti
o
n
s o
n
Pa
r
a
ll
e
l
a
n
d
Distrib
u
ted
S
y
ste
ms
,
v
o
l.
1
3
,
p
p
.
2
6
0
–
2
7
4
,
2
0
0
2
.
[1
0
]
M
.
Ha
k
e
m
a
n
d
F
.
Bu
telle,
“
Re
li
a
b
il
it
y
a
n
d
sc
h
e
d
u
li
n
g
o
n
sy
ste
m
s
su
b
jec
t
to
f
a
il
u
re
s,
”
in
Pa
ra
ll
e
l
Pro
c
e
ss
in
g
,
2
0
0
7
.
ICPP
2
0
0
7
.
I
n
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
o
n
,
2
0
0
7
,
p
p
.
3
8
–
3
8
.
[1
1
]
A
.
G
.
I.
A
ss
a
y
a
d
a
n
d
H.
Ka
ll
a
,
“
A
b
icriteria
sc
h
e
d
u
li
n
g
h
e
u
risti
c
f
o
r
d
istri
b
u
te
d
e
m
b
e
d
d
e
d
sy
ste
m
s
u
n
d
e
r
re
li
a
b
il
it
y
a
n
d
re
a
lt
im
e
c
o
n
stra
in
ts,
”
in
T
h
e
In
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
o
n
De
p
e
n
d
a
b
le
S
y
ste
ms
a
n
d
Ne
two
rk
s,
I
EE
E
Co
mp
u
ter
S
o
c
iety
,
2
0
0
4
.
[1
2
]
A
.
G
irau
lt
a
n
d
H.
Ka
ll
a
,
“
A
n
o
v
e
l
b
icriteria
sc
h
e
d
u
li
n
g
h
e
u
risti
c
s
p
ro
v
id
in
g
a
g
u
a
ra
n
tee
d
g
lo
b
a
l
s
y
ste
m
f
a
il
u
re
ra
te,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
De
p
e
n
d
a
b
le a
n
d
S
e
c
u
re
Co
m
p
u
ti
n
g
,
v
o
l.
6
,
n
o
.
4
,
p
p
.
2
4
1
–
2
5
4
,
2
0
0
9
.
[1
3
]
A
.
Do
g
a
n
a
n
d
F
.
Oz
g
u
n
e
r,
“
Bio
b
jec
ti
v
e
sc
h
e
d
u
li
n
g
a
lg
o
rit
h
m
s
f
o
r
e
x
e
c
u
ti
o
n
ti
m
e
-
re
li
a
b
il
it
y
trad
e
-
o
ff
in
h
e
tero
g
e
n
e
o
u
s co
m
p
u
ri
n
g
sy
ste
m
s,”
T
h
e
c
o
mp
u
ter
jo
u
rn
a
l
,
v
o
l
.
4
8
(3
),
p
p
.
3
0
0
–
3
1
4
,
2
0
0
5
.
[1
4
]
P
.
P
.
Ch
it
ra
,
“
Co
m
p
a
riso
n
o
f
e
v
o
l
u
ti
o
n
a
ry
c
o
m
p
u
tatio
n
a
lg
o
rit
h
m
s
f
o
r
so
lv
in
g
b
i
-
o
b
jec
ti
v
e
tas
k
s
c
h
e
d
u
li
n
g
p
ro
b
lem
o
n
h
e
tero
g
e
n
e
o
u
s
d
istri
b
u
ted
c
o
m
p
u
ti
n
g
s
y
ste
m
s,”
S
a
d
h
a
n
a
,
In
d
ia
n
Aca
d
e
my
o
f
S
c
ien
c
e
s
,
v
o
l.
3
6
,
p
.
1
6
7
U
1
8
0
,
2
0
1
1
.
[1
5
]
Y.
S
o
re
l,
“
T
h
e
a
l
g
o
rit
h
m
a
rc
h
it
e
c
tu
re
a
d
e
q
u
a
ti
o
n
m
e
th
o
d
o
l
o
g
y
,
”
in
T
h
e
M
a
ss
ive
ly
Pa
ra
ll
e
l
Co
mp
u
ti
n
g
sy
ste
ms
,
1
9
9
4
.
[1
6
]
J.
W
.
S
.
S
h
a
tz
a
n
d
M
.
G
o
to
,
“
T
a
sk
a
ll
o
c
a
ti
o
n
f
o
r
m
a
x
i
m
i
z
in
g
re
li
a
b
il
it
y
o
f
d
istri
b
u
ted
c
o
m
p
u
ter
s
y
ste
m
s,”
IEE
E
T
ra
n
s.
C
o
mp
u
ter
s
,
v
o
l.
4
1
,
p
p
.
1
5
6
–
1
6
8
,
1
9
9
2
.
[1
7
]
R.
T
.
M
a
rler
a
n
d
J.
S
.
A
ro
ra
,
“
S
u
rv
e
y
o
f
m
u
lt
io
b
jec
ti
v
e
o
p
ti
m
iza
ti
o
n
m
e
th
o
d
s
f
o
r
e
n
g
in
e
e
rin
g
,
”
S
tru
c
tu
ra
l
a
n
d
M
u
lt
id
isc
ip
l
in
a
ry
Op
ti
miza
ti
o
n
,
v
o
l.
2
6
,
p
p
.
3
6
9
–
3
Evaluation Warning : The document was created with Spire.PDF for Python.