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Dec
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2
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K
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r
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s
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C
ap
ac
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v
eh
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r
o
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g
p
r
o
b
lem
Op
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n
al
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esear
ch
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o
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te
o
p
tim
izatio
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Simu
lated
an
n
ea
lin
g
Veh
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r
o
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tin
g
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
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n
d
e
r th
e
CC B
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SA
li
c
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n
se
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C
o
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r
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p
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A
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r
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Flo
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C
ar
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en
as M
ar
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Dep
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d
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n
v
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d
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San
Ma
r
co
s
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a
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Per
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f
ca
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@
u
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s
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e
d
u
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p
e
1.
I
NT
RO
D
UCT
I
O
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n
an
in
cr
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s
in
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ly
in
ter
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o
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ted
wo
r
ld
,
wh
er
e
s
u
p
p
l
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ch
ain
s
an
d
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-
co
m
m
e
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ce
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tly
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g
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r
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te
o
p
tim
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n
h
as
b
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m
e
a
p
r
io
r
ity
f
o
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co
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p
an
ies
an
d
g
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v
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m
en
ts
.
Acc
o
r
d
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g
to
th
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r
ep
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t
[
1
]
,
in
t
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US,
e
-
co
m
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ten
s
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ticle
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UPS
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to
in
v
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r
o
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tim
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alg
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ith
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ed
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.
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Am
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r
ica,
v
eh
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r
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p
r
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VR
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also
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m
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tatio
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p
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f
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m
ally
[
2
]
,
wh
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p
r
ev
e
n
ts
th
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im
p
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en
t
atio
n
o
f
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v
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tech
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l
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la
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f
r
o
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s
y
s
tem
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
7
0
7
-
7
1
8
708
Veh
icle
r
o
u
tin
g
is
a
f
u
n
d
am
e
n
tal
ch
allen
g
e
in
lo
g
is
tics
o
p
ti
m
izatio
n
an
d
p
lan
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in
g
an
d
is
p
r
esen
t
in
a
wid
e
r
an
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o
f
i
n
d
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s
tr
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p
p
licatio
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s
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f
r
o
m
v
eh
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leet
m
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ag
em
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t
to
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ct
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s
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tio
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n
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o
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o
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all
s
u
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p
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if
ic
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n
s
tr
ain
ts
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T
h
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co
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s
tr
ain
ts
in
clu
d
e
v
e
h
icle
ca
r
r
y
in
g
ca
p
ac
ity
,
tim
e
win
d
o
ws in
wh
ich
l
o
ca
tio
n
s
ca
n
b
e
v
is
ited
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a
n
d
d
is
t
an
ce
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itatio
n
s
.
Op
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n
s
r
elate
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s
u
p
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ly
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d
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tics
ar
e
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f
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co
s
tly
.
Pro
d
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ct
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is
tr
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th
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m
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im
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o
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s
tag
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f
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s
u
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ch
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n
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as
it
in
v
o
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d
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etailer
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d
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s
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s
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wev
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s
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m
e
lar
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e
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o
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n
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f
tim
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ec
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o
m
ic
r
eso
u
r
ce
s
an
d
en
v
ir
o
n
m
en
tal
p
o
llu
ti
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n
.
T
h
er
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r
e,
th
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o
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is
m
o
d
eled
in
m
an
y
s
itu
atio
n
s
as a
VR
P
[
3
]
.
Acc
o
r
d
in
g
to
[
4
]
,
th
e
lo
ad
d
is
tr
ib
u
tio
n
o
f
a
f
leet
o
f
tr
u
ck
s
d
eliv
er
in
g
lo
ad
s
f
r
o
m
a
d
ep
o
t
to
m
u
ltip
le
d
esti
n
atio
n
s
ca
n
b
e
co
m
p
li
ca
ted
wh
en
th
er
e
ar
e
m
an
y
r
o
u
t
es
an
d
d
esti
n
atio
n
s
in
v
o
l
v
ed
.
On
e
o
f
th
e
b
ig
g
est
ch
allen
g
es
in
v
eh
icle
r
o
u
tin
g
is
th
e
co
m
p
lex
ity
o
f
th
e
p
r
o
b
le
m
b
ec
au
s
e
as
th
e
n
u
m
b
er
o
f
v
eh
icles,
d
eliv
er
ies
an
d
co
n
s
tr
ain
ts
in
cr
ea
s
es,
t
h
e
n
u
m
b
er
o
f
p
o
s
s
ib
le
r
o
u
t
es
also
in
cr
ea
s
es
ex
p
o
n
en
ti
ally
,
d
esp
ite
th
ese
ch
allen
g
es,
ef
f
ec
tiv
ely
s
o
l
v
in
g
VR
P
s
ca
n
h
av
e
a
s
ig
n
if
ican
t
im
p
ac
t
o
n
lo
g
is
tics
ef
f
icien
cy
an
d
c
o
s
t
r
ed
u
ctio
n
f
o
r
co
m
p
an
ies
th
at
r
ely
o
n
th
e
d
eliv
er
y
an
d
co
llectio
n
o
f
g
o
o
d
s
an
d
s
er
v
ices.
On
e
o
f
th
e
p
r
o
b
lem
s
ad
d
r
ess
ed
b
y
o
p
er
atio
n
s
r
esear
ch
is
th
e
VR
P,
wh
ich
is
a
k
e
y
f
u
n
cti
o
n
in
lo
g
is
tics
s
y
s
tem
s
an
d
i
n
v
o
lv
es
th
e
f
lo
w
o
f
p
r
o
d
u
cts
f
r
o
m
m
an
u
f
ac
t
u
r
in
g
p
lan
ts
o
r
d
is
tr
ib
u
tio
n
ce
n
ter
s
th
r
o
u
g
h
a
tr
an
s
p
o
r
tatio
n
n
et
wo
r
k
to
co
n
s
u
m
er
s
.
T
h
er
e
h
av
e
b
ee
n
s
ev
er
al
s
tu
d
ies
o
n
VR
P
s
in
ce
d
ec
ad
es
ag
o
,
f
ir
s
t
p
r
o
p
o
s
ed
in
r
esear
ch
in
its
class
ical
f
o
r
m
u
latio
n
[
5
]
an
d
s
in
ce
th
en
it h
as b
ee
n
a
wid
ely
s
tu
d
ied
p
r
o
b
lem
.
T
h
e
o
r
i
g
in
o
f
t
h
e
VR
P
co
m
e
s
f
r
o
m
y
ea
r
s
ag
o
a
n
d
is
in
t
r
o
d
u
ce
d
b
y
Dan
tzin
g
an
d
R
am
s
er
,
wh
o
r
ep
r
esen
ted
a
r
ea
l
ap
p
licatio
n
r
elate
d
to
th
e
d
eliv
er
y
o
f
g
aso
lin
e
to
s
er
v
ice
s
tat
io
n
s
an
d
p
r
o
p
o
s
ed
th
e
m
ath
em
atica
l
f
o
r
m
u
latio
n
to
t
h
is
p
r
o
b
lem
,
wh
ich
a
r
is
es
as
a
g
en
er
aliza
tio
n
o
f
t
h
e
class
ical
tr
av
elin
g
s
alesm
an
p
r
o
b
l
em
(
T
SP
)
in
wh
ic
h
a
s
al
esm
an
h
as
to
tr
a
v
el
to
a
s
er
ie
s
o
f
cu
s
to
m
er
s
o
n
ly
o
n
ce
,
a
n
d
th
en
r
etu
r
n
to
th
e
s
tar
tin
g
p
o
in
t.
T
h
e
VR
P
is
co
n
s
id
er
ed
as
a
p
r
o
b
lem
th
at
s
ta
r
ts
in
a
ce
n
tr
al
d
ep
o
t
o
r
war
e
h
o
u
s
e,
wh
ich
h
as
a
f
leet
o
f
v
e
h
icles th
at
m
u
s
t ser
v
e
a
s
et
o
f
cu
s
to
m
er
s
s
ca
tter
ed
i
n
a
g
eo
g
r
ap
h
ical
ar
ea
[
6
]
.
T
h
er
e
ar
e
d
if
f
e
r
en
t
alg
o
r
ith
m
s
th
at
allo
w
to
tr
av
er
s
e
th
e
g
e
n
er
ated
s
o
lu
tio
n
s
to
f
in
d
o
p
tim
a
l
s
o
lu
tio
n
s
o
r
g
et
clo
s
e
to
th
em
,
s
u
ch
as
th
e
g
e
n
etic
alg
o
r
it
h
m
(
GA
)
,
an
t
co
lo
n
y
alg
o
r
ith
m
a
n
d
h
y
b
r
id
s
ea
r
ch
alg
o
r
ith
m
.
Ho
wev
er
,
th
e
VR
P
is
a
ty
p
ic
al
n
o
n
-
d
eter
m
in
is
tic
p
o
ly
n
o
m
ial
p
r
o
b
lem
,
th
e
ex
ac
t
s
o
lu
tio
n
is
o
n
ly
p
o
s
s
ib
le
wh
en
th
e
n
u
m
b
er
o
f
d
em
a
n
d
p
o
in
ts
an
d
r
o
ad
s
ec
tio
n
s
is
s
m
all,
s
o
it
is
g
en
er
ally
d
if
f
icu
lt
to
o
b
tain
a
g
lo
b
al
o
p
tim
al
o
r
s
atis
f
ac
to
r
y
s
o
lu
tio
n
[
7
]
.
An
alter
n
ativ
e
is
th
e
s
im
u
lated
a
n
n
ea
lin
g
(
SA)
al
g
o
r
ith
m
.
T
h
is
is
a
s
to
ch
asti
c
o
p
tim
izatio
n
tech
n
iq
u
e,
i.e
.
,
th
e
s
ea
r
ch
f
o
r
th
e
o
p
tim
al
s
o
lu
tio
n
u
s
es
r
an
d
o
m
elem
en
ts
.
T
h
is
o
p
tim
izatio
n
m
eth
o
d
h
as
its
o
r
ig
in
in
s
tatis
tical
m
ec
h
an
ics
an
d
is
b
a
s
ed
o
n
m
im
ick
in
g
th
e
an
n
ea
lin
g
p
r
o
ce
s
s
u
s
ed
in
m
etallu
r
g
y
.
Acc
o
r
d
in
g
to
[
8
]
,
th
e
tim
e
-
d
ep
en
d
en
t
VR
P
(
T
DVRP
)
wit
h
f
lex
ib
le
tim
e
win
d
o
ws
a
n
d
s
to
ch
asti
c
f
ac
to
r
s
,
s
u
ch
as
v
ar
ia
b
ilit
y
in
v
eh
icle
s
p
ee
d
s
an
d
tr
av
el
tim
e
s
,
is
ad
d
r
ess
ed
.
T
o
s
o
lv
e
th
is
p
r
o
b
lem
,
th
e
au
th
o
r
s
p
r
o
p
o
s
e
a
h
y
b
r
id
alg
o
r
ith
m
(
HA)
th
at
co
m
b
in
es
th
e
s
ca
n
n
in
g
alg
o
r
ith
m
to
g
en
er
ate
in
iti
al
s
o
lu
tio
n
s
with
an
im
p
r
o
v
e
d
p
ar
ticle
s
war
m
o
p
ti
m
izatio
n
(
PS
O)
alg
o
r
ith
m
to
o
p
tim
ize
th
ese
s
o
lu
tio
n
s
.
T
h
i
s
h
y
b
r
id
ap
p
r
o
ac
h
s
ee
k
s
to
m
in
im
ize
th
e
t
o
tal
d
i
s
tr
ib
u
tio
n
co
s
t,
co
n
s
id
er
in
g
cu
s
to
m
er
tim
e
co
n
s
tr
ain
ts
an
d
u
n
ce
r
tain
ty
in
tr
af
f
ic
co
n
d
itio
n
s
.
I
n
th
e
s
tu
d
y
b
y
[
9
]
,
th
e
m
u
lti
-
d
ep
o
t
p
etr
o
l
s
tatio
n
r
ef
u
elin
g
p
r
o
b
lem
with
tim
e
win
d
o
ws
(
MPSR
PT
W
)
i
s
ad
d
r
ess
ed
,
th
ey
s
et
o
u
t
to
o
p
tim
ize
th
e
d
eliv
er
y
o
f
p
etr
o
leu
m
p
r
o
d
u
cts.
E
ac
h
d
ep
o
t
h
as
a
h
eter
o
g
en
e
o
u
s
f
leet
o
f
co
m
p
ar
tm
en
talized
t
r
u
ck
s
,
an
d
k
ey
d
ec
is
io
n
s
in
clu
d
e
r
o
u
tin
g
,
tr
u
ck
allo
ca
tio
n
,
s
ch
ed
u
le
p
lan
n
in
g
,
a
n
d
p
r
o
d
u
ct
d
is
tr
ib
u
tio
n
ac
r
o
s
s
co
m
p
ar
t
m
en
ts
.
T
h
e
p
r
o
p
o
s
ed
m
ath
em
atica
l
m
o
d
el
s
elec
ts
f
ea
s
ib
le
r
o
u
tes to
m
ax
im
ize
d
a
ily
r
ev
en
u
e
,
u
s
in
g
h
eu
r
is
tics
to
h
an
d
le
th
e
ex
ten
s
iv
e
s
et
o
f
p
o
s
s
ib
le
r
o
u
tes.
Acc
o
r
d
in
g
to
[
1
0
]
,
to
m
ee
t
th
e
d
iv
er
s
e
an
d
s
p
ec
if
ic
d
em
a
n
d
s
o
f
cu
s
to
m
er
s
,
a
v
eh
icle
s
ch
ed
u
lin
g
b
y
p
ick
u
p
a
n
d
d
eliv
er
y
m
o
d
el
h
as
b
ee
n
im
p
lem
en
ted
.
T
o
ad
d
r
ess
th
is
p
r
o
b
lem
,
a
HA
was
d
esig
n
ed
,
wh
ich
co
m
b
in
es
a
GA
with
v
ar
iab
le
n
eig
h
b
o
r
h
o
o
d
s
ea
r
ch
,
s
tag
es
th
at
in
co
r
p
o
r
ates
th
e
c
o
n
ce
p
t
o
f
tem
p
o
r
al
-
s
p
atial
d
is
tan
ce
.
T
h
e
r
esu
lts
o
f
th
e
s
tu
d
y
s
h
o
w
t
h
at
th
e
in
itial
s
o
lu
tio
n
th
at
co
n
s
id
er
s
th
e
tem
p
o
r
al
-
s
p
atial
d
is
tan
ce
o
f
f
er
s
clea
r
ad
v
an
tag
es in
ter
m
s
o
f
alg
o
r
ith
m
ef
f
icien
c
y
an
d
s
o
lu
tio
n
q
u
ality
.
T
h
e
o
b
jectiv
e
o
f
th
is
r
esear
c
h
is
to
d
esig
n
an
o
p
tim
izatio
n
m
o
d
el
b
ased
o
n
th
e
SA
alg
o
r
ith
m
,
s
p
ec
if
ically
ad
ap
ted
f
o
r
th
e
c
ap
ac
ity
ca
p
ac
itated
v
eh
icle
r
o
u
tin
g
p
r
o
b
lem
(
C
VR
P).
T
h
is
m
o
d
el
m
in
im
izes
at
th
e
s
am
e
tim
e
th
e
n
u
m
b
er
o
f
v
eh
icles
r
eq
u
ir
e
d
,
an
d
th
e
t
o
tal
d
is
tan
ce
tr
av
eled
in
th
e
d
is
tr
i
b
u
tio
n
o
f
p
r
o
d
u
cts.
T
o
ac
h
iev
e
th
is
o
b
jectiv
e,
a
n
i
n
teg
r
ated
o
b
jectiv
e
f
u
n
ctio
n
is
d
esig
n
ed
th
at
in
clu
d
es,
in
ad
d
itio
n
to
ca
lcu
latin
g
th
e
d
is
tan
ce
s
,
a
p
en
alty
f
o
r
th
e
ex
ce
s
s
iv
e
u
s
e
o
f
v
e
h
icles,
wh
ich
p
r
o
m
o
tes
th
e
ad
eq
u
ate
an
d
ef
f
icien
t
u
s
e
o
f
th
e
av
ailab
le
f
leet.
2.
RE
L
AT
E
D
WO
RK
I
n
r
esear
ch
[
1
1
]
,
a
s
o
lu
tio
n
to
th
e
two
-
d
im
e
n
s
io
n
al
C
VR
P
(
2
L
-
C
VR
P)
is
p
r
o
p
o
s
ed
b
y
d
e
v
elo
p
in
g
a
h
eu
r
is
tic
b
ased
o
n
o
p
e
n
s
p
ac
e
s
to
id
en
tif
y
t
h
e
r
o
u
te
p
a
ck
in
g
p
atter
n
s
a
n
d
an
ef
f
icien
t
d
ata
s
tr
u
ctu
r
e
(
T
r
ie)
to
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Gen
era
tio
n
o
f d
is
tr
ib
u
tio
n
r
o
u
tes w
ith
s
h
o
r
te
r
d
is
ta
n
ce
s
a
n
d
few
er v
eh
icles
…
(
F
lo
r
C
a
r
d
en
a
s
-
Ma
r
iñ
o
)
709
r
ec
o
r
d
th
e
f
ea
s
ib
ilit
y
in
f
o
r
m
a
tio
n
an
d
co
n
t
r
o
l
th
e
ef
f
o
r
t
in
v
ested
in
ea
ch
r
o
u
te.
I
n
class
1
in
s
tan
ce
s
,
it
is
o
b
s
er
v
ed
th
at
im
p
lem
e
n
tatio
n
b
y
SA
was le
s
s
ex
p
en
s
iv
e
th
an
o
th
er
m
eth
o
d
s
.
I
n
class
2
-
5
i
n
s
tan
ce
s
,
it ties
in
7
in
s
tan
ce
s
with
th
e
b
est s
o
lu
tio
n
s
an
d
f
in
d
s
b
etter
s
o
lu
tio
n
s
f
o
r
2
3
o
th
er
i
n
s
tan
ce
s
,
esp
ec
ially
in
th
e
lar
g
e
o
n
es.
I
n
r
esear
ch
[
1
2
]
,
t
h
ey
p
r
o
p
o
s
e
a
SA
alg
o
r
ith
m
f
o
r
th
e
VR
P
with
tim
e
win
d
o
ws
an
d
s
y
n
ch
r
o
n
izatio
n
co
n
s
tr
ain
ts
(
VR
PT
W
Sy
n
)
.
I
n
th
is
p
r
o
b
lem
,
ea
ch
cu
s
to
m
er
i
s
ass
o
ciate
d
w
ith
a
tim
e
win
d
o
w
th
at
r
ep
r
esen
ts
th
e
tim
e
in
ter
v
al
d
u
r
in
g
wh
ich
th
e
cu
s
to
m
er
is
av
ailab
le
to
r
ec
eiv
e
a
d
e
liv
er
y
.
I
f
th
e
v
e
h
icle
ar
r
iv
es
to
o
ea
r
ly
,
it
m
u
s
t
wait
u
n
til
th
e
o
p
en
in
g
o
f
th
e
tim
e
win
d
o
w,
b
u
t
late
a
r
r
iv
als
ar
e
n
o
t
allo
wed
.
T
h
e
v
i
s
its
as
s
o
ciate
d
with
a
p
ar
ticu
lar
cu
s
to
m
er
m
u
s
t
b
e
s
y
n
ch
r
o
n
ize
d
b
y
s
tar
tin
g
at
th
e
s
am
e
tim
e.
T
h
e
s
o
lu
tio
n
p
r
o
p
o
s
ed
in
[
5
]
,
in
tr
o
d
u
ce
s
s
ev
er
al
h
e
u
r
is
tic
m
eth
o
d
s
to
s
o
lv
e
th
e
v
eh
icle
r
o
u
tin
g
a
n
d
s
ch
e
d
u
lin
g
p
r
o
b
lem
with
tim
e
win
d
o
ws
(
VR
SP
T
W
)
.
In
[
1
3
]
,
a
n
in
n
o
v
ativ
e
alg
o
r
it
h
m
f
u
s
in
g
SA
an
d
v
a
r
iab
le
n
eig
h
b
o
r
h
o
o
d
d
escen
t
(
VND)
tech
n
iq
u
es
was
p
r
o
p
o
s
ed
to
s
o
lv
e
t
h
e
ch
allen
g
in
g
Hete
r
o
g
en
eo
u
s
Fleet
VR
P
with
m
u
ltip
le
f
o
r
war
d
/
r
ev
er
s
e
cr
o
s
s
-
d
o
c
k
s
(
HF
-
VR
PM
FR
C
D)
,
wh
ich
ad
d
r
ess
es
b
o
th
f
o
r
w
ar
d
an
d
r
ev
er
s
e
lo
g
is
tics
.
T
h
is
ap
p
r
o
ac
h
co
n
s
id
er
ed
a
wid
e
r
an
g
e
o
f
v
eh
icles
with
d
if
f
er
e
n
t
lo
ad
ca
p
ac
ities
an
d
tr
an
s
p
o
r
tatio
n
co
s
ts
,
in
ad
d
itio
n
to
m
u
l
tip
le
cr
o
s
s
-
d
o
ck
in
g
o
p
er
atio
n
s
s
p
an
n
in
g
b
o
th
th
e
d
ir
ec
t
an
d
r
ev
er
s
e
p
r
o
ce
s
s
.
T
h
e
r
esu
lts
o
b
tain
ed
b
y
t
h
i
s
alg
o
r
ith
m
d
em
o
n
s
tr
ate
its
ab
ilit
y
to
p
r
o
v
id
e
o
p
tim
al
s
o
lu
tio
n
s
in
s
m
all
-
s
ca
le
ca
s
es
an
d
s
u
p
er
i
o
r
s
o
lu
tio
n
s
co
m
p
a
r
e
d
to
th
e
GUROB
I
s
o
lv
er
in
m
o
r
e
co
m
p
lex
HF
-
VR
PMF
R
C
D
in
s
tan
ce
s
.
I
n
[
1
4
]
th
e
y
ad
d
r
ess
ed
th
e
VR
P
with
s
im
u
ltan
eo
u
s
p
ick
u
p
an
d
d
eliv
er
y
an
d
tim
e
win
d
o
ws
(
VR
PS
PDTW),
a
co
m
p
lex
v
ar
ian
t
o
f
th
e
VR
P
th
at
b
elo
n
g
s
to
th
e
class
o
f
N
P
-
h
ar
d
p
r
o
b
lem
s
,
f
o
r
wh
ich
th
ey
d
ev
elo
p
a
SA
alg
o
r
ith
m
th
at
co
m
b
in
es
lo
ca
l
s
ea
r
ch
s
tr
at
eg
ies
with
a
co
o
lin
g
p
r
o
g
r
a
m
th
at
co
n
tr
o
ls
th
e
p
r
o
b
a
b
ilit
y
o
f
ac
ce
p
tin
g
s
u
b
o
p
tim
al
s
o
lu
tio
n
s
to
escap
e
lo
ca
l
m
in
im
a
an
d
f
in
d
h
ig
h
-
q
u
ality
g
lo
b
al
s
o
lu
tio
n
s
.
T
h
e
s
o
lu
tio
n
p
r
o
p
o
s
als
o
f
[
1
5
]
an
d
[
1
6
]
ar
e
v
er
y
s
im
ilar
,
m
o
r
eo
v
er
,
b
o
th
in
v
esti
g
atio
n
s
co
n
tr
ast
th
eir
r
esu
lts
with
s
o
lu
tio
n
m
eth
o
d
s
b
ased
o
n
GA
s
.
Ob
tain
in
g
av
er
ag
e
an
d
m
ax
im
u
m
p
er
ce
n
ta
g
e
d
if
f
er
e
n
ce
s
o
f
-
0
,
2
2
%
a
n
d
1
,
6
1
%
r
esp
ec
tiv
ely
.
T
h
e
r
esu
lts
in
[
1
5
]
s
i
m
ilar
ly
f
in
d
o
p
tim
al
s
o
lu
tio
n
s
f
o
r
all
th
e
ca
s
es
ev
alu
ated
.
I
n
r
esear
ch
[
1
7
]
,
th
e
y
p
r
o
p
o
s
e
a
m
etah
eu
r
is
tic
to
s
o
lv
e
th
e
C
VR
P
b
ased
o
n
th
e
SA
alg
o
r
ith
m
.
I
n
th
is
r
esear
ch
,
th
e
cu
s
to
m
er
'
s
d
em
an
d
with
r
esp
ec
t
to
its
s
u
p
p
li
er
is
k
n
o
wn
.
Ho
wev
er
,
f
o
r
p
r
o
d
u
ct
d
eliv
er
y
,
th
e
ca
p
ac
ity
o
f
ea
c
h
v
eh
icle
m
u
s
t
b
e
co
n
s
tr
ain
ed
.
T
h
e
r
esear
ch
e
r
s
m
ain
tain
ed
th
eir
g
o
al
o
f
d
e
cr
ea
s
in
g
th
e
weig
h
t
o
n
ea
ch
p
ath
as lo
n
g
as it is p
o
s
s
ib
le
to
d
eliv
er
all
p
r
o
d
u
cts to
th
e
cu
s
to
m
er
.
Sev
er
al
s
o
lu
tio
n
s
ex
is
t
in
th
e
f
ield
o
f
v
eh
icle
r
o
u
tin
g
to
a
d
d
r
ess
d
if
f
er
en
t
v
a
r
ian
ts
o
f
t
h
e
p
r
o
b
lem
.
On
o
n
e
h
an
d
,
in
th
e
p
ap
er
[
1
8
]
,
a
s
o
lu
tio
n
f
o
r
th
e
p
er
io
d
ic
C
VR
P
(
PC
V
R
P)
is
p
r
o
p
o
s
ed
u
s
in
g
th
e
SA
alg
o
r
ith
m
im
p
lem
en
ted
in
th
e
J
u
lia
p
r
o
g
r
am
m
in
g
lan
g
u
ag
e.
T
h
is
ap
p
r
o
ac
h
o
p
tim
izes
th
e
r
o
u
tes
o
f
a
f
u
r
n
itu
r
e
p
ar
ts
m
an
u
f
ac
tu
r
in
g
c
o
m
p
a
n
y
in
T
u
r
k
ey
,
ac
h
iev
in
g
a
s
ig
n
if
ican
t
r
ed
u
ctio
n
in
th
e
d
is
tan
ce
tr
av
el
ed
an
d
th
e
n
u
m
b
er
o
f
v
eh
icles
u
s
ed
,
im
p
r
o
v
in
g
e
f
f
icien
cy
b
y
8
8
.
7
2
%
with
r
esp
ec
t
to
p
r
ev
io
u
s
s
o
lu
tio
n
s
,
alth
o
u
g
h
with
a
lo
n
g
er
co
m
p
u
tatio
n
al
tim
e.
O
n
th
e
o
t
h
er
h
an
d
,
th
e
p
ap
e
r
[
1
9
]
ad
d
r
e
s
s
es
th
e
o
p
en
VR
P
(
OVRP
)
,
in
wh
ich
v
e
h
icles
d
o
n
o
t
r
etu
r
n
to
th
e
d
ep
o
t.
T
h
e
C
lar
k
e
-
W
r
ig
h
t
(
C
W
)
h
eu
r
is
tic
alg
o
r
ith
m
is
m
o
d
if
ied
,
in
c
o
r
p
o
r
atin
g
p
r
o
ce
d
u
r
es
s
u
ch
as o
p
en
r
o
u
te
c
o
n
s
tr
u
ctio
n
an
d
p
o
s
t
-
r
o
u
te
im
p
r
o
v
em
en
t
s
th
r
o
u
g
h
in
s
er
tio
n
o
p
er
ato
r
s
an
d
s
wap
s
.
I
n
r
esear
ch
[
2
0
]
,
t
h
ey
p
r
esen
t
an
ap
p
r
o
ac
h
b
ased
o
n
a
d
u
al
GA
co
m
b
in
ed
wi
th
SA
to
s
o
l
v
e
th
e
VR
P
with
m
u
ltip
le
d
ep
o
ts
an
d
tr
af
f
ic
n
etwo
r
k
s
with
tim
e
-
v
ar
y
in
g
s
p
ee
d
s
,
tak
in
g
in
to
ac
co
u
n
t
th
e
m
in
im
izatio
n
o
f
d
is
tr
ib
u
tio
n
c
o
s
ts
an
d
ca
r
b
o
n
em
is
s
io
n
s
.
I
n
th
e
s
tu
d
y
co
n
d
u
cted
b
y
[
2
1
]
,
v
eh
icle
t
r
ajec
to
r
y
o
p
tim
izatio
n
u
s
in
g
I
o
T
tech
n
o
lo
g
y
a
n
d
GA
was
in
v
esti
g
ated
.
First,
th
e
o
p
tim
i
za
tio
n
o
f
th
e
tr
ad
itio
n
al
GA
was
p
er
f
o
r
m
ed
b
y
an
aly
zin
g
th
e
en
c
o
d
in
g
,
f
itn
es
s
f
u
n
ctio
n
,
s
elec
tio
n
,
cr
o
s
s
o
v
e
r
an
d
m
u
tatio
n
o
p
er
at
o
r
s
.
A
cr
o
s
s
o
v
er
p
r
o
b
ab
ilit
y
o
f
0
.
6
an
d
a
m
u
tatio
n
p
r
o
b
ab
il
ity
o
f
0
.
1
wer
e
estab
lis
h
ed
.
I
n
th
e
s
tu
d
y
d
escr
ib
ed
in
r
ef
er
en
ce
[
2
2
]
,
a
s
o
lu
tio
n
to
r
ed
u
ce
d
is
tr
ib
u
tio
n
co
s
ts
f
o
r
a
d
air
y
co
o
p
er
ativ
e
i
n
I
n
d
ia
b
y
a
p
p
l
y
in
g
clu
s
ter
in
g
a
n
d
ca
p
ac
itat
ed
r
o
u
tin
g
tech
n
iq
u
es
is
p
r
o
p
o
s
ed
.
Usi
n
g
th
e
k
-
m
ea
n
s
alg
o
r
ith
m
to
d
iv
id
e
d
eliv
er
y
lo
ca
t
io
n
s
in
to
clu
s
ter
s
o
f
s
im
ilar
s
ize
b
ased
o
n
p
r
o
x
im
ity
,
an
d
r
esp
ec
tin
g
m
ax
im
u
m
v
eh
icle
ca
p
ac
ities
,
th
e
clu
s
ter
s
wer
e
ass
ig
n
ed
to
lo
ca
l sto
ck
is
ts
.
In
[
2
3
]
,
th
e
p
ap
e
r
p
r
esen
ts
a
n
o
p
tim
izatio
n
alg
o
r
ith
m
f
o
r
th
e
tr
a
n
s
p
o
r
tatio
n
an
d
d
is
tr
i
b
u
tio
n
o
f
v
eg
etab
les
th
at
m
in
im
izes
th
e
co
s
t,
tr
an
s
p
o
r
tatio
n
tim
e
an
d
n
u
m
b
er
o
f
v
eh
icles
u
s
ed
,
co
n
s
id
er
in
g
co
n
s
tr
ain
ts
s
u
ch
as
v
e
h
icle
ca
p
ac
ity
an
d
s
p
ec
if
ic
tim
e
win
d
o
ws
to
m
ain
tain
th
e
f
r
esh
n
ess
o
f
th
e
p
r
o
d
u
cts.
A
h
y
b
r
id
ap
p
r
o
ac
h
is
p
r
o
p
o
s
ed
b
ased
o
n
a
GA
e
n
h
an
ce
d
with
a
SA
p
r
o
ce
s
s
,
u
s
in
g
th
e
ad
a
p
tiv
e
Me
tr
o
p
o
lis
ac
ce
p
tan
ce
cr
iter
io
n
.
B
esid
es,
in
[
2
4
]
,
t
h
ey
p
r
o
p
o
s
ed
a
n
o
v
el
ap
p
r
o
ac
h
u
s
in
g
an
n
ea
lin
g
n
eu
r
al
n
etwo
r
k
s
b
ased
o
n
L
ag
r
an
g
e
b
ar
r
ier
f
u
n
ctio
n
s
.
T
h
ese
m
eth
o
d
s
f
o
cu
s
ed
o
n
ad
d
r
ess
in
g
b
o
th
lin
ea
r
eq
u
ality
c
o
n
s
tr
ai
n
ts
u
s
in
g
th
e
L
ag
r
an
g
e
f
u
n
ctio
n
an
d
r
ea
ch
i
n
g
n
ea
r
-
g
lo
b
al
o
r
g
lo
b
al
o
p
tim
a
l so
lu
tio
n
s
u
s
in
g
th
e
b
a
r
r
ier
f
u
n
ctio
n
.
Stu
d
y
[
2
5
]
a
n
aly
ze
s
th
e
o
p
tim
izatio
n
o
f
f
is
h
in
g
v
ess
el
r
o
u
te
s
in
twen
ty
-
s
ix
f
is
h
in
g
lan
d
in
g
b
ases
to
th
e
n
atio
n
al
f
is
h
in
g
p
o
r
t
u
s
in
g
th
e
C
VR
P
m
o
d
el,
wh
ich
c
o
n
s
id
er
s
co
n
s
tr
ain
ts
s
u
ch
as
d
is
tan
ce
,
n
u
m
b
e
r
o
f
v
ess
els,
ca
p
ac
ity
,
ca
tch
es,
tr
av
el
tim
e
an
d
o
p
er
atio
n
al
co
s
ts
.
G
u
id
ed
lo
ca
l
s
ea
r
ch
(
GL
S)
an
d
SA
m
eth
o
d
s
with
Go
o
g
le
OR
-
T
o
o
ls
wer
e
u
s
ed
,
p
r
o
v
in
g
to
b
e
e
f
f
icien
t
in
h
eu
r
is
tic
p
r
o
b
lem
s
.
T
h
e
r
esu
lts
s
h
o
wed
th
at,
f
o
r
two
an
d
th
r
ee
s
h
ip
s
,
b
o
th
m
eth
o
d
s
g
en
er
ated
s
im
ilar
r
esu
lts
(
2
9
0
an
d
3
5
5
m
iles
)
,
b
u
t
with
f
o
u
r
s
h
ip
s
,
SA
was
m
o
r
e
ef
f
icien
t
(
4
3
9
m
iles
v
er
s
u
s
4
6
4
f
o
r
GL
S).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
7
0
7
-
7
1
8
710
3.
G
E
NE
R
AT
I
O
N
O
F
DIS
T
RIB
U
T
I
O
N
RO
U
T
E
S
WI
T
H
F
E
WE
R
VE
H
I
C
L
E
S
USI
NG
T
H
E
SI
M
UL
A
T
E
D
ANN
E
A
L
I
N
G
AL
G
O
RIT
H
M
T
h
is
s
tu
d
y
f
o
cu
s
es o
n
th
e
s
o
lu
tio
n
o
f
th
e
C
VR
P
s
,
wh
ich
i
s
a
v
ar
ian
t o
f
VR
P,
th
r
o
u
g
h
a
m
et
ah
eu
r
is
tic
ap
p
r
o
ac
h
(
SA)
.
Fo
r
th
is
p
u
r
p
o
s
e,
we
p
r
o
p
o
s
e
a
m
eth
o
d
o
lo
g
y
co
n
s
is
tin
g
o
f
f
iv
e
s
tag
es:
d
ata
co
llectio
n
an
d
o
r
g
an
izatio
n
,
g
en
er
atio
n
o
f
a
n
in
itial
s
o
lu
tio
n
u
s
in
g
th
e
G
r
ee
d
y
alg
o
r
ith
m
,
m
o
d
el
d
ef
i
n
itio
n
,
s
ea
r
ch
f
o
r
th
e
o
p
tim
al
s
o
lu
tio
n
th
r
o
u
g
h
SA
u
s
in
g
n
eig
h
b
o
r
h
o
o
d
o
p
er
ato
r
s
(
s
wap
p
in
g
,
in
s
er
tio
n
a
n
d
in
v
er
s
io
n
)
to
ex
p
lo
r
e
th
e
s
o
lu
tio
n
s
p
ac
e,
an
d
an
aly
s
is
o
f
th
e
r
esu
lts
.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
in
teg
r
a
tes
two
m
ain
co
m
p
o
n
en
ts
:
tr
a
v
el
d
is
tan
ce
an
d
a
p
en
alty
f
o
r
ex
ce
s
s
iv
e
tr
u
ck
u
s
e,
p
r
o
m
o
tin
g
alter
n
ati
v
es
th
at
m
in
im
ize
b
o
th
f
ac
to
r
s
s
im
u
ltan
eo
u
s
ly
.
T
h
e
SA
alg
o
r
ith
m
d
y
n
am
ically
ad
ju
s
ts
th
e
tem
p
er
atu
r
e
an
d
s
ea
r
ch
in
ten
s
ity
,
p
r
o
m
o
tin
g
a
b
alan
ce
d
tr
an
s
itio
n
b
etwe
en
ex
p
lo
r
atio
n
an
d
ex
p
lo
itatio
n
,
th
u
s
p
r
ev
e
n
tin
g
p
r
em
atu
r
e
co
n
v
er
g
en
ce
.
A.
Data
co
llectio
n
an
d
o
r
g
an
izati
o
n
Stan
d
ar
d
ized
ex
am
p
les
f
r
o
m
th
e
C
VR
P
L
ib
r
ar
y
(
C
VR
PLI
B
)
,
a
wid
ely
u
s
ed
v
eh
icle
r
o
u
tin
g
d
atab
ase
av
ailab
le
at
h
ttp
://v
r
p
.
g
al
g
o
s
.
in
f
.
p
u
c
-
r
io
.
b
r
/in
d
e
x
.
p
h
p
/en
/
wer
e
u
s
ed
.
T
h
e
in
s
tan
ce
s
ch
o
s
en
in
clu
d
e
th
e
co
o
r
d
in
ates
o
f
ea
ch
cu
s
to
m
e
r
,
th
e
co
r
r
esp
o
n
d
i
n
g
d
em
a
n
d
s
an
d
th
e
m
ax
im
u
m
v
eh
icle
ca
p
a
city
.
T
h
e
d
ata
wer
e
u
s
ed
i
n.
v
r
p
f
o
r
m
at
o
b
tain
ed
f
r
o
m
b
o
t
h
o
n
lin
e
r
eso
u
r
ce
s
an
d
lo
ca
l f
iles
th
at
h
ad
b
ee
n
p
r
e
v
i
o
u
s
ly
d
o
wn
l
o
ad
ed
.
T
ab
le
1
s
h
o
ws
th
e
i
n
itial
d
at
a
with
in
th
e
d
ataset
th
e
d
ata
s
et
co
llected
f
r
o
m
C
VR
PLI
B
,
th
e
f
ir
s
t
co
lu
m
n
is
th
e
n
am
e
o
f
th
e
d
at
a
s
et
A,
B
,
C
,
E
,
X,
th
e
s
ec
o
n
d
co
lu
m
n
is
“k
”
th
e
s
o
lu
ti
o
n
with
5
v
eh
icles,
th
e
th
ir
d
co
lu
m
n
is
“N°
v
er
tices
”
is
th
e
n
u
m
b
er
o
f
p
o
in
ts
o
r
n
u
m
b
er
s
o
f
cu
s
to
m
er
s
to
d
is
tr
ib
u
te,
th
e
f
o
u
r
t
h
co
lu
m
n
is
“Q”
is
th
e
ca
r
r
y
in
g
ca
p
ac
ity
o
f
t
h
e
v
eh
icle,
t
h
e
last
co
lu
m
n
“Distan
ce
”
is
th
e
co
s
t
d
is
t
an
ce
tr
av
eled
b
y
th
e
v
eh
icles in
th
e
d
is
tr
ib
u
t
io
n
.
T
ab
le
1
.
C
VR
PLI
B
d
ata
s
et
co
llected
D
a
t
a
s
e
t
k
N
°
o
f
v
e
r
t
i
c
e
s
Q
D
i
st
a
n
c
e
A
-
n
3
2
-
k5
5
32
1
0
0
7
8
4
B
-
n
3
1
-
k5
5
31
1
0
0
6
7
2
E
-
n
1
0
1
-
k14
14
1
0
1
1
1
2
1
,
0
7
1
X
-
n
1
0
1
-
k
2
5
25
1
0
1
2
0
6
27
,
591
B.
Gen
er
atio
n
o
f
th
e
in
itial so
lu
ti
o
n
T
h
e
in
itial
s
o
lu
tio
n
is
g
en
er
ated
u
s
in
g
th
e
Gr
ee
d
y
alg
o
r
ith
m
,
wh
ich
cr
ea
tes
s
eq
u
en
tial
r
o
u
tes
ch
o
o
s
in
g
at
ea
c
h
s
tag
e
th
e
c
u
s
to
m
er
clo
s
est
to
th
e
last
v
is
ited
n
o
d
e,
as
lo
n
g
as
th
e
r
em
ain
i
n
g
v
e
h
icle
ca
p
ac
ity
allo
ws
it.
T
h
is
p
r
o
ce
s
s
is
r
ep
e
at
ed
u
n
til
all
clien
t
n
o
d
es
h
a
v
e
b
ee
n
ass
ig
n
ed
to
s
o
m
e
r
o
u
te
,
lo
ca
lly
o
p
tim
izin
g
th
e
d
is
tan
ce
an
d
c
o
m
p
ly
in
g
wi
th
ca
p
ac
ity
co
n
s
tr
ain
ts
:
−
I
t star
ts
at
d
ep
o
t (
Ver
tex
0
)
−
T
h
e
n
o
d
e
clo
s
est to
th
e
v
is
ited
n
o
d
e
is
s
elec
ted
to
b
e
ad
d
e
d
t
o
th
e
r
o
u
te.
−
C
h
ec
k
if
th
e
s
u
m
o
f
c
u
s
to
m
er
d
em
an
d
s
o
n
th
e
r
o
u
te
ex
ce
ed
s
th
e
v
eh
icle
ca
p
ac
ity
(
Q)
,
s
tar
t
a
n
ew
r
o
u
te
f
r
o
m
th
e
d
ep
o
t.
−
R
ep
ea
t th
is
p
r
o
ce
s
s
u
n
til th
e
lo
ad
lim
it p
er
tr
u
ck
is
r
ea
ch
e
d
.
−
T
er
m
in
ate
wh
en
all
c
u
s
to
m
er
s
h
av
e
b
ee
n
v
is
ited
an
d
r
o
u
tes h
av
e
b
ee
n
ass
ig
n
ed
.
W
ith
th
e
r
esu
lt
o
f
th
e
in
itial
s
o
lu
tio
n
o
f
th
e
Gr
ee
d
y
alg
o
r
ith
m
th
e
SA
m
o
d
el
is
d
e
f
in
ed
th
is
to
o
p
tim
ize
an
d
im
p
r
o
v
e
th
e
q
u
al
ity
o
f
th
e
s
o
lu
tio
n
s
.
C.
Def
in
itio
n
o
f
t
h
e
SA m
o
d
el
T
h
e
p
r
o
b
lem
is
m
ath
em
atica
l
ly
m
o
d
eled
b
y
m
ea
n
s
o
f
c
o
m
p
lete
d
ir
ec
ted
g
r
a
p
h
s
G=
(
V,
A)
,
wh
er
e
ea
ch
v
er
tex
r
ep
r
esen
ts
cu
s
to
m
er
s
with
ass
o
ciate
d
d
em
an
d
an
d
ed
g
es
wh
o
s
e
weig
h
t
i
s
ca
lcu
lated
b
y
th
e
E
u
clid
ea
n
d
is
tan
ce
b
etwe
en
two
v
er
tices.
T
h
er
e
is
a
s
in
g
le
d
ep
o
t,
r
ep
r
esen
ted
b
y
v
er
tex
0
,
f
r
o
m
wh
er
e
v
eh
icles
d
ep
a
r
t
an
d
r
etu
r
n
af
ter
co
m
p
letin
g
th
eir
r
o
u
tes.
E
a
c
h
v
er
te
x
h
as
a
p
o
s
itio
n
in
a
two
-
d
im
en
s
io
n
al
p
lan
e,
d
ef
in
ed
b
y
its
X
a
n
d
Y
co
o
r
d
in
ates.
Fig
u
r
e
1
s
h
o
ws
th
e
g
r
a
p
h
ica
l
r
ep
r
esen
tatio
n
o
f
th
e
VR
P
m
o
d
el,
th
e
n
o
d
es
lab
eled
“N
o
d
e
with
d
em
an
d
”
r
ep
r
esen
t
th
e
cu
s
to
m
er
s
(
A,
B
,
C
,
D,
E
,
F,
G)
,
wh
ile
th
e
d
e
p
o
t
(
b
la
ck
s
q
u
a
r
e)
is
in
th
e
ce
n
ter
,
id
en
tifie
d
with
th
e
n
u
m
b
e
r
0
.
W
h
er
e
,
−
Veh
icle
1
: Ser
v
es n
o
d
es A,
B
,
C
an
d
r
etu
r
n
to
its
p
o
s
itio
n
,
−
Veh
icle
2
: Ser
v
es n
o
d
es D,
E
.
−
Veh
icle
3
: Ser
v
es n
o
d
es F,
G.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Gen
era
tio
n
o
f d
is
tr
ib
u
tio
n
r
o
u
tes w
ith
s
h
o
r
te
r
d
is
ta
n
ce
s
a
n
d
few
er v
eh
icles
…
(
F
lo
r
C
a
r
d
en
a
s
-
Ma
r
iñ
o
)
711
Fig
u
r
e
1
.
Gr
a
p
h
ical
r
ep
r
esen
tatio
n
o
f
th
e
VR
P m
o
d
el
E
ac
h
v
er
te
x
is
lo
ca
ted
in
a
t
wo
-
d
im
en
s
io
n
al
E
u
clid
ea
n
s
p
ac
e,
an
d
t
h
e
ed
g
e
weig
h
ts
r
e
p
r
esen
t
th
e
E
u
clid
ea
n
d
is
tan
ce
b
etwe
en
p
air
s
o
f
n
o
d
es.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
to
b
e
m
in
im
ize
d
co
n
s
is
ts
o
f
two
elem
en
ts
:
th
e
to
tal
d
is
tan
ce
tr
av
eled
o
n
all
v
eh
icle
r
o
u
tes
an
d
a
p
en
alt
y
cr
iter
io
n
p
r
o
p
o
r
tio
n
al
to
t
h
e
n
u
m
b
er
o
f
v
e
h
icles
em
p
lo
y
ed
.
T
h
is
d
u
al
-
o
b
jecti
v
e
f
o
r
m
u
latio
n
p
r
o
m
o
tes
s
o
lu
tio
n
s
th
at
m
ax
im
ize
b
o
th
lo
g
is
tical
ef
f
icien
cy
(
s
h
o
r
test
d
is
tan
ce
tr
a
v
eled
)
an
d
f
leet
u
tili
za
tio
n
(
f
ewe
s
t
n
u
m
b
er
o
f
v
eh
icles),
e
f
f
ec
tiv
ely
p
en
al
izin
g
s
o
lu
tio
n
s
th
at
in
v
o
lv
e
e
x
ce
s
s
iv
e
v
eh
icle
u
s
ag
e.
D.
Op
tim
al
So
lu
tio
n
Sear
ch
T
h
e
SA
is
a
m
etah
eu
r
is
tic
o
p
tim
izatio
n
alg
o
r
ith
m
th
at
allo
ws
to
ex
p
lo
r
e
th
e
s
o
lu
tio
n
s
p
ac
e
to
f
i
n
d
th
e
o
p
tim
al
s
o
lu
tio
n
,
it
is
also
ab
le
to
ac
ce
p
t
wo
r
s
en
in
g
m
o
v
es
ac
co
r
d
in
g
to
a
ce
r
tain
p
r
o
b
ab
ilit
y
d
ef
in
ed
b
y
th
e
co
n
tr
o
l
v
ar
iab
les,
wh
er
e
t
h
e
p
r
o
b
a
b
ilit
y
o
f
ac
ce
p
tin
g
w
o
r
s
en
in
g
m
o
v
es
will
d
ep
en
d
o
n
h
o
w
b
ad
th
e
n
ew
s
o
lu
tio
n
is
co
m
p
ar
ed
to
th
e
c
u
r
r
en
t
s
o
lu
tio
n
.
T
h
e
g
r
ea
ter
th
e
d
if
f
er
e
n
ce
,
th
e
m
o
r
e
d
if
f
icu
lt
it
will
b
e
to
ac
ce
p
t
s
u
ch
a
m
o
v
e.
T
h
e
p
r
o
b
ab
ilit
y
o
f
ac
ce
p
tan
ce
will
d
ep
en
d
m
a
in
ly
o
n
a
co
n
tr
o
l
v
ar
ia
b
le
T
(
t
em
p
er
atu
r
e)
,
wh
ich
d
ec
r
ea
s
es
in
ea
ch
iter
atio
n
,
w
h
en
T
is
h
i
g
h
an
d
m
o
r
e
wo
r
s
en
in
g
m
o
v
es
ar
e
ac
ce
p
ted
th
e
s
o
lu
tio
n
in
d
icate
s
th
at
m
o
r
e
ex
p
l
o
r
atio
n
o
f
th
e
s
ea
r
ch
s
p
ac
e
is
allo
w
e
d
to
b
e
p
er
f
o
r
m
e
d
.
On
th
e
o
th
er
h
an
d
,
as
T
d
ec
r
ea
s
es,
th
e
am
o
u
n
t
o
f
ac
ce
p
tan
ce
o
f
m
o
v
es
th
at
wo
r
s
en
t
h
e
s
o
lu
tio
n
also
d
ec
r
ea
s
es,
th
e
n
th
e
s
o
lu
tio
n
is
co
n
ce
n
tr
ated
in
a
ce
r
tain
lo
ca
tio
n
.
T
h
is
r
esear
ch
im
p
lem
en
ts
th
e
SA
alg
o
r
ith
m
ad
ap
ted
an
d
ap
p
lied
to
th
e
p
r
o
b
lem
o
f
r
o
u
te
g
en
er
atio
n
f
o
r
v
eh
icles
with
lim
ited
ca
p
ac
ity
,
wh
ich
ex
p
l
o
r
es
th
e
s
et
o
f
s
o
lu
tio
n
s
th
r
o
u
g
h
m
o
d
i
f
icatio
n
s
b
ased
o
n
p
r
o
x
im
ity
o
p
er
at
o
r
s
: n
o
d
e
ex
c
h
an
g
e,
r
elo
ca
tio
n
a
n
d
s
eq
u
e
n
c
e
r
ev
er
s
al.
−
E
x
ch
an
g
e
(
2
elem
en
ts
)
:
“On
e
-
to
-
o
n
e
ex
ch
an
g
e”
.
T
h
is
tr
a
n
s
f
o
r
m
atio
n
m
ad
e
it
p
o
s
s
ib
le
to
ex
ch
an
g
e
th
e
p
o
s
itio
n
o
f
two
clien
ts
with
in
th
e
s
o
lu
tio
n
.
T
h
e
two
clien
ts
ar
e
ch
o
s
en
r
an
d
o
m
ly
an
d
ca
n
b
elo
n
g
to
th
e
s
am
e
r
o
u
te
o
r
to
d
if
f
er
en
t
r
o
u
tes.
I
f
o
n
e
o
f
th
e
s
elec
ted
clien
ts
i
s
a
d
ep
o
t,
a
s
p
ec
ial
p
r
o
ce
d
u
r
e
is
p
er
f
o
r
m
ed
to
e
n
s
u
r
e
th
at
th
e
s
o
lu
tio
n
r
em
ai
n
s
v
alid
.
−
R
elo
ca
te
(
1
elem
en
t)
:
“De
lete
an
d
I
n
s
er
t”.
I
n
t
h
is
tech
n
iq
u
e
,
a
cu
s
to
m
er
is
r
an
d
o
m
ly
s
elec
ted
f
r
o
m
th
e
s
eq
u
en
ce
an
d
in
s
er
ted
in
to
a
n
o
th
er
p
o
s
itio
n
.
T
h
e
r
el
o
ca
tio
n
ca
n
o
cc
u
r
with
in
th
e
s
am
e
r
o
u
te
o
r
b
etwe
en
d
if
f
er
en
t
r
o
u
tes,
d
ep
en
d
in
g
o
n
th
e
s
tr
u
ctu
r
e
o
f
th
e
s
o
lu
tio
n
.
I
f
th
e
r
ea
s
s
ig
n
ed
cu
s
to
m
er
i
s
a
d
ep
o
t,
two
r
o
u
tes
ar
e
co
m
b
i
n
ed
a
n
d
at
th
e
s
am
e
tim
e,
a
n
o
th
er
r
o
u
te
is
s
p
lit
in
two
t
o
p
r
eser
v
e
t
h
e
co
n
s
is
ten
cy
o
f
th
e
s
o
lu
tio
n
.
−
I
n
v
er
t
s
eq
u
e
n
ce
:
“Par
tial
r
ev
er
s
al”.
I
n
th
is
tr
an
s
f
o
r
m
atio
n
,
g
iv
en
two
r
e
f
er
en
ce
p
o
in
ts
(
i,
j
)
,
th
e
s
u
b
s
tr
in
g
b
etwe
en
th
em
is
ex
tr
ac
te
d
a
n
d
r
ein
s
er
ted
in
th
e
s
am
e
p
o
s
itio
n
,
b
u
t
i
n
an
in
v
er
ted
m
an
n
e
r
(
j,
i)
.
As
in
o
th
er
tr
a
n
s
f
o
r
m
atio
n
s
,
th
is
tech
n
iq
u
e
ca
n
b
e
ap
p
lied
b
o
th
wi
th
in
a
p
at
h
an
d
b
etwe
en
d
if
f
e
r
en
t
p
ath
s
.
As
a
r
esu
lt,
a
s
o
lu
tio
n
d
i
f
f
er
en
t
f
r
o
m
th
e
o
r
ig
in
al
o
n
e
is
g
en
er
at
ed
.
E
ac
h
n
eig
h
b
o
r
in
g
s
o
lu
tio
n
is
ev
alu
ated
o
n
th
e
b
asis
o
f
its
t
o
tal
co
s
t
(
d
is
tan
ce
c
o
v
er
ed
)
.
I
f
th
e
n
ew
s
o
lu
tio
n
h
as
a
lo
wer
co
s
t,
it
i
s
co
n
s
id
er
ed
as
th
e
n
ew
c
u
r
r
e
n
t
s
o
lu
tio
n
.
Oth
er
wis
e,
it
ca
n
b
e
ac
ce
p
ted
with
a
ce
r
tain
p
r
o
b
ab
ilit
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d
ep
e
n
d
in
g
o
n
th
e
d
if
f
er
en
ce
in
c
o
s
t
an
d
cu
r
r
en
t
tem
p
e
r
atu
r
e,
wh
ic
h
allo
ws
it
to
leav
e
th
e
o
p
tim
al
lo
ca
tio
n
.
T
h
is
iter
ativ
e
p
r
o
ce
s
s
is
p
er
f
o
r
m
ed
with
a
ce
r
tain
n
u
m
b
er
o
f
c
y
cles
o
r
u
n
til
th
e
te
m
p
er
at
u
r
e
r
ea
ch
es th
e
th
r
esh
o
l
d
.
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e
p
r
o
p
o
s
e
th
e
f
lo
wch
ar
t
u
s
i
n
g
th
e
SA
alg
o
r
ith
m
ap
p
lied
to
th
e
p
r
o
b
lem
o
f
g
en
e
r
atin
g
r
o
u
tes
f
o
r
v
eh
icles with
lim
ited
ca
p
ac
ity
in
Fig
u
r
e
2
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I
SS
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&
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r
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m
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ic
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v
al
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a
te
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f
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f
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)
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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n
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lec
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n
g
&
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m
p
Sci
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N:
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4
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f d
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(
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lo
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s
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tab
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ates th
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o
lu
tio
n
,
Gr
ee
d
y
s
o
lu
tio
n
an
d
s
o
lu
tio
n
af
ter
SA)
h
el
p
s
to
h
av
e
a
c
o
m
p
ar
ativ
e
v
is
u
al
an
aly
s
is
.
T
h
e
iter
atio
n
s
in
wh
ich
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
ts
o
cc
u
r
a
r
e
also
r
ec
o
r
d
ed
an
d
a
s
en
s
itiv
ity
a
n
aly
s
is
is
p
er
f
o
r
m
ed
ag
ain
s
t
ch
an
g
es
in
in
itial
tem
p
er
atu
r
e,
c
o
o
lin
g
r
ate
an
d
n
eig
h
b
o
r
h
o
o
d
s
ize.
T
h
is
ex
ten
d
ed
v
alid
atio
n
en
s
u
r
es
th
at
o
p
tim
al
o
r
v
er
y
clo
s
e
to
o
p
tim
al
s
o
lu
tio
n
s
ar
e
o
b
tain
ed
,
wh
ich
ar
e
r
o
b
u
s
t a
n
d
c
o
n
s
is
ten
t.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
p
r
o
v
id
es
a
r
o
b
u
s
t
ap
p
r
o
ac
h
th
at
allo
w
s
d
ec
is
io
n
m
ak
er
s
to
lo
wer
o
p
er
atio
n
al
co
s
ts
an
d
ev
alu
ate
th
e
im
p
ac
t
o
f
ea
ch
v
ar
iatio
n
in
th
e
n
u
m
b
e
r
o
f
v
e
h
icles a
n
d
r
o
u
te
ef
f
ec
tiv
en
ess
.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
o
p
er
f
o
r
m
th
e
test
an
d
v
alid
a
tio
n
o
f
th
e
p
r
o
p
o
s
al
we
h
av
e
u
s
ed
4
d
atasets
o
f
th
e
C
VR
PLI
B
wh
ich
is
v
is
ib
le
at
h
ttp
://v
r
p
.
g
alg
o
s
.
in
f
.
p
u
c
-
r
io
.
b
r
/in
d
e
x
.
p
h
p
/en
/
.
I
n
th
e
ex
p
er
im
en
t
we
h
av
e
u
s
ed
4
d
atasets
A,
B
,
E
,
X
s
ee
T
ab
le
1
.
T
h
e
r
esu
lts
o
b
tain
ed
f
r
o
m
th
e
im
p
lem
en
tat
io
n
o
f
t
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
ar
e
s
h
o
wn
b
e
lo
w,
it
is
d
is
tin
g
u
is
h
ed
in
t
h
r
ee
s
tag
es:
in
itial
s
o
lu
tio
n
,
r
ef
in
ed
Gr
ee
d
y
an
d
en
h
an
ce
d
SA.
E
ac
h
o
f
th
ese
lev
els
f
ac
ilit
ates
th
e
o
b
s
er
v
atio
n
o
f
th
e
g
r
ad
u
al
im
p
r
o
v
em
e
n
t
in
ter
m
s
o
f
to
ta
l
d
is
tan
ce
tr
av
eled
,
n
u
m
b
er
o
f
tr
u
ck
s
u
s
ed
,
p
en
alize
d
co
s
t,
ex
ec
u
tio
n
tim
e
an
d
n
u
m
b
er
o
f
iter
atio
n
s
u
n
til co
n
v
er
g
en
ce
is
r
ea
c
h
ed
.
T
ab
le
2
co
m
p
ar
es
th
r
ee
m
eth
o
d
s
ap
p
lied
to
th
e
A
-
n32
-
k
5
d
a
taset,
wh
ich
in
clu
d
es
3
2
cu
s
to
m
er
s
.
T
h
e
in
itial
s
o
lu
tio
n
,
g
en
e
r
ated
wi
th
th
e
Gr
ee
d
y
alg
o
r
ith
m
,
r
e
q
u
ir
es
5
tr
u
ck
s
,
tr
a
v
els
a
to
t
al
o
f
7
9
0
k
m
a
n
d
g
en
er
ates
a
p
en
alize
d
co
s
t
o
f
3
2
9
0
.
B
y
ap
p
l
y
in
g
a
r
ef
in
e
d
v
er
s
io
n
o
f
th
e
Gr
ee
d
y
alg
o
r
ith
m
,
an
d
a
f
ter
5
0
iter
atio
n
s
o
f
ad
ju
s
tm
en
t,
s
ig
n
if
ican
t
im
p
r
o
v
e
m
en
ts
wer
e
o
b
t
ain
ed
:
T
h
e
to
tal
d
is
tan
ce
was
r
ed
u
ce
d
b
y
3
.
1
6
%
(
f
r
o
m
7
9
0
k
m
to
7
6
5
k
m
)
,
t
h
e
n
u
m
b
er
o
f
tr
u
ck
s
d
ec
r
ea
s
ed
f
r
o
m
5
to
4
,
r
ep
r
esen
tin
g
an
im
p
r
o
v
em
e
n
t
o
f
2
0
%,
an
d
th
e
p
en
alize
d
co
s
t w
as r
ed
u
ce
d
b
y
1
5
.
9
6
% (
f
r
o
m
3
2
9
0
to
2
7
6
5
)
.
T
ab
le
2
.
R
esu
lts
o
f
test
s
p
er
f
o
r
m
ed
with
A
-
n
3
2
-
k
5
d
atasets
D
a
t
a
s
e
t
C
l
i
e
n
t
s
(
n
o
d
e
s)
M
e
t
h
o
d
To
t
a
l
d
i
s
t
a
n
c
e
(
k
m)
Tr
u
c
k
s
P
e
n
a
l
i
z
e
d
C
o
s
t
I
t
e
r
a
t
i
o
n
s
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
d
i
s
t
a
n
c
e
(
%)
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
t
r
u
c
k
s
(
%)
I
mp
r
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v
e
m
e
n
t
o
v
e
r
c
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st
(
%)
R
u
n
t
i
m
e
(
s)
A
-
n
3
2
-
k5
32
I
n
i
t
i
a
l
S
o
l
u
t
i
o
n
7
9
0
5
3
,
2
9
0
G
e
n
e
r
a
t
e
d
w
i
t
h
G
r
e
e
d
y
-
-
1
.
5
R
e
f
i
n
e
d
G
r
e
e
d
y
7
6
5
4
2
,
7
6
5
5
0
i
t
e
r
a
t
i
o
n
s
o
f
a
d
j
u
s
t
me
n
t
3
.
1
6
20
1
5
.
9
6
2
.
0
En
h
a
n
c
e
d
SA
7
1
5
3
2
,
2
1
5
C
o
n
v
e
r
g
e
n
c
e
o
n
9
5
6
.
5
4
25
1
9
.
8
9
1
8
.
0
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
7
0
7
-
7
1
8
714
Fin
ally
,
b
y
ap
p
ly
in
g
th
e
SA
alg
o
r
ith
m
,
an
ev
e
n
m
o
r
e
e
f
f
icien
t
s
o
lu
tio
n
was
ac
h
iev
ed
af
ter
9
5
iter
atio
n
s
:
T
h
e
to
tal
d
is
tan
ce
was
r
ed
u
ce
d
to
7
1
5
k
m
,
r
e
p
r
esen
tin
g
a
6
.
5
4
%
im
p
r
o
v
e
m
e
n
t
o
v
er
th
e
in
itial
s
o
lu
tio
n
,
o
n
ly
3
tr
u
ck
s
wer
e
u
s
ed
,
ac
h
iev
in
g
a
2
5
%
im
p
r
o
v
em
en
t,
an
d
th
e
p
e
n
alize
d
co
s
t
d
ec
r
ea
s
ed
to
2
2
1
5
,
with
an
im
p
r
o
v
em
en
t
o
f
1
9
.
8
9
%.
T
ab
le
3
p
r
esen
ts
th
e
r
esu
lt
s
o
f
t
h
e
v
eh
icle
r
o
u
tin
g
o
p
tim
i
za
tio
n
u
s
in
g
th
e
B
-
n31
-
k
5
d
ataset,
in
v
o
lv
i
n
g
3
1
c
u
s
to
m
er
s
.
I
n
th
e
in
itial
s
o
lu
tio
n
,
g
en
er
ated
with
th
e
Gr
ee
d
y
alg
o
r
ith
m
,
5
tr
u
ck
s
wer
e
tak
en
to
c
o
v
er
a
to
tal
d
is
tan
ce
o
f
8
4
5
k
m
,
with
a
p
en
ali
ze
d
co
s
t o
f
3
3
4
5
.
W
h
en
ap
p
ly
in
g
th
e
Gr
ee
d
y
alg
o
r
ith
m
(
a
f
ter
5
5
iter
atio
n
s
)
,
s
ig
n
if
ican
t
im
p
r
o
v
em
en
ts
wer
e
o
b
s
er
v
ed
:
T
h
e
to
tal
d
is
tan
ce
was
r
ed
u
ce
d
b
y
6
.
5
1
%
(
f
r
o
m
8
4
5
k
m
t
o
7
9
0
k
m
)
,
with
r
esp
ec
t
to
f
leets
it
was
r
ed
u
ce
d
b
y
4
tr
u
ck
s
(
2
0
% less
)
,
an
d
th
e
p
e
n
alize
d
co
s
t d
ec
r
ea
s
ed
to
2
8
9
0
,
r
ep
r
esen
tin
g
a
n
im
p
r
o
v
em
e
n
t
o
f
1
3
.
6
0
%.
Su
b
s
eq
u
en
tly
,
with
th
e
im
p
le
m
en
tatio
n
o
f
th
e
E
n
h
a
n
ce
d
SA
alg
o
r
ith
m
,
af
ter
1
0
0
iter
ati
o
n
s
u
n
til
co
n
v
er
g
en
ce
was
r
ea
ch
ed
,
m
o
r
e
ef
f
icien
t
r
esu
lts
wer
e
o
b
tain
ed
:
T
h
e
to
tal
d
is
tan
ce
d
ec
r
ea
s
ed
to
7
5
5
k
m
,
with
a
f
u
r
th
er
im
p
r
o
v
em
en
t
o
f
4
.
4
3
%
o
v
er
th
e
p
r
ev
i
o
u
s
s
o
lu
tio
n
,
th
e
n
u
m
b
er
o
f
tr
u
ck
s
was
o
p
tim
ized
to
3
,
im
p
ly
in
g
an
im
p
r
o
v
em
en
t
o
f
2
5
%
co
m
p
ar
ed
to
th
e
in
itial
s
o
lu
tio
n
,
an
d
t
h
e
p
e
n
alize
d
c
o
s
t
was
r
ed
u
ce
d
t
o
2
2
5
5
,
ac
h
iev
in
g
an
im
p
r
o
v
em
en
t o
f
2
1
.
9
7
% o
v
er
t
h
e
Gr
ee
d
y
m
eth
o
d
.
T
ab
le
4
s
h
o
ws
th
e
r
esu
lts
o
b
t
ain
ed
b
y
ap
p
l
y
in
g
d
if
f
er
en
t
o
p
tim
izatio
n
m
eth
o
d
s
o
n
th
e
E
-
n
1
0
1
-
k
1
4
d
ataset,
wh
ich
co
n
s
id
er
s
1
0
1
c
u
s
to
m
er
s
.
T
h
e
in
itial
s
o
lu
tio
n
was
g
en
er
ated
with
1
4
tr
u
ck
s
,
tr
av
elin
g
a
to
tal
o
f
3
1
0
0
k
m
an
d
g
en
er
atin
g
a
p
en
alize
d
c
o
s
t
o
f
1
0
1
0
0
.
I
m
p
r
o
v
e
m
en
t
with
Gr
ee
d
y
af
ter
7
0
iter
atio
n
s
,
a
s
ig
n
if
ican
t
im
p
r
o
v
em
en
t
was
o
b
tain
ed
:
T
h
e
d
is
tan
ce
was
r
e
d
u
ce
d
b
y
7
.
1
0
%,
d
o
wn
t
o
2
8
8
0
k
m
.
T
h
e
n
u
m
b
er
o
f
tr
u
ck
s
was
o
p
tim
ized
t
o
1
2
,
r
ep
r
esen
tin
g
a
n
im
p
r
o
v
em
e
n
t
o
f
1
4
.
2
9
%.
An
d
t
h
e
p
en
alize
d
co
s
t
was
r
ed
u
ce
d
t
o
8
6
8
0
,
an
i
m
p
r
o
v
em
en
t
o
f
1
4
.
0
6
% o
v
er
th
e
i
n
itial so
lu
tio
n
.
T
ab
le
3
.
R
esu
lts
o
f
test
s
p
er
f
o
r
m
ed
with
B
-
n31
-
k
5
d
atasets
D
a
t
a
s
e
t
C
l
i
e
n
t
s
(
n
o
d
e
s)
M
e
t
h
o
d
To
t
a
l
d
i
s
t
a
n
c
e
(
k
m)
Tr
u
c
k
s
P
e
n
a
l
i
z
e
d
C
o
s
t
I
t
e
r
a
t
i
o
n
s
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
d
i
s
t
a
n
c
e
(
%)
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
t
r
u
c
k
s
(
%)
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
c
o
st
(
%)
R
u
n
t
i
m
e
(
s)
B
-
n
3
1
-
k5
31
I
n
i
t
i
a
l
S
o
l
u
t
i
o
n
8
4
5
5
3
,
3
4
5
G
e
n
e
r
a
t
e
d
w
i
t
h
G
r
e
e
d
y
-
-
-
1
.
6
R
e
f
i
n
e
d
G
r
e
e
d
y
7
9
0
4
2
,
8
9
0
5
5
i
t
e
r
a
t
i
o
n
s
o
f
a
d
j
u
s
t
me
n
t
6
.
5
1
20
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3
.
6
0
2
.
3
En
h
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c
e
d
SA
7
5
5
3
2
,
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C
o
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25
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1
.
9
7
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0
.
0
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ab
le
4
.
R
esu
lts
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f
test
s
p
er
f
o
r
m
ed
with
E
-
n
1
0
1
-
k
1
4
d
atasets
D
a
t
a
s
e
t
C
l
i
e
n
t
s
(
n
o
d
e
s)
M
e
t
h
o
d
To
t
a
l
d
i
s
t
a
n
c
e
(
k
m)
Tr
u
c
k
s
P
e
n
a
l
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z
e
d
C
o
s
t
I
t
e
r
a
t
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n
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mp
r
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v
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m
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n
t
o
v
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r
d
i
s
t
a
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e
(
%)
I
mp
r
o
v
e
m
e
n
t
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v
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r
t
r
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c
k
s
(
%)
I
mp
r
o
v
e
m
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n
t
o
v
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r
c
o
st
(
%)
R
u
n
t
i
m
e
(
s)
E
-
n
1
0
1
-
k
1
4
1
0
1
I
n
i
t
i
a
l
S
o
l
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t
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o
n
3
,
1
0
0
14
10
,
100
G
e
n
e
r
a
t
e
d
w
i
t
h
G
r
e
e
d
y
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-
-
3
.
0
R
e
f
i
n
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d
G
r
e
e
d
y
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,
8
8
0
12
8
,
6
8
0
7
0
i
t
e
r
a
t
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o
n
s
o
f
a
d
j
u
s
t
me
n
t
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.
1
0
1
4
.
2
9
1
4
.
0
6
5
.
9
En
h
a
n
c
e
d
S
A
2
,
7
6
0
10
7
,
7
6
0
C
o
n
v
e
r
g
e
n
c
e
o
n
1
2
0
4
.
1
7
1
6
.
6
7
1
0
.
6
0
5
2
.
0
Op
tim
izin
g
with
th
e
SA
alg
o
r
i
th
m
in
1
2
0
iter
atio
n
s
u
n
til
r
ea
ch
in
g
co
n
v
er
g
en
ce
,
an
ef
f
icien
t
s
o
lu
tio
n
was
ac
h
iev
ed
,
th
e
to
tal
d
is
tan
ce
d
ec
r
ea
s
ed
t
o
2
7
6
0
k
m
,
r
ep
r
esen
tin
g
an
im
p
r
o
v
em
e
n
t
o
f
4
.
1
7
%
o
v
er
th
e
p
r
ev
io
u
s
s
o
lu
tio
n
,
th
e
n
u
m
b
er
o
f
c
h
an
g
es
d
ec
r
ea
s
ed
to
1
0
,
wh
ich
im
p
lies
an
im
p
r
o
v
em
e
n
t
o
f
1
6
.
6
7
%.
T
h
e
p
en
alize
d
co
s
t d
ec
r
ea
s
ed
t
o
7
7
6
0
,
wh
ich
is
an
im
p
r
o
v
em
en
t
o
f
1
0
.
6
0
% c
o
m
p
ar
ed
to
th
e
p
r
ev
io
u
s
s
o
lu
tio
n
.
Fin
ally
,
T
ab
le
5
s
h
o
ws
th
e
r
e
s
u
lts
o
b
tain
ed
b
y
ap
p
l
y
in
g
th
r
ee
o
p
tim
izatio
n
m
eth
o
d
s
o
n
th
e
d
ataset
X
-
n101
-
k
2
5
,
in
v
o
lv
in
g
1
0
1
c
u
s
to
m
er
s
.
I
n
t
h
e
in
itial
s
o
lu
tio
n
,
2
5
tr
u
ck
s
wer
e
u
s
ed
,
t
r
av
el
in
g
2
8
,
1
5
0
k
m
an
d
g
en
er
atin
g
a
p
en
alize
d
co
s
t
o
f
1
5
3
,
6
5
0
.
Ap
p
ly
i
n
g
th
e
Gr
e
ed
y
alg
o
r
ith
m
,
af
ter
8
0
iter
ati
o
n
s
,
im
p
r
o
v
em
e
n
ts
wer
e
o
b
s
er
v
e
d
,
t
h
e
d
is
tan
ce
was
r
ed
u
ce
d
to
2
6
,
7
2
0
k
m
,
wh
ich
r
ep
r
esen
ts
an
im
p
r
o
v
e
m
en
t
o
f
5
.
0
8
%,
t
h
e
n
u
m
b
er
o
f
tr
u
ck
s
d
ec
r
ea
s
ed
to
2
2
,
with
an
im
p
r
o
v
em
e
n
t o
f
1
2
%,
an
d
th
e
p
en
alize
d
co
s
t d
ec
r
ea
s
ed
to
1
3
2
,
7
2
0
,
im
p
r
o
v
in
g
b
y
1
3
.
6
2
%
with
r
esp
ec
t
to
th
e
i
n
itial
s
o
lu
tio
n
.
Op
tim
izin
g
with
th
e
SA
alg
o
r
ith
m
ac
h
iev
ed
im
p
r
o
v
em
e
n
ts
,
with
1
3
5
iter
atio
n
s
u
n
til
co
n
v
e
r
g
en
ce
,
a
m
o
r
e
ef
f
icien
t
s
o
lu
ti
o
n
was
ac
h
iev
ed
:
T
h
e
t
o
tal
d
is
tan
ce
was
r
ed
u
ce
d
to
2
5
,
8
0
0
k
m
,
with
an
ad
d
itio
n
al
im
p
r
o
v
em
en
t
o
f
3
.
4
4
%,
o
n
ly
1
9
tr
u
ck
s
wer
e
n
ee
d
ed
,
im
p
ly
in
g
an
im
p
r
o
v
em
en
t
o
f
1
3
.
6
4
%,
an
d
th
e
p
e
n
al
ized
co
s
t
was
r
ed
u
ce
d
to
1
2
7
,
3
0
0
,
r
ep
r
esen
tin
g
an
im
p
r
o
v
em
e
n
t o
f
4
.
0
8
% o
v
er
th
e
p
r
ev
i
o
u
s
s
o
lu
tio
n
.
Fro
m
th
e
an
aly
s
is
o
f
th
e
f
o
u
r
d
atasets
,
it
is
s
h
o
w
n
th
at
ea
ch
o
f
th
e
a
p
p
lied
m
eth
o
d
s
p
r
esen
ts
p
r
o
g
r
ess
iv
e
im
p
r
o
v
em
e
n
ts
.
C
alcu
latin
g
th
e
av
er
ag
es:
T
h
e
s
o
lu
tio
n
with
th
e
Gr
ee
d
y
alg
o
r
ith
m
m
an
a
g
ed
to
r
ed
u
ce
th
e
to
tal
d
is
tan
ce
b
y
5
.
7
1
%,
th
e
r
ed
u
ctio
n
in
n
u
m
b
er
o
f
tr
u
ck
s
b
y
1
6
.
5
7
%
an
d
r
e
d
u
ce
d
th
e
p
en
alize
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Gen
era
tio
n
o
f d
is
tr
ib
u
tio
n
r
o
u
tes w
ith
s
h
o
r
te
r
d
is
ta
n
ce
s
a
n
d
few
er v
eh
icles
…
(
F
lo
r
C
a
r
d
en
a
s
-
Ma
r
iñ
o
)
715
co
s
t
b
y
1
4
.
7
1
%
with
r
esp
ec
t
to
th
e
in
itial
s
o
lu
tio
n
.
L
o
o
k
in
g
f
o
r
m
o
r
e
ef
f
icien
c
y
,
th
e
SA
alg
o
r
ith
m
o
f
f
e
r
ed
ev
en
m
o
r
e
ef
f
icien
t
r
esu
lts
o
n
av
er
ag
e:
th
e
d
is
tan
ce
was
r
ed
u
ce
d
b
y
1
0
.
3
6
%,
th
e
u
s
e
o
f
tr
u
ck
s
d
ec
r
ea
s
ed
b
y
2
0
.
0
8
%,
a
n
d
th
e
p
en
alize
d
co
s
t
d
ec
r
ea
s
ed
b
y
1
8
.
6
4
%,
co
m
p
ar
ed
to
t
h
e
in
itial
s
o
lu
tio
n
.
T
h
ese
r
esu
lts
s
h
o
w
th
at
th
e
alg
o
r
ith
m
p
r
o
v
id
es a
n
o
p
tim
al
s
o
lu
tio
n
.
Fig
u
r
e
3
s
h
o
ws
th
e
ev
id
e
n
c
e,
with
n
u
m
er
ical
ac
cu
r
ac
y
,
o
f
th
e
d
ec
r
ea
s
in
g
tr
en
d
o
f
th
r
ee
k
ey
v
ar
iab
les:
to
tal
d
is
tan
ce
tr
av
el
ed
,
n
u
m
b
er
o
f
tr
u
c
k
s
u
s
ed
an
d
p
en
alize
d
c
o
s
t,
th
r
o
u
g
h
o
u
t
t
h
e
s
tag
es
o
f
in
itial
s
o
lu
tio
n
,
r
ef
in
e
d
Gr
ee
d
y
a
n
d
o
p
tim
izatio
n
b
y
m
ea
n
s
o
f
SA.
Fro
m
a
tech
n
ical
p
er
s
p
ec
tiv
e
,
it
ca
n
b
e
s
ee
n
th
at
th
e
im
p
r
o
v
em
e
n
t
cu
r
v
e
is
m
o
r
e
ac
ce
n
tu
ated
in
th
e
p
ass
ag
e
f
r
o
m
th
e
in
itial
s
o
lu
tio
n
to
Gr
ee
d
y
,
co
n
s
o
lid
atin
g
with
SA,
wh
er
e
th
e
r
ed
u
ctio
n
s
ar
e
s
tab
ilized
an
d
o
p
tim
iz
ed
.
T
h
e
g
r
a
p
h
ical
an
aly
s
is
co
n
f
ir
m
s
t
h
e
m
o
d
el'
s
ab
ilit
y
to
m
in
im
ize
l
o
g
is
tic
r
eso
u
r
ce
s
with
o
u
t
c
o
m
p
r
o
m
i
s
in
g
th
e
tr
ajec
to
r
y
,
r
e
d
u
cin
g
f
leet
o
v
e
r
u
s
e
an
d
ex
ce
s
s
iv
e
d
is
tan
ce
s
.
T
h
is
g
r
ap
h
ical
r
ep
r
esen
tatio
n
,
s
u
p
p
o
r
te
d
b
y
n
u
m
e
r
ical
an
aly
s
is
,
co
n
f
i
r
m
s
th
e
alg
o
r
ith
m
'
s
ab
ilit
y
to
b
alan
ce
o
p
e
r
atio
n
al
e
f
f
icien
cy
a
n
d
r
eso
u
r
ce
u
s
ag
e,
lead
in
g
t
o
r
e
d
u
ce
d
f
leet
o
v
e
r
u
s
e
an
d
e
x
ce
s
s
iv
e
d
is
tan
ce
,
wh
ich
is
p
ar
ticu
lar
l
y
n
o
tab
le
in
lar
g
e
-
s
ca
le
d
ata
s
ets
s
u
ch
as
X
-
n
1
0
1
-
k
2
5
,
wh
er
e
s
ca
lab
ilit
y
an
d
m
eth
o
d
o
l
o
g
ical
r
esil
ien
ce
allo
w
f
o
r
s
u
s
tain
ed
co
n
v
er
g
en
ce
t
o
war
d
s
h
ig
h
ly
ef
f
icien
t so
lu
tio
n
s
.
I
t
is
also
im
p
o
r
tan
t
to
r
ec
o
g
n
ize
th
at
th
e
SA
alg
o
r
ith
m
is
n
o
n
d
eter
m
in
is
tic,
s
o
it
is
p
r
o
b
ab
ly
n
o
t
p
o
s
s
ib
le
to
r
ec
r
ea
te
e
x
ac
tly
th
e
s
am
e
r
esu
lts
,
ev
en
with
t
h
e
s
am
e
s
tar
tin
g
p
ar
am
eter
s
,
h
ar
d
war
e,
an
d
s
o
f
twar
e
s
p
ec
if
icatio
n
s
.
T
ab
le
5
.
R
esu
lts
o
f
test
s
p
er
f
o
r
m
ed
with
X
-
n
1
0
1
-
k
2
5
d
atasets
D
a
t
a
s
e
t
C
l
i
e
n
t
s
(
n
o
d
e
s)
M
e
t
h
o
d
To
t
a
l
d
i
s
t
a
n
c
e
(
k
m)
Tr
u
c
k
s
P
e
n
a
l
i
z
e
d
C
o
s
t
I
t
e
r
a
t
i
o
n
s
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
d
i
s
t
a
n
c
e
(
%)
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
t
r
u
c
k
s
(
%)
I
mp
r
o
v
e
m
e
n
t
o
v
e
r
c
o
s
t
(
%)
R
u
n
t
i
m
e
(
s)
X
-
n
1
0
1
-
k
2
5
1
0
1
I
n
i
t
i
a
l
S
o
l
u
t
i
o
n
28
,
150
25
1
5
3
,
6
5
0
G
e
n
e
r
a
t
e
d
w
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t
h
G
r
e
e
d
y
-
-
-
3
.
5
R
e
f
i
n
e
d
G
r
e
e
d
y
26
,
720
22
1
3
2
,
7
2
0
8
0
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t
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t
i
o
n
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f
a
d
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u
s
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me
n
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.
0
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12
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3
.
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2
8
.
2
En
h
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d
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A
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o
n
1
3
5
3
.
4
4
1
3
.
6
4
4
.
0
8
6
3
.
0
Fig
u
r
e
3
.
C
o
m
p
a
r
ativ
e
g
r
ap
h
o
f
to
tal
d
is
tan
ce
tr
av
ele
d
an
d
n
u
m
b
er
o
f
tr
u
ck
s
r
eq
u
ir
ed
p
er
d
ataset
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
40
,
No
.
2
,
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v
em
b
er
20
25
:
7
0
7
-
7
1
8
716
5.
DIS
CU
SS
I
O
N
I
n
[
2
5
]
th
ey
h
ig
h
lig
h
t
th
e
u
s
e
o
f
n
eig
h
b
o
r
h
o
o
d
o
p
er
ato
r
s
a
n
d
d
y
n
am
ic
p
en
alty
s
tr
u
ctu
r
e
s
to
av
o
i
d
p
r
em
atu
r
e
c
o
n
v
e
r
g
en
ce
,
th
u
s
d
iv
er
s
if
y
in
g
s
ea
r
c
h
es,
r
esu
ltin
g
in
a
c
o
s
t
r
ed
u
ctio
n
o
n
av
er
ag
e
o
f
ab
o
u
t
5
%
co
m
p
ar
ed
to
SA
alo
n
e.
I
n
o
u
r
r
esear
ch
,
th
is
m
eth
o
d
was
s
tr
en
g
t
h
en
ed
b
y
ap
p
ly
i
n
g
ad
ap
tiv
e
tem
p
er
atu
r
e
ad
ju
s
tm
en
t
co
n
tr
o
l
s
tr
ateg
ies,
o
p
er
ato
r
s
h
av
e
a
weig
h
te
d
r
an
d
o
m
weig
h
t
an
d
ad
d
in
g
a
p
en
alty
s
ch
em
e
f
o
r
o
v
er
lo
ad
o
r
o
v
e
r
f
lo
w
r
o
u
tes.
I
n
ad
d
itio
n
,
i
n
teg
r
ated
m
etr
ic
s
h
av
e
b
ee
n
in
clu
d
ed
t
o
s
im
u
ltan
eo
u
s
ly
ev
alu
ate
to
tal
r
o
u
te
d
is
tan
ce
,
n
u
m
b
e
r
o
f
tr
u
c
k
s
u
s
ed
a
n
d
p
en
alty
co
s
ts
,
th
u
s
p
r
o
v
id
in
g
a
b
etter
ass
ess
m
en
t
o
f
lo
g
is
tics
p
er
f
o
r
m
an
ce
.
T
h
is
co
m
b
i
n
atio
n
o
f
th
ese
f
ac
to
r
s
allo
ws
ex
p
lo
r
in
g
s
o
lu
tio
n
s
in
ad
d
itio
n
to
lo
ca
l
im
p
r
o
v
em
e
n
t
an
d
im
p
r
o
v
in
g
th
e
f
in
al
q
u
alit
y
co
m
p
ar
ed
to
t
h
e
tr
ad
itio
n
al
SA
an
d
th
e
GL
S
-
SA
f
r
am
ewo
r
k
in
s
talled
in
[2
5
]
.
T
h
er
ef
o
r
e,
o
u
r
p
r
o
p
o
s
al
p
r
o
v
i
d
es
a
g
r
ea
t
a
d
d
ed
v
alu
e,
wh
ic
h
p
r
o
v
id
es
a
s
tr
o
n
g
a
n
d
f
lex
ib
le
ap
p
r
o
ac
h
th
at
is
lik
ely
to
b
e
a
p
p
lied
to
m
ajo
r
p
r
o
b
lem
s
an
d
lo
g
is
tic
co
m
p
lex
i
ty
.
I
n
co
m
p
ar
is
o
n
with
p
ap
e
r
[
1
1
]
,
wh
ich
s
h
o
ws
an
SA
alg
o
r
ith
m
f
o
r
r
o
u
tin
g
p
r
o
b
lem
s
with
two
-
d
im
en
s
io
n
al
lo
ad
co
n
s
tr
ain
ts
,
it
is
s
ee
n
th
at,
alth
o
u
g
h
it
co
v
er
ed
th
e
ch
allen
g
e
o
f
s
p
atial
co
m
p
lex
ity
,
its
f
o
cu
s
lay
in
h
an
d
lin
g
g
eo
m
et
r
ic
an
d
lo
ad
co
n
s
tr
ain
ts
.
Ou
r
p
r
o
p
o
s
a
l,
d
esp
ite
ca
p
ac
ity
co
n
s
tr
ain
ts
,
ad
d
r
ess
es
d
is
tan
ce
an
d
f
leet
m
in
im
izatio
n
e
q
u
a
lly
,
an
d
b
y
u
s
in
g
an
ad
ju
s
tab
le
p
e
n
alty
s
y
s
tem
o
n
v
eh
i
cle
s
u
r
p
lu
s
es.
T
h
e
in
tr
o
d
u
ctio
n
o
f
m
u
ltip
le
o
p
er
ato
r
s
an
d
tem
p
er
atu
r
e
ad
a
p
tab
ilit
y
en
s
u
r
e
a
m
o
r
e
f
lex
ib
le
ad
ap
tab
ilit
y
,
wh
ic
h
p
u
ts
u
s
in
an
ad
v
an
tag
e
o
u
s
p
o
s
itio
n
.
C
o
m
p
ar
in
g
with
p
ap
er
[
1
5
]
,
C
o
m
p
ar
in
g
with
th
e
ar
ticle
[
1
5
]
,
wh
ic
h
ad
d
r
ess
es
th
e
s
o
lu
tio
n
o
f
a
p
er
io
d
ic
ca
p
ac
itated
r
o
u
tin
g
p
r
o
b
lem
u
s
in
g
t
h
e
SA
tech
n
iq
u
e,
it
s
h
o
u
l
d
b
e
n
o
ted
t
h
at
th
is
r
esear
ch
is
f
o
c
u
s
ed
o
n
th
e
ex
e
r
cise
o
f
d
eliv
er
i
n
g
l
o
ad
s
o
v
er
s
ev
er
al
p
er
io
d
s
with
h
ig
h
e
r
r
an
k
in
th
e
s
tab
ilit
y
an
d
r
ep
ea
ta
b
ilit
y
o
f
r
o
u
tes.
I
n
co
n
tr
ast,
o
u
r
p
r
o
p
o
s
al
f
o
cu
s
es
o
n
th
e
tr
ea
tm
en
t
o
f
s
tatic
in
s
tan
ce
s
,
b
u
t
with
m
o
r
e
r
estrictio
n
in
th
e
o
p
tim
izatio
n
o
f
th
e
m
ar
g
in
o
f
d
is
tan
ce
,
n
u
m
b
er
o
f
v
eh
icles
an
d
co
s
ts
in
ea
ch
iter
atio
n
in
th
e
s
o
lu
tio
n
.
Als
o
,
we
co
n
s
id
er
th
e
u
s
e
o
f
v
alid
ity
co
n
tr
o
l
m
eth
o
d
s
o
f
th
e
s
o
lu
tio
n
s
,
wh
ich
ar
e
au
to
m
atic
a
n
d
ad
ap
tiv
e
in
th
e
p
ar
am
eter
s
an
d
n
eig
h
b
o
r
h
o
o
d
s
elec
tio
n
,
wh
ich
m
ak
es
it
p
o
s
s
ib
le
to
d
ea
l
with
v
ar
ia
b
ilit
y
an
d
a
v
o
id
g
ettin
g
tr
ap
p
ed
in
lo
ca
l
o
p
tim
a.
T
h
e
d
if
f
er
en
tiatio
n
lies
in
th
e
p
o
s
s
i
b
ilit
y
o
f
ca
lcu
latin
g
th
e
co
s
t
o
f
f
leet
o
v
er
r
u
n
s
an
d
p
u
n
is
h
in
g
with
s
tep
-
ty
p
e
p
e
n
alties,
wh
ich
g
iv
es
m
o
r
e
f
r
ee
d
o
m
to
im
p
lem
e
n
t
in
en
v
ir
o
n
m
en
ts
with
lim
ited
r
eso
u
r
ce
s
an
d
u
n
s
ta
b
le
d
em
a
n
d
.
In
[2
5
]
,
r
esear
ch
er
s
ad
d
r
ess
ed
th
e
p
lan
n
i
n
g
o
f
d
is
tr
ib
u
tio
n
r
o
u
tes
f
o
r
2
6
f
is
h
in
g
v
ess
els
lo
ca
ted
in
th
e
Natio
n
al
Fis
h
in
g
Po
r
t
o
f
Mo
lu
cc
as,
tak
in
g
in
to
ac
co
u
n
t
t
h
e
attr
ib
u
tes
o
f
d
is
tan
ce
,
v
ess
el
ca
p
ac
ity
,
ca
tch
v
o
lu
m
e,
tim
e
a
n
d
o
p
er
atin
g
co
s
ts
.
T
h
e
s
tu
d
y
ap
p
lies
GL
S
an
d
SA
d
ev
elo
p
e
d
in
Go
o
g
le
OR
-
T
o
o
ls
.
T
h
e
r
esear
ch
s
h
o
ws
t
h
at,
with
two
o
r
th
r
ee
v
ess
els,
th
e
d
is
tan
ce
s
ar
e
s
im
ilar
to
2
9
0
an
d
3
5
5
m
iles
.
B
u
t
wh
en
u
s
in
g
f
o
u
r
s
h
ip
s
,
th
e
d
is
tan
ce
o
b
tai
n
ed
b
y
GL
S
is
4
6
4
m
iles
,
w
h
ile
SA
ac
h
iev
es
it
in
4
3
9
m
iles
,
g
iv
in
g
a
6
%
in
cr
ea
s
e
in
ef
f
icien
cy
.
T
h
is
d
if
f
er
en
ce
s
h
o
ws
th
at,
wh
en
th
e
p
r
o
b
lem
is
m
o
r
e
c
o
m
p
lex
,
SA
b
ec
o
m
es
m
o
r
e
ef
f
ec
tiv
e
an
d
m
an
a
g
es
to
m
in
im
ize
d
is
tan
ce
,
tim
e
an
d
co
s
ts
.
I
n
o
u
r
r
esear
ch
,
we
h
av
e
u
s
e
d
th
e
SA
alg
o
r
ith
m
b
u
t
m
o
d
if
ie
d
it
to
h
an
d
le
ad
d
i
tio
n
al
tem
p
o
r
al
d
im
e
n
s
io
n
s
an
d
o
p
er
atio
n
al
co
n
s
tr
ain
ts
s
u
ch
as
tim
e
win
d
o
ws,
ca
p
ac
ity
co
n
s
tr
ain
ts
,
an
d
lo
ad
r
etu
r
n
s
.
B
y
s
u
b
jectin
g
it
t
o
2
0
0
test
in
s
tan
ce
s
,
we
o
b
tain
ed
o
n
av
e
r
ag
e
a
1
0
.
0
7
%
im
p
r
o
v
em
en
t
in
r
o
u
te
d
is
tr
ib
u
tio
n
an
d
cu
s
to
m
er
s
er
v
i
ce
,
co
n
f
ir
m
i
n
g
th
e
r
o
b
u
s
tn
es
s
an
d
o
p
tim
izatio
n
ca
p
ab
ilit
y
o
f
th
e
p
r
o
p
o
s
ed
a
p
p
r
o
ac
h
in
h
ig
h
ly
co
m
p
le
x
lo
g
is
t
ics s
ce
n
ar
io
s
.
6.
CO
NCLU
SI
O
N
T
h
e
p
r
esen
t
s
tu
d
y
h
as
d
em
o
n
s
tr
ated
th
e
ef
f
ec
tiv
en
ess
o
f
h
e
u
r
is
tic
an
d
m
etah
eu
r
is
tic
ap
p
r
o
ac
h
es
in
th
e
o
p
tim
izatio
n
o
f
th
e
co
n
s
tr
a
i
n
ed
VR
P
.
T
h
e
co
m
b
i
n
atio
n
o
f
th
e
G
r
ee
d
y
an
d
SA
alg
o
r
ith
m
s
allo
ws
o
b
tain
in
g
ef
f
icien
t
s
o
lu
tio
n
s
,
s
ig
n
if
ican
tly
r
ed
u
cin
g
th
e
t
o
tal
d
is
tan
c
e
tr
av
eled
,
th
e
n
u
m
b
er
o
f
tr
u
ck
s
u
s
ed
an
d
th
e
ass
o
ciate
d
p
en
alize
d
c
o
s
t
in
t
h
e
VR
P.
Giv
en
a
n
in
itial
s
o
lu
tio
n
,
th
e
Gr
ee
d
y
alg
o
r
ith
m
s
i
g
n
if
ican
tly
r
ed
u
ce
d
th
e
d
is
tan
ce
,
n
u
m
b
e
r
o
f
tr
u
c
k
s
an
d
p
en
alty
co
s
t,
an
d
wh
en
th
e
SA
alg
o
r
ith
m
was
ap
p
lied
,
th
e
d
is
tan
ce
,
n
u
m
b
er
o
f
ch
a
n
g
es
an
d
p
e
n
alty
co
s
ts
wer
e
f
u
r
th
er
r
ed
u
ce
d
,
d
em
o
n
s
tr
atin
g
th
at
a
c
o
m
b
in
atio
n
o
f
t
h
ese
alg
o
r
ith
m
s
co
u
l
d
b
e
u
s
ed
to
ac
h
iev
e
m
o
r
e
r
o
b
u
s
t
an
d
s
tab
le
s
o
lu
tio
n
s
co
m
p
ar
e
d
to
co
n
v
en
tio
n
al
m
eth
o
d
o
l
o
g
ies.
I
n
ter
m
s
o
f
i
m
p
ac
t,
co
s
t
r
ed
u
ctio
n
an
d
b
etter
u
tili
za
tio
n
o
f
a
v
ailab
le
r
eso
u
r
ce
s
r
ep
r
esen
t
s
u
b
s
tan
tial
b
en
ef
its
f
o
r
g
o
o
d
s
d
is
tr
ib
u
tio
n
m
a
n
ag
em
en
t.
T
h
is
s
tu
d
y
lay
s
th
e
g
r
o
u
n
d
w
o
r
k
f
o
r
f
u
tu
r
e
r
esear
ch
in
th
e
in
teg
r
atio
n
o
f
o
t
h
er
ad
v
a
n
ce
d
m
etah
eu
r
is
tic
ap
p
r
o
ac
h
es
an
d
th
e
in
co
r
p
o
r
atio
n
o
f
d
y
n
am
ic
co
n
s
tr
ain
ts
in
r
o
u
te
p
lan
n
in
g
,
with
th
e
aim
o
f
f
u
r
th
e
r
im
p
r
o
v
in
g
ef
f
icien
c
y
in
lo
g
is
tics
an
d
tr
an
s
p
o
r
tatio
n
.
ACK
NO
WL
E
DG
M
E
N
T
T
h
is
wo
r
k
was
f
u
n
d
ed
b
y
C
ONCYTE
C
-
PR
O
C
I
E
NC
I
A
w
ith
in
th
e
f
r
a
m
ewo
r
k
o
f
th
e
c
o
m
p
etitio
n
“M
o
b
ilizatio
n
s
AM
SUD
2
0
2
3
-
0
1
”
co
n
tr
ac
t n
u
m
b
er
N° PE
5
0
1
0
8
4
0
1
0
-
2
0
2
3
-
PR
OC
I
E
NC
I
A
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