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20
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[
1
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,
[
2
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.
At
th
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ag
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[
3
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.
T
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tag
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r
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Prio
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ts
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cr
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Evaluation Warning : The document was created with Spire.PDF for Python.
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I
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C
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,
Vo
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14
,
No
.
6
,
Dec
em
b
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r
20
24
:
6
2
7
9
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6
2
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6
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an
ce
ac
tiv
ities
to
m
in
im
ize
d
o
wn
tim
e,
r
ed
u
ce
co
s
ts
,
an
d
m
ax
im
ize
o
v
er
all
p
r
o
d
u
ctiv
ity
[
4
]
–
[
6
]
.
R
ep
r
esen
tin
g
a
s
ig
n
if
ican
t
ad
v
an
ce
m
e
n
t
in
ag
r
icu
ltu
r
al
o
p
er
atio
n
s
m
an
ag
em
e
n
t,
o
u
r
in
n
o
v
ativ
e
m
ath
em
atica
l
m
o
d
el
alig
n
s
with
th
e
s
p
ec
if
ic
r
e
q
u
ir
em
e
n
ts
a
n
d
c
o
n
s
tr
ain
ts
o
f
ag
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
s
y
s
tem
s
.
B
y
o
f
f
er
in
g
d
ec
is
io
n
-
m
ak
er
s
i
n
s
ig
h
ts
in
to
th
e
tim
in
g
a
n
d
p
r
io
r
itizatio
n
o
f
m
ain
ten
a
n
ce
ta
s
k
s
[
7
]
,
th
e
m
o
d
el
f
ac
ilit
ates
p
r
o
ac
tiv
e
in
ter
v
e
n
tio
n
s
to
p
r
ev
en
t
b
r
ea
k
d
o
wn
s
an
d
en
s
u
r
e
s
m
o
o
th
f
a
r
m
in
g
o
p
e
r
atio
n
s
.
Ultim
ately
,
th
e
m
o
d
el
aim
s
to
en
h
an
ce
th
e
ef
f
icien
cy
an
d
s
u
s
tain
ab
ilit
y
o
f
ag
r
icu
ltu
r
al
ac
tiv
ities
,
co
n
tr
ib
u
tin
g
to
th
e
b
r
o
ad
e
r
g
o
als o
f
s
u
s
tain
ab
le
f
a
r
m
in
g
an
d
f
o
o
d
s
ec
u
r
it
y
.
Desp
ite
th
e
cr
itical
r
o
le
o
f
o
p
er
atio
n
al
p
la
n
n
in
g
in
p
lan
t
m
ain
ten
an
ce
,
s
ch
o
lar
ly
liter
at
u
r
e
o
n
th
is
s
u
b
ject
r
em
ain
s
lim
ited
.
T
h
is
p
ap
er
ad
d
r
ess
es
th
is
g
ap
b
y
p
r
o
p
o
s
in
g
an
o
p
tim
izatio
n
-
b
ased
ap
p
r
o
ac
h
to
s
o
lv
in
g
p
lan
t
m
ain
ten
a
n
ce
p
lan
n
in
g
c
h
allen
g
es
th
r
o
u
g
h
th
e
d
ev
elo
p
m
e
n
t
o
f
a
co
m
p
r
eh
en
s
iv
e
p
la
n
t
m
ain
ten
an
ce
p
lan
n
in
g
m
o
d
el.
L
ev
er
ag
i
n
g
m
ix
ed
-
i
n
teg
er
n
o
n
lin
ea
r
p
r
o
g
r
am
m
in
g
(
M
I
NL
P)
tech
n
iq
u
es,
th
e
p
r
o
p
o
s
ed
m
o
d
el
o
p
tim
izes
r
eso
u
r
ce
allo
ca
tio
n
an
d
s
ch
ed
u
lin
g
f
o
r
p
la
n
t
m
ain
ten
an
ce
ac
tiv
ities
,
th
er
eb
y
en
h
an
cin
g
a
g
r
icu
ltu
r
al
p
r
o
d
u
ctiv
ity
an
d
s
u
s
tain
ab
ilit
y
.
O
u
r
m
o
d
el
p
r
o
v
id
es
a
s
tr
ateg
ic
to
o
l
f
o
r
f
ar
m
er
s
,
allo
win
g
th
em
to
m
ak
e
d
at
a
-
d
r
iv
en
d
ec
is
io
n
s
t
h
at
s
u
p
p
o
r
t
b
o
th
s
h
o
r
t
-
te
r
m
e
f
f
icie
n
cy
a
n
d
lo
n
g
-
ter
m
ag
r
icu
ltu
r
al
v
ia
b
ilit
y
.
2.
T
H
E
CO
M
P
RE
H
E
NS
I
VE
T
H
E
O
RE
T
I
CA
L
B
ASI
S
T
h
e
liter
atu
r
e
o
n
o
p
er
atio
n
a
l
p
lan
n
in
g
f
o
r
p
la
n
t
m
ain
te
n
an
ce
r
em
ai
n
s
r
elativ
ely
li
m
ited
,
with
ex
is
tin
g
s
tu
d
ies
p
r
im
ar
ily
f
o
c
u
s
in
g
o
n
p
h
y
s
io
lo
g
ical,
c
h
em
ical,
an
d
p
h
y
s
ical
asp
ec
ts
o
f
p
lan
t
g
r
o
wth
a
n
d
m
ain
ten
an
ce
.
Ho
wev
er
,
th
es
e
s
tu
d
ies
ty
p
ically
lac
k
em
p
h
asis
o
n
waste
r
e
d
u
ctio
n
o
r
co
m
p
r
eh
en
s
iv
e
o
p
er
atio
n
al
p
lan
n
in
g
an
d
s
ch
ed
u
lin
g
f
o
r
d
iv
e
r
s
e
p
lan
t
m
a
in
ten
an
ce
task
s
.
Sev
e
r
al
wo
r
k
s
h
av
e
ad
d
r
ess
ed
r
eso
u
r
ce
o
p
tim
izatio
n
in
ag
r
ic
u
ltu
r
al
co
n
te
x
ts
.
Fo
r
in
s
tan
ce
,
Gu
o
et
a
l.
[
8
]
p
r
esen
ted
a
m
ath
em
atica
l
m
o
d
el
f
o
r
o
p
tim
izin
g
wate
r
co
n
s
u
m
p
tio
n
,
wh
ile
Ad
h
am
et
a
l.
[
9
]
ex
p
lo
r
ed
th
e
u
s
e
o
f
r
ain
wate
r
to
en
h
an
ce
p
lan
t
wate
r
u
s
ag
e
ef
f
icien
cy
.
Ad
d
itio
n
ally
,
th
e
s
tu
d
ies
[
1
0
]
,
[
1
1
]
d
elv
e
d
in
to
m
o
d
elin
g
p
er
is
h
ab
le
b
io
lo
g
ica
l
co
n
d
itio
n
s
an
d
d
ec
is
io
n
-
m
a
k
in
g
r
eg
ar
d
in
g
ce
r
ea
l c
r
o
p
s
,
s
u
g
a
r
b
ee
t,
an
d
v
eg
eta
b
les,
r
esp
ec
tiv
ely
.
Fu
r
th
er
s
tu
d
ies
h
av
e
f
o
cu
s
ed
o
n
p
r
o
d
u
ctio
n
p
lan
n
in
g
an
d
o
p
tim
izatio
n
.
C
aix
eta
-
Fil
h
o
[
1
2
]
p
r
o
p
o
s
ed
a
m
o
d
el
f
o
r
s
ch
ed
u
lin
g
citr
u
s
f
r
u
its
,
wh
ile
B
is
was
an
d
Pal
[
1
3
]
d
e
v
elo
p
ed
c
r
o
p
p
la
n
n
in
g
m
o
d
els
aim
ed
at
m
in
im
izin
g
in
p
u
ts
an
d
o
p
er
a
tin
g
tim
e.
Mo
r
eo
v
er
,
o
p
er
ati
o
n
al
r
esear
ch
tech
n
iq
u
es
h
av
e
b
ee
n
u
tili
ze
d
to
o
p
tim
ize
h
ar
v
est
q
u
an
tity
a
n
d
y
ield
,
as
d
em
o
n
s
tr
ated
b
y
s
t
u
d
ies
[
1
4
]
,
[
1
5
]
.
Desp
ite
th
ese
co
n
tr
ib
u
tio
n
s
,
th
e
in
teg
r
atio
n
o
f
lean
m
a
n
u
f
ac
t
u
r
in
g
(
L
M)
p
r
in
cip
les
in
to
cr
o
p
m
ain
ten
a
n
ce
task
s
h
as
b
ee
n
lar
g
ely
o
v
e
r
lo
o
k
e
d
[
1
6
]
–
[
1
8
]
.
So
lan
o
et
a
l.
[
4
]
n
o
ted
th
e
ab
s
en
ce
o
f
to
o
ls
f
o
r
f
ar
m
m
an
a
g
em
en
t
a
k
in
to
t
h
o
s
e
u
s
ed
in
o
th
er
in
d
u
s
tr
ies,
p
r
esen
tin
g
a
n
o
p
p
o
r
tu
n
ity
to
lev
e
r
ag
e
L
M
p
r
in
cip
les f
o
r
waste
r
ed
u
ctio
n
.
Mo
r
eo
v
er
,
r
ec
en
t
s
tu
d
ies
h
a
v
e
h
ig
h
lig
h
te
d
th
e
p
o
ten
tial
o
f
c
o
m
b
in
in
g
o
p
tim
izatio
n
tech
n
i
q
u
es
with
L
M
m
eth
o
d
o
lo
g
ies
t
o
e
n
h
a
n
ce
ag
r
icu
ltu
r
al
p
r
o
ce
s
s
es.
Fo
r
ex
am
p
le,
th
e
s
tu
d
ies
[
1
9
]
,
[
2
0
]
ad
d
r
ess
ed
ch
allen
g
es
in
ag
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
s
y
s
tem
s
s
u
ch
as
r
o
ck
r
em
o
v
al
o
p
er
atio
n
s
,
p
la
n
tin
g
,
an
d
ir
r
ig
atio
n
.
Th
e
s
tu
d
ies
[
2
1
]
,
[
2
2
]
f
o
c
u
s
ed
o
n
waste
r
ed
u
ctio
n
s
tr
ateg
ies
in
h
ar
v
esti
n
g
o
p
er
atio
n
s
,
u
n
d
er
s
co
r
in
g
t
h
e
im
p
o
r
tan
ce
o
f
m
in
im
izin
g
co
s
ts
ass
o
ciate
d
with
waste.
Fu
r
th
er
m
o
r
e
,
th
er
e
h
as
b
ee
n
a
g
r
o
win
g
in
ter
est
in
a
p
p
ly
in
g
I
n
d
u
s
tr
y
4
.
0
tech
n
o
lo
g
ies
to
a
g
r
icu
ltu
r
al
p
r
o
ce
s
s
es,
with
r
esear
ch
er
s
e
x
p
lo
r
in
g
way
s
to
en
h
an
ce
ef
f
icien
cy
an
d
co
n
tr
o
l
s
y
s
tem
s
.
R
o
s
ales
et
a
l.
[
2
3
]
in
v
esti
g
ated
th
e
ap
p
licatio
n
o
f
L
ea
n
m
eth
o
d
s
in
h
o
r
ticu
lt
u
r
al
s
u
p
p
ly
ch
ai
n
s
,
wh
ile
th
e
s
tu
d
ies
[
2
4
]
,
[
2
5
]
p
r
o
p
o
s
ed
d
if
f
er
e
n
tiated
lean
im
p
lem
en
tatio
n
f
r
a
m
ewo
r
k
s
ta
ilo
r
ed
to
s
m
all
an
d
m
ed
iu
m
f
ar
m
s
.
T
h
ese
s
tu
d
ies
h
ig
h
lig
h
t
t
h
e
p
o
ten
tial
o
f
in
t
eg
r
atin
g
m
o
d
er
n
tech
n
o
lo
g
ies
an
d
m
a
n
ag
em
e
n
t
m
eth
o
d
o
l
o
g
ies
to
o
p
tim
ize
ag
r
icu
ltu
r
al
o
p
er
atio
n
s
an
d
e
n
h
an
ce
s
u
s
tain
ab
ilit
y
.
I
n
s
u
m
m
ar
y
,
wh
ile
s
ig
n
if
ican
t
p
r
o
g
r
es
s
h
as
b
ee
n
m
ad
e
in
ad
d
r
ess
in
g
v
ar
io
u
s
asp
ec
ts
o
f
ag
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
an
d
m
ain
ten
an
ce
,
th
er
e
r
em
ain
s
a
n
ee
d
f
o
r
f
u
r
t
h
er
in
teg
r
atio
n
o
f
o
p
tim
izatio
n
tec
h
n
iq
u
es,
L
M
p
r
in
cip
les,
a
n
d
a
d
v
an
ce
d
tech
n
o
lo
g
ies
t
o
ac
h
iev
e
s
u
s
tain
ab
le
a
n
d
ef
f
icien
t
ag
r
icu
ltu
r
al
s
y
s
tem
s
.
T
h
is
p
ap
er
aim
s
to
c
o
n
t
r
ib
u
te
to
th
is
ev
o
lv
in
g
f
iel
d
b
y
p
r
o
p
o
s
in
g
a
co
m
p
r
eh
e
n
s
iv
e
ap
p
r
o
ac
h
th
a
t
co
m
b
in
es
MI
NL
P
with
L
M
p
r
in
cip
les
to
o
p
tim
ize
r
eso
u
r
ce
allo
ca
tio
n
,
m
in
im
ize
co
s
ts
,
an
d
im
p
r
o
v
e
o
p
er
atio
n
al
e
f
f
icien
cy
i
n
p
lan
t
m
ain
ten
an
ce
p
la
n
n
in
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
tr
a
teg
ic
p
la
n
t m
a
in
ten
a
n
ce
p
la
n
n
in
g
in
a
g
r
icu
ltu
r
e
b
y
in
te
g
r
a
tin
g
lea
n
…
(
Ga
yu
s
S
ima
r
ma
ta
)
6281
3.
M
E
T
H
O
D
T
h
e
co
n
ce
p
tu
al
f
r
a
m
ewo
r
k
o
f
a
m
ath
em
atica
l
m
o
d
el
f
o
r
p
l
an
t
m
ain
ten
an
ce
p
lan
n
i
n
g
in
v
o
lv
es
th
e
in
teg
r
atio
n
o
f
v
ar
io
u
s
elem
en
t
s
an
d
co
n
s
tr
ain
ts
to
d
ev
elo
p
d
ec
is
io
n
v
ar
iab
les
f
o
r
m
ain
te
n
a
n
ce
o
p
er
atio
n
s
.
T
h
e
m
o
d
el
aim
s
to
o
p
tim
ize
m
ai
n
ten
an
ce
ac
tiv
ities
,
r
eso
u
r
ce
al
lo
ca
tio
n
,
an
d
s
ch
ed
u
lin
g
to
e
n
s
u
r
e
th
e
r
eliab
ilit
y
an
d
p
er
f
o
r
m
an
ce
o
f
p
lan
t
eq
u
ip
m
en
t.
T
h
e
p
r
o
p
o
s
ed
co
n
ce
p
tu
al
f
r
am
ew
o
r
k
d
r
aws
o
n
m
ath
em
atica
l
o
p
tim
izatio
n
p
r
in
cip
les
to
g
u
id
e
th
e
d
ev
elo
p
m
e
n
t
o
f
d
ec
i
s
io
n
v
ar
iab
les
an
d
co
n
s
tr
ain
t
s
f
o
r
m
ain
ten
an
ce
p
lan
n
in
g
.
Ad
d
itio
n
ally
,
th
e
in
t
eg
r
atio
n
o
f
lean
p
r
in
ci
p
les
an
d
o
p
tim
izatio
n
i
n
a
g
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
s
y
s
tem
s
o
f
f
er
s
a
co
n
ce
p
tu
al
m
o
d
el
f
o
r
th
e
co
n
s
tr
u
ctio
n
o
f
a
m
ath
e
m
atica
l
m
o
d
el,
em
p
h
asizin
g
t
h
e
n
ee
d
to
co
n
s
id
er
waste
p
r
o
d
u
cts,
s
u
s
tain
ab
ilit
y
,
an
d
ag
r
icu
ltu
r
al
o
p
er
atio
n
s
in
th
e
d
ev
elo
p
m
e
n
t
o
f
d
ec
i
s
io
n
v
ar
iab
les
an
d
o
b
jectiv
e
f
u
n
ctio
n
s
.
T
h
e
co
n
ce
p
tu
al
f
r
a
m
ewo
r
k
also
c
o
n
s
id
er
s
th
e
u
tili
za
tio
n
o
f
m
at
h
e
m
atica
l
m
o
d
els
an
d
co
m
p
u
ter
s
im
u
latio
n
s
to
s
u
p
p
o
r
t
ef
f
ec
tiv
e
r
eso
u
r
ce
allo
ca
tio
n
an
d
d
ec
is
io
n
-
m
ak
in
g
in
d
is
ea
s
e
d
y
n
am
ics,
h
ig
h
lig
h
tin
g
th
e
r
elev
a
n
ce
o
f
m
ath
em
atica
l
m
o
d
elin
g
in
in
f
o
r
m
in
g
m
ai
n
ten
an
ce
p
lan
n
in
g
d
ec
is
io
n
s
.
Ad
d
itio
n
ally
,
th
e
in
teg
r
atio
n
o
f
m
ain
ten
an
ce
an
d
p
r
o
d
u
ctio
n
p
la
n
n
in
g
in
th
e
co
n
ce
p
tu
al
f
r
am
ewo
r
k
em
p
h
asizes
th
e
d
ev
elo
p
m
en
t
o
f
a
co
s
t
-
b
ased
m
o
d
el
f
o
r
in
teg
r
ated
p
lan
n
in
g
,
e
n
s
u
r
in
g
th
at
m
ain
ten
an
ce
s
tr
ateg
ies ar
e
ef
f
ec
tiv
ely
in
co
r
p
o
r
ated
in
t
o
p
r
o
d
u
ctio
n
co
n
tr
o
l.
T
h
e
u
tili
za
tio
n
o
f
m
ix
e
d
i
n
teg
er
n
o
n
lin
ea
r
p
r
o
g
r
am
m
in
g
(
MI
NL
P)
p
r
o
v
id
es
a
p
o
wer
f
u
l
f
r
am
ewo
r
k
f
o
r
en
ca
p
s
u
latin
g
th
e
in
tr
icac
i
es o
f
p
lan
n
in
g
in
v
ar
io
u
s
d
o
m
ain
s
.
MI
NL
P h
as b
ee
n
ap
p
lied
to
ad
d
r
ess
co
m
p
le
x
s
ch
ed
u
lin
g
,
co
n
tr
o
l,
an
d
o
p
tim
izatio
n
ch
allen
g
es
in
d
iv
er
s
e
f
ield
s
,
in
clu
d
in
g
c
h
em
ical
p
r
o
ce
s
s
es,
m
an
u
f
ac
tu
r
in
g
,
en
er
g
y
,
an
d
i
n
f
r
astru
ctu
r
e
p
lan
n
in
g
.
T
h
e
i
n
teg
r
atio
n
o
f
MI
NL
P
en
a
b
les
d
ec
is
io
n
-
m
a
k
er
s
to
co
n
s
id
er
d
is
cr
ete
a
n
d
c
o
n
tin
u
o
u
s
v
a
r
iab
les,
n
o
n
lin
ea
r
r
el
atio
n
s
h
ip
s
,
an
d
in
teg
er
co
n
s
tr
ain
ts
,
o
f
f
er
i
n
g
a
co
m
p
r
eh
e
n
s
iv
e
ap
p
r
o
ac
h
t
o
ad
d
r
ess
in
g
p
lan
n
in
g
co
m
p
lex
ities
.
MI
NL
P
p
r
esen
ts
a
co
m
p
lex
o
p
tim
izatio
n
p
ar
a
d
ig
m
wh
e
r
e
in
ce
r
tain
v
ar
ia
b
les
ar
e
co
n
s
tr
ain
ed
to
ass
u
m
e
in
teg
er
v
alu
es,
wh
ile
b
o
th
t
h
e
o
b
jectiv
e
f
u
n
ctio
n
an
d
th
e
f
ea
s
ib
le
r
e
g
io
n
ar
e
d
elin
ea
ted
b
y
n
o
n
lin
ea
r
f
u
n
ctio
n
s
.
T
h
is
o
p
tim
izatio
n
tech
n
iq
u
e
f
in
d
s
ex
ten
s
iv
e
u
tili
ty
ac
r
o
s
s
v
ar
io
u
s
d
o
m
ai
n
s
,
en
co
m
p
ass
in
g
in
d
u
s
tr
ial
p
r
o
ce
s
s
es,
f
in
an
cia
l
o
p
er
atio
n
s
,
s
cien
tific
m
a
n
a
g
em
en
t,
en
g
in
ee
r
in
g
en
d
ea
v
o
r
s
,
an
d
o
p
er
atio
n
s
r
esear
ch
.
I
n
teg
er
v
ar
ia
b
les
s
er
v
e
to
m
o
d
el
lo
g
ical
r
elatio
n
s
h
ip
s
,
f
ix
ed
co
s
ts
,
p
iece
wis
e
lin
ea
r
f
u
n
ctio
n
s
,
j
o
in
t
co
n
s
tr
ain
ts
,
an
d
in
d
iv
is
ib
le
r
eso
u
r
ce
s
,
th
u
s
a
d
d
in
g
a
la
y
er
o
f
in
tr
icac
y
to
th
e
o
p
t
im
izatio
n
p
r
o
ce
s
s
.
C
o
n
cu
r
r
en
tly
,
n
o
n
lin
ea
r
f
u
n
cti
o
n
s
ar
e
in
d
is
p
en
s
ab
le
f
o
r
ac
c
u
r
ately
ca
p
tu
r
in
g
p
h
y
s
ical
p
r
o
p
er
ties
,
co
v
ar
ian
ce
,
an
d
ec
o
n
o
m
ies o
f
s
ca
le.
MI
NL
Ps
co
n
s
titu
te
a
f
o
r
m
id
a
b
le
class
o
f
o
p
tim
izatio
n
ch
all
en
g
es
o
win
g
to
t
h
e
co
n
f
lu
en
ce
o
f
in
teg
er
v
ar
iab
le
o
p
tim
izatio
n
a
n
d
n
o
n
lin
ea
r
f
u
n
ctio
n
s
o
lv
i
n
g
.
T
h
is
m
o
d
elin
g
p
a
r
ad
ig
m
is
u
b
iq
u
ito
u
s
in
o
p
tim
izatio
n
,
en
ca
p
s
u
latin
g
n
o
n
lin
ea
r
p
r
o
g
r
am
m
in
g
(
NL
P)
an
d
m
ix
e
d
-
in
t
eg
er
lin
ea
r
p
r
o
g
r
am
m
i
n
g
(
MI
L
P)
as
co
n
s
titu
en
t
s
u
b
p
r
o
b
lem
s
.
E
x
p
r
ess
in
g
MI
N
L
P su
cc
in
ctly
,
it m
ay
b
e
r
ep
r
e
s
en
ted
as (
1
)
.
Min
im
ize
(
)
with
co
n
s
tr
ain
t
(
)
≤
0
∈
∈
ℤ
,
∀
∈
(
1
)
I
n
th
e
co
n
tex
t
wh
e
r
e
:
ℝ
→
ℝ
an
d
:
→
r
ep
r
esen
t
d
o
u
b
ly
d
if
f
e
r
en
tia
b
le
co
n
tin
u
o
u
s
f
u
n
ctio
n
s
,
⊂
ℝ
d
en
o
tes
a
f
in
ite
p
o
ly
h
e
d
r
al
s
et,
an
d
⊆
{
1
,
2
,
⋯
,
}
s
ig
n
if
ies
a
s
et
co
m
p
r
is
in
g
in
d
ices
o
f
in
te
g
er
v
ar
iab
les,
it
is
e
v
id
en
t
th
at
m
a
x
im
izatio
n
,
al
o
n
g
with
m
o
r
e
g
en
er
al
co
n
s
tr
ain
ts
s
u
ch
as
s
i
m
ilar
ity
co
n
s
tr
ain
ts
,
o
r
lo
wer
an
d
u
p
p
er
b
o
u
n
d
s
≤
(
)
,
ar
e
p
er
tin
en
t c
o
n
s
id
er
atio
n
s
.
Pro
b
lem
(
1
)
em
er
g
es
as
an
NP
-
h
ar
d
c
o
m
b
in
ato
r
ial
ch
all
en
g
e,
o
win
g
to
its
in
clu
s
io
n
o
f
MI
L
P,
co
n
s
eq
u
en
tly
n
ec
ess
itatin
g
tr
av
er
s
al
th
r
o
u
g
h
a
co
n
s
id
er
ab
ly
v
ast
s
ea
r
ch
tr
ee
f
o
r
s
o
lu
t
io
n
d
eter
m
in
atio
n
.
Mo
r
eo
v
er
,
n
o
n
co
n
v
ex
in
te
g
er
o
p
tim
izatio
n
p
r
o
b
lem
s
ar
e
t
y
p
ically
d
ee
m
ed
u
n
d
ec
i
d
ab
le,
as
d
em
o
n
s
tr
ated
b
y
J
er
o
s
lo
w
[
2
6
]
.
T
h
e
au
th
o
r
p
r
o
v
id
es
in
s
tan
ce
s
o
f
q
u
ad
r
atica
lly
co
n
s
tr
ain
ed
in
teg
er
p
r
o
g
r
a
m
s
an
d
illu
s
tr
ates
th
e
in
ab
ilit
y
o
f
co
m
p
u
tatio
n
al
d
e
v
ices
to
co
m
p
u
te
s
o
lu
tio
n
s
f
o
r
all
p
r
o
b
lem
s
with
in
th
is
cla
s
s
.
R
eso
lv
in
g
p
r
o
b
lem
(
1
)
ca
n
b
e
ac
h
ie
v
ed
b
y
eith
er
e
n
s
u
r
in
g
co
n
v
ex
it
y
o
f
o
r
b
y
p
r
esu
m
in
g
co
n
v
ex
ity
o
f
th
e
p
r
o
b
lem
f
u
n
ctio
n
s
.
W
ith
in
th
e
s
co
p
e
o
f
th
is
p
ap
er
,
(
)
d
en
o
tes
th
e
iter
atio
n
o
f
,
wh
ile
=
(
(
)
)
s
ig
n
if
ies
th
e
ca
lcu
latio
n
o
f
th
e
o
b
jectiv
e
f
u
n
ctio
n
o
n
(
)
.
T
h
e
s
am
e
n
o
m
en
clatu
r
e
c
o
n
v
e
n
tio
n
is
m
ain
tain
ed
f
o
r
co
n
s
tr
ain
ts
,
g
r
ad
ien
ts
,
an
d
Hess
ian
s
co
n
ce
r
n
in
g
(
)
.
Su
b
s
cr
ip
ts
ar
e
em
p
lo
y
e
d
to
d
e
n
o
te
co
m
p
o
n
en
ts
,
wh
er
ein
r
ep
r
esen
ts
th
e
-
th
co
m
p
o
n
e
n
t
o
f
.
Fo
r
th
e
s
et
⊂
{
1
,
2
,
⋯
,
}
,
co
r
r
es
p
o
n
d
s
to
th
e
-
co
m
p
o
n
e
n
t
ass
o
ciate
d
with
,
with
d
esig
n
ated
as
an
i
n
teg
er
v
ar
iab
le.
Ad
d
itio
n
ally
,
=
{
1
,
⋯
,
}
−
an
d
d
en
o
t
e
co
n
tin
u
o
u
s
v
ar
iab
les.
T
h
e
d
i
m
en
s
io
n
s
o
f
th
e
in
teg
e
r
s
p
ac
e
ar
e
in
d
icate
d
b
y
=
|
|
.
No
tab
ly
,
th
e
f
lo
o
r
a
n
d
ce
ilin
g
o
p
er
ato
r
s
ar
e
s
y
m
b
o
liz
ed
b
y
⌊
⌋
an
d
⌈
⌉
,
r
ep
r
esen
tin
g
th
e
lar
g
est
in
teg
er
less
th
an
o
r
eq
u
al
to
an
d
th
e
s
m
allest
in
teg
er
g
r
ea
ter
th
an
o
r
eq
u
al
to
,
r
esp
ec
tiv
ely
.
Giv
en
two
m
atr
ices
o
f
s
ize
×
,
an
d
,
∘
=
∑
∑
=
1
=
1
r
ep
r
esen
ts
th
eir
in
n
er
p
r
o
d
u
c
t.
I
n
g
en
e
r
al,
th
e
p
r
esen
ce
o
f
an
in
teg
er
v
a
r
iab
le
∈
ℤ
lead
s
to
th
e
f
ea
s
ib
le
r
eg
io
n
o
f
p
r
o
b
lem
(
1
)
b
ein
g
n
o
n
-
co
n
v
ex
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
7
9
-
6
2
8
6
6282
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
4
.
1
.
M
o
dellin
g
T
h
e
p
lan
t
m
ain
ten
an
ce
p
lan
n
i
n
g
p
r
o
b
lem
ad
d
r
ess
ed
in
th
is
s
tu
d
y
en
c
o
m
p
ass
es
s
ev
er
al
k
ey
elem
en
ts
,
in
clu
d
in
g
t
h
e
ar
ea
d
esig
n
ate
d
f
o
r
m
ain
ten
a
n
ce
,
a
s
eq
u
e
n
ce
o
f
m
ain
te
n
an
ce
ac
tiv
ities
,
an
d
th
e
p
lan
n
i
n
g
h
o
r
izo
n
,
all
wh
ile
en
s
u
r
i
n
g
t
h
e
p
r
eser
v
atio
n
o
f
h
ar
v
est
q
u
ality
.
T
h
e
p
r
im
ar
y
o
b
jectiv
e
f
u
n
ctio
n
aim
s
to
m
in
im
ize
cr
o
p
m
ain
ten
an
ce
e
x
p
en
s
es
wh
ile
ef
f
ec
tiv
ely
d
is
tr
ib
u
tin
g
r
eso
u
r
ce
s
an
d
s
ch
e
d
u
li
n
g
task
s
with
in
th
e
ag
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
f
r
a
m
e
wo
r
k
.
Utilizin
g
MI
NL
P
-
b
ase
d
m
o
d
els
allo
ws
f
o
r
th
e
i
n
teg
r
atio
n
o
f
p
er
tin
e
n
t
p
ar
am
eter
s
an
d
v
ar
iab
les ess
en
tial to
th
is
p
r
o
b
lem
d
o
m
ai
n
.
T
h
e
f
o
llo
win
g
co
m
p
o
n
e
n
ts
ar
e
elu
cid
ated
h
er
ei
n
:
Ass
u
m
p
tio
n
s
:
−
T
h
e
d
esig
n
ated
l
o
t o
r
h
ec
tar
e
f
o
r
m
ain
ten
a
n
ce
is
p
r
ed
eter
m
in
ed
.
−
C
o
s
ts
a
s
s
o
ciate
d
with
cu
ltiv
ati
o
n
ac
tiv
ities
ar
e
p
r
e
-
estab
lis
h
e
d
.
−
T
h
e
d
u
r
atio
n
an
d
tem
p
o
r
al
win
d
o
w
f
o
r
task
ex
ec
u
tio
n
ar
e
well
-
d
ef
in
ed
.
−
T
h
e
r
ep
er
c
u
s
s
io
n
s
o
f
m
ain
ten
a
n
ce
task
f
ailu
r
es o
n
cr
o
p
g
r
o
wth
o
r
s
u
b
s
eq
u
en
t h
ar
v
ests
ar
e
u
n
d
er
s
to
o
d
.
Set:
:
Hec
tar
es u
n
d
er
cu
ltiv
atio
n
,
=
1
,
2
,
3
,
…
,
:
Stag
es o
f
th
e
p
r
o
ce
s
s
(
f
er
tili
za
tio
n
,
ir
r
ig
atio
n
,
an
d
wee
d
co
n
tr
o
l.)
,
=
1
,
2
,
3
,
…
,
:
Plan
n
in
g
p
er
i
o
d
s
,
=
1
,
2
,
3
,
…
,
Par
am
eter
:
: T
im
e
r
eq
u
ir
e
d
to
m
ai
n
tain
h
e
ctar
e
in
s
tag
e
: L
o
ts
o
f
lan
d
r
eq
u
ir
in
g
lab
o
r
in
p
er
io
d
C
: Co
s
t p
er
h
ec
tar
e
f
o
r
ass
ess
m
en
t w
ith
in
th
e
o
p
tim
al
tim
e
win
d
o
w
: Co
s
t p
er
h
ec
tar
e
f
o
r
ass
ess
m
en
t o
u
ts
id
e
th
e
o
p
tim
al
tim
e
w
in
d
o
w
: Wo
r
k
in
g
d
a
y
s
in
p
er
io
d
: H
o
u
r
s
p
er
cr
ew
f
o
r
la
b
o
r
t
y
p
e
: T
im
e
lo
s
t b
y
m
ac
h
i
n
er
y
i
n
s
tag
e
d
u
r
in
g
p
er
io
d
(
ir
r
ig
atio
n
s
y
s
tem
an
d
wee
d
co
n
t
r
o
l e
q
u
ip
m
en
t.)
: Co
s
t o
f
h
ir
in
g
s
o
m
e
o
n
e
f
o
r
p
r
o
ce
s
s
s
tag
e
: Co
s
t o
f
f
ir
in
g
s
o
m
eo
n
e
f
o
r
p
r
o
ce
s
s
s
tag
e
: Co
s
t p
er
u
n
t tim
e
lo
s
t d
u
e
t
o
m
ac
h
in
er
y
u
s
ed
in
p
r
o
ce
s
s
s
tag
e
Dec
is
io
n
v
ar
iab
les:
:
Qu
an
tity
o
f
h
ec
tar
e
to
b
e
m
a
n
ag
ed
d
u
r
in
g
n
o
r
m
al
p
er
i
o
d
(
with
in
th
e
o
p
tim
al
tim
e
win
d
o
w)
:
Qu
an
tity
o
f
h
ec
tar
e
to
b
e
m
a
n
ag
ed
d
u
r
in
g
n
o
r
m
al
p
er
i
o
d
(
o
u
ts
id
e
th
e
o
p
tim
al
tim
e
win
d
o
w)
:
Nu
m
b
er
o
f
av
ailab
le
em
p
lo
y
ee
s
f
o
r
s
tag
e
in
p
er
io
d
:
Nu
m
b
er
o
f
em
p
l
o
y
ee
s
to
b
e
r
ec
r
u
ited
f
o
r
s
tag
e
in
p
er
io
d
:
Nu
m
b
er
o
f
em
p
l
o
y
ee
s
to
b
e
f
ir
ed
at
s
tag
e
in
p
er
io
d
B
in
ar
y
Var
iab
les:
Ω
1
:
Var
iab
le
ac
tiv
atin
g
o
n
e
cr
ew
o
r
g
r
o
u
p
f
o
r
wo
r
k
(
co
n
s
id
er
in
g
th
at
s
h
if
ts
in
d
icate
wo
r
k
d
o
n
e
at
ea
ch
p
r
o
ce
s
s
s
tag
e)
Ω
2
:
Var
iab
le
ac
tiv
atin
g
s
h
if
t 2
f
o
r
wo
r
k
Ω
3
:
Var
iab
le
ac
tiv
atin
g
s
h
if
t 3
f
o
r
lab
o
r
Pro
b
lem
f
o
r
m
u
latio
n
:
Min
=
∑
∑
∑
(
∗
+
∗
+
∗
+
∗
+
∗
)
W
ith
co
n
s
tr
ain
ts
:
∑
∗
−
(
Ω
1
+
Ω
2
+
Ω
3
)
∗
∗
∗
+
≤
0
∀
∈
,
∀
∈
(
2
)
∑
∗
−
2
(
Ω
1
+
Ω
2
)
∗
∗
≤
0
∀
∈
,
∀
∈
(
3
)
(
Ω
1
+
Ω
2
+
Ω
3
)
=
2
∀
∈
(
4
)
(
−
1
)
+
−
=
∀
∈
,
∀
∈
(
5
)
+
=
∀
∈
,
∀
∈
(
6
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
tr
a
teg
ic
p
la
n
t m
a
in
ten
a
n
ce
p
la
n
n
in
g
in
a
g
r
icu
ltu
r
e
b
y
in
te
g
r
a
tin
g
lea
n
…
(
Ga
yu
s
S
ima
r
ma
ta
)
6283
≥
0
∀
∈
,
∀
∈
(
7
)
≥
0
∀
∈
,
∀
∈
(
8
)
C
o
n
s
tr
ain
t
(
2
)
d
elin
ea
tes
th
e
r
eq
u
ir
em
en
ts
f
o
r
tim
e
lo
s
s
.
C
o
n
s
tr
ain
t
(
3
)
d
en
o
tes
th
e
p
r
er
e
q
u
is
ites
f
o
r
co
n
d
u
ctin
g
cr
o
p
m
ain
ten
a
n
ce
wo
r
k
with
in
th
e
o
p
tim
al
tim
e
win
d
o
w.
C
o
n
s
tr
ain
t
(
4
)
elu
cid
ates
th
e
ac
tiv
atio
n
r
eq
u
ir
em
e
n
ts
f
o
r
s
h
if
ts
o
r
wo
r
k
cr
ews.
C
o
n
s
tr
ain
t
(
5
)
estab
l
is
h
es
th
e
wo
r
k
in
g
r
eq
u
ir
em
en
ts
with
in
s
p
ec
if
ied
tim
ef
r
am
es
with
av
ailab
le
em
p
lo
y
ee
s
.
C
o
n
s
tr
ain
t
(
6
)
s
p
ec
if
ies
th
e
em
p
lo
y
ee
s
n
ee
d
e
d
to
f
u
lf
ill
th
e
r
eq
u
ir
e
d
h
ec
tar
es to
b
e
ten
d
ed
.
C
o
n
s
tr
a
in
ts
(
7
)
an
d
(
8
)
in
d
icate
p
o
s
itiv
e
in
teg
er
v
ar
iab
les.
4
.
2
.
Alg
o
rit
hm
B
elo
w
is
th
e
o
u
tlin
ed
o
p
tim
iza
tio
n
alg
o
r
ith
m
.
Ass
u
m
e
th
e
f
o
l
lo
win
g
:
a.
Feasib
le
v
ec
to
r
x
s
atis
f
ies
[
B
S
N
]
x
=
b
,
l
≤
x
≤
u
.
b.
C
o
r
r
esp
o
n
d
in
g
f
u
n
ctio
n
v
alu
e
(
)
an
d
g
r
ad
ien
t v
ec
t
o
r
(
)
=
[
]
.
c.
Nu
m
b
er
o
f
s
u
p
er
b
asic
v
ar
iab
l
es,
(
0
≤
≤
−
)
.
d.
L
U
f
ac
to
r
izatio
n
o
f
th
e
×
b
asis
m
atr
ix
.
e.
f
ac
to
r
izatio
n
o
f
th
e
q
u
asi
-
N
ewto
n
ap
p
r
o
x
im
atio
n
to
th
e
×
m
atr
ix
(
No
te
th
at
,
,
an
d
ar
e
n
ev
e
r
f
u
lly
c
o
m
p
u
ted
)
.
f.
Vec
to
r
s
atis
f
y
in
g
B
T
=
g
B
.
g.
R
ed
u
ce
d
g
r
a
d
ien
t v
ec
to
r
h
=
g
s
-
S
T
.
h.
Sm
all
p
o
s
itiv
e
co
n
v
er
g
en
ce
to
ler
an
ce
s
T
OL
R
G
an
d
T
OL
DJ.
Step
1
.
(
T
est f
o
r
co
n
v
er
g
en
ce
in
t
h
e
c
u
r
r
en
t su
b
s
p
ac
e
)
.
I
f
‖
ℎ
‖
>
g
o
to
s
tep
3
.
Step
2
.
(
"PR
I
C
E
",
e.
g
.
,
E
s
tim
ate
L
ag
r
an
g
e
m
u
ltip
lier
s
,
ad
d
o
n
e
s
u
p
e
r
b
asic)
.
a.
C
alcu
late
=
−
b.
C
h
o
o
s
e
1
<
−
T
OL
DJ
(
2
>
+T
OL
DJ),
th
e
lar
g
est
elem
e
n
t
co
r
r
esp
o
n
d
in
g
to
a
v
ar
iab
le
b
elo
w
(
ab
o
v
e)
its
b
o
u
n
d
.
I
f
n
o
n
e,
s
to
p
;
n
ec
ess
ar
y
Ku
h
n
-
T
u
ck
er
co
n
d
itio
n
s
f
o
r
o
p
tim
al
s
o
lu
tio
n
m
et.
c.
if
n
o
t,
−
ch
o
o
s
e
=
1
o
r
=
2
ac
co
r
d
i
n
g
to
|
|
=
(
|
1
|
,
|
2
|
)
;
−
ad
d
as a
n
ew
co
lu
m
n
t
o
;
−
ad
d
as a
n
ew
elem
en
t to
ℎ
;
−
ad
d
co
r
r
esp
o
n
d
in
g
n
ew
co
lu
m
n
to
.
d.
in
cr
em
en
t
b
y
1
.
Step
3
.
(
C
o
m
p
u
te
s
ea
r
ch
d
ir
ec
tio
n
,
p
=
Zp
s
)
.
a.
So
lv
e
=
−
ℎ
.
b.
So
lv
e
=
−
.
c.
s
et
p
=
[
0
]
Step
4
.
(
T
est
r
atio
s
,
"CHUZR")
.
a.
Fin
d
0
,
th
e
lar
g
est v
al
u
e
o
f
f
o
r
wh
ich
+
is
f
ea
s
ib
le.
b.
If
0
p
r
o
ce
ed
to
Step
7
.
Step
5
.
(
L
in
e
Sear
ch
)
.
a.
Fin
d
,
an
ap
p
r
o
x
im
ate
*
,
wh
er
e;
(
+
∗
)
=
0
<
≤
b.
Up
d
ate
to
+
an
d
s
et
an
d
an
d
to
th
eir
v
alu
es a
t th
e
n
ew
.
Step
6
.
(
C
o
m
p
u
te
r
ed
u
ce
d
g
r
ad
ien
t,
ℎ
̄
=
).
a.
So
lv
e
=
.
b.
C
alcu
late
n
ew
r
ed
u
ce
d
g
r
ad
ie
n
t,
ℎ
̄
=
−
.
c.
Mo
d
if
y
to
r
ef
lect
s
o
m
e
r
ec
u
r
s
iv
e
v
ar
iab
le
-
m
etr
ic
ch
an
g
es
in
,
u
s
in
g
,
an
d
ch
an
g
es
in
r
ed
u
ce
d
g
r
ad
ien
t,
ℎ
̄
−
ℎ
.
d.
Set
ℎ
=
ℎ
̄
.
e.
If
<
p
r
o
ce
ed
to
s
tep
1
.
No
n
ew
co
n
s
tr
ain
ts
f
o
u
n
d
,
s
o
we
r
em
ai
n
in
th
e
c
u
r
r
en
t su
b
s
p
ac
e.
Step
7
.
(
C
h
an
g
e
b
ase
if
n
ec
ess
ar
y
; r
em
o
v
e
o
n
e
s
u
p
e
r
b
asic)
.
Her
e
<
an
d
f
o
r
s
o
m
e
(
0
<
+
)
th
e
v
ar
iab
le
co
r
r
esp
o
n
d
in
g
to
co
lu
m
n
o
f
[
B
S]
h
as r
ea
c
h
ed
o
n
e
o
f
its
b
o
u
n
d
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
2
7
9
-
6
2
8
6
6284
a.
If
b
asic v
ar
iab
le
r
ea
ch
es its
b
o
u
n
d
(
0
<
)
.
−
s
wap
-
th
an
d
-
th
co
lu
m
n
s
o
f
[
]
a
n
d
[
]
r
esp
ec
tiv
ely
,
wh
er
e
is
ch
o
s
en
to
k
ee
p
n
o
n
s
in
g
u
la
r
(
th
is
r
eq
u
ir
es a
v
ec
to
r
s
atis
f
y
i
n
g
=
);
−
m
o
d
if
y
L
,
U
,
R
an
d
to
r
ef
lec
t th
ese
ch
an
g
es in
B
;
−
ca
lcu
late
n
ew
r
ed
u
ce
d
g
r
a
d
ien
t
ℎ
=
−
;
−
p
r
o
ce
ed
t
o
(
c)
.
b.
I
f
n
o
t,
s
u
p
er
b
asic v
ar
ia
b
le
r
ea
ch
es its
b
o
u
n
d
(
<
+
)
.
Dete
r
m
in
e
=
−
.
c.
Ma
k
e
-
th
v
ar
iab
le
in
n
o
n
b
asic
at
th
e
ap
p
r
o
p
r
iate
b
o
u
n
d
,
th
u
s
;
−
r
em
o
v
e
-
th
co
lu
m
n
f
r
o
m
[
]
an
d
[
ℎ
]
−
r
etu
r
n
to
tr
ian
g
u
lar
f
o
r
m
.
d.
Dec
r
em
en
t
b
y
1
an
d
p
r
o
ce
ed
t
o
s
tep
1.
T
h
e
tab
le
s
in
c
lu
d
ed
in
th
e
p
a
p
er
p
r
o
v
id
e
e
s
s
en
t
ia
l
d
a
ta
f
o
r
u
n
d
er
s
t
an
d
in
g
th
e
o
p
t
im
i
za
ti
o
n
o
f
p
lan
t
m
ain
ten
an
c
e
p
lan
n
in
g
.
T
ab
l
e
1
l
is
t
s
th
e
n
u
m
b
er
o
f
h
e
cta
r
e
s
to
b
e
cu
lt
iv
a
ted
d
u
r
i
n
g
n
o
r
m
al
p
er
io
d
s
,
in
d
i
ca
tin
g
th
e
d
i
s
tr
i
b
u
t
io
n
o
f
l
an
d
m
an
a
g
em
en
t
t
a
s
k
s
ac
r
o
s
s
d
if
f
er
en
t
t
im
e
p
e
r
io
d
s
.
T
ab
le
2
p
r
e
s
en
t
s
th
e
v
ar
i
ab
l
e
s
,
s
h
o
win
g
th
e
q
u
an
ti
ty
o
f
h
ec
tar
es
m
an
ag
ed
o
u
t
s
i
d
e
th
e
o
p
ti
m
a
l
ti
m
e
w
in
d
o
w,
wh
ich
m
ay
in
cu
r
h
ig
h
e
r
co
s
ts
.
T
ab
le
3
d
e
ta
il
s
l
ab
o
r
al
lo
c
at
io
n
,
in
c
lu
d
i
n
g
th
e
n
u
m
b
er
o
f
lab
o
r
er
s
av
ai
lab
le,
u
ti
l
ized
,
an
d
u
n
u
s
ed
a
cr
o
s
s
d
i
f
f
er
en
t
m
a
in
ten
a
n
ce
p
er
io
d
s
.
T
h
e
s
e
t
ab
l
es
co
l
le
ct
iv
e
ly
il
lu
s
t
r
a
te
th
e
m
o
d
el
's
ef
f
ic
ien
cy
in
lan
d
u
s
e
an
d
l
ab
o
r
d
i
s
tr
ib
u
ti
o
n
,
s
u
p
p
o
r
t
in
g
th
e
g
o
a
l
o
f
m
in
i
m
i
zin
g
co
s
t
s
a
n
d
en
h
an
cin
g
p
r
o
d
u
c
tiv
ity
in
ag
r
i
cu
l
tu
r
al
o
p
er
at
io
n
s
.
T
ab
le
1
.
Nu
m
b
er
o
f
h
ec
tar
es t
o
b
e
cu
ltiv
ated
in
n
o
r
m
al
p
e
r
io
d
X
1
2
3
4
1
3
5
0
3
5
0
3
5
0
3
0
0
2
7
0
0
7
0
0
7
0
0
7
5
0
3
3
0
0
3
0
0
3
0
0
3
0
0
4
3
0
0
3
0
0
3
0
0
4
1
0
5
3
0
0
3
0
0
3
0
0
3
0
0
6
3
0
0
3
0
0
3
0
0
3
0
0
7
3
0
0
3
0
0
3
1
0
4
6
0
8
1
1
8
3
.
3
3
3
0
0
3
0
0
3
0
0
T
ab
le
2
.
Var
iab
les
XE
1
2
3
4
1
2
0
0
.
0
0
0
0
0
2
0
0
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0
0
0
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5
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5
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0
0
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T
ab
le
3
.
Nu
m
b
er
o
f
lab
o
r
s
K
A
v
a
i
l
U
sed
U
n
u
s
e
d
1
1
5
0
.
0
0
0
0
0
4
5
0
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0
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0
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0
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5.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
esen
ts
a
co
m
p
r
e
h
en
s
iv
e
m
o
d
el
f
o
r
p
lan
t
m
ai
n
ten
an
ce
p
lan
n
in
g
aim
e
d
at
m
in
im
izin
g
p
r
o
d
u
ctio
n
co
s
ts
with
in
ag
r
icu
ltu
r
al
o
p
er
atio
n
s
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
en
co
m
p
ass
es
th
e
p
lan
n
in
g
o
f
lab
o
r
r
eso
u
r
ce
s
,
s
ch
ed
u
lin
g
o
f
o
p
er
atio
n
s
,
id
en
tific
atio
n
o
f
m
ai
n
ten
an
ce
ar
ea
s
,
u
tili
za
tio
n
o
f
m
ac
h
in
er
y
,
an
d
th
e
o
v
er
ar
c
h
in
g
o
b
jectiv
e
o
f
co
s
t
m
in
im
izatio
n
f
o
r
f
ar
m
er
s
.
I
n
n
u
m
e
r
o
u
s
ag
r
icu
ltu
r
al
co
n
tex
ts
,
p
r
o
d
u
ctio
n
p
lan
n
in
g
is
o
f
ten
r
elian
t
o
n
f
ar
m
er
s
'
p
r
ac
tical
ex
p
er
tis
e
a
n
d
em
p
ir
ical
k
n
o
wled
g
e.
Ho
wev
er
,
d
esp
ite
th
e
co
llectio
n
o
f
r
elev
a
n
t
d
ata,
i
n
ad
eq
u
ate
an
aly
s
is
f
r
e
q
u
en
tl
y
r
esu
lts
in
p
lan
n
in
g
d
is
cr
ep
an
cies,
lead
in
g
to
elev
ated
o
p
e
r
atio
n
al
c
o
s
ts
ass
o
ciate
d
with
p
lan
t
m
ain
te
n
an
ce
an
d
jeo
p
ar
d
izin
g
h
a
r
v
est
q
u
ality
.
T
h
e
o
p
tim
izatio
n
m
o
d
el
in
t
r
o
d
u
ce
d
h
er
ei
n
s
er
v
es
as
a
d
ec
is
io
n
-
s
u
p
p
o
r
t
to
o
l,
o
f
f
e
r
in
g
s
y
s
te
m
atic
g
u
id
an
ce
to
m
itig
ate
p
lan
n
in
g
er
r
o
r
s
an
d
o
p
tim
ize
r
eso
u
r
ce
u
tili
za
tio
n
ef
f
ec
tiv
ely
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
tr
a
teg
ic
p
la
n
t m
a
in
ten
a
n
ce
p
la
n
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in
g
in
a
g
r
icu
ltu
r
e
b
y
in
te
g
r
a
tin
g
lea
n
…
(
Ga
yu
s
S
ima
r
ma
ta
)
6285
RE
F
E
R
E
NC
E
S
[
1
]
A
.
S
h
a
r
ma,
G
.
S
.
Y
a
d
a
v
a
,
a
n
d
S
.
G
.
D
e
s
h
m
u
k
h
,
“
A
l
i
t
e
r
a
t
u
r
e
r
e
v
i
e
w
a
n
d
f
u
t
u
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e
p
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p
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t
i
v
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n
m
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i
n
t
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n
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n
c
e
o
p
t
i
m
i
z
a
t
i
o
n
,
”
J
o
u
rn
a
l
o
f
Q
u
a
l
i
t
y
i
n
Ma
i
n
t
e
n
a
n
c
e
En
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
7
,
n
o
.
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p
p
.
5
–
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5
,
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a
r
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o
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/
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3
5
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2
.
[
2
]
T.
Te
sl
e
n
k
o
,
V
.
V
o
r
o
n
k
o
v
a
,
a
n
d
M
.
H
a
k
o
v
a
,
“
G
r
e
e
n
a
g
r
o
-
p
r
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d
u
c
t
i
o
n
a
s
a
f
a
c
t
o
r
o
f
c
o
mp
e
t
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i
v
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n
e
ss,
s
u
s
t
a
i
n
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b
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l
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t
y
,
e
f
f
i
c
i
e
n
t
a
n
d
e
c
o
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o
g
i
c
a
l
l
y
safe
a
g
r
i
c
u
l
t
u
r
e
,
”
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3
S
W
e
b
o
f
C
o
n
f
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e
s
,
v
o
l
.
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o
v
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sc
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/
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.
[
3
]
C
.
A
.
V
.
C
a
v
a
l
c
a
n
t
e
,
P
.
A
.
S
c
a
r
f
,
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.
D
o
,
a
n
d
S
.
W
u
,
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S
p
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i
a
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ss
u
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o
n
r
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l
i
a
b
i
l
i
t
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r
i
sk
a
n
d
ma
i
n
t
e
n
a
n
c
e
,
”
Pe
s
q
u
i
sa
O
p
e
r
a
c
i
o
n
a
l
,
v
o
l
.
4
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.
sp
e
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0
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s
p
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.
[
4
]
N
.
E.
C
.
S
o
l
a
n
o
,
G
.
A
.
G
.
Ll
i
n
á
s,
a
n
d
J.
R
.
M
o
n
t
o
y
a
‐
To
r
r
e
s,
“
To
w
a
r
d
s
t
h
e
i
n
t
e
g
r
a
t
i
o
n
o
f
l
e
a
n
p
r
i
n
c
i
p
l
e
s
a
n
d
o
p
t
i
mi
z
a
t
i
o
n
f
o
r
a
g
r
i
c
u
l
t
u
r
a
l
p
r
o
d
u
c
t
i
o
n
s
y
st
e
ms
:
a
c
o
n
c
e
p
t
u
a
l
r
e
v
i
e
w
p
r
o
p
o
s
i
t
i
o
n
,
”
J
o
u
r
n
a
l
o
f
t
h
e
S
c
i
e
n
c
e
o
f
F
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o
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4
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/
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sf
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.
[
5
]
Y
.
G
u
,
Z
.
Y
a
n
g
,
T.
Zh
u
,
J
.
W
a
n
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,
a
n
d
Y
.
H
a
n
,
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O
p
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i
ma
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c
i
si
o
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ma
k
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n
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m
o
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a
se
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c
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