I
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t
e
r
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at
ion
al
Jou
r
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a
l
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f
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at
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an
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Com
m
u
n
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T
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c
h
n
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ogy
(
I
J
-
I
CT
)
Vo
l
.
1
5
,
N
o
.
4
,
D
e
c
e
m
b
e
r
20
2
6
,
pp.
1929
~
194
3
I
S
S
N:
2252
-
8776
,
DO
I
:
10
.
11591/i
ji
c
t
.
v
1
5
i
4
.
pp
19
29
-
194
3
1929
Jou
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page
:
ht
tp:
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K
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:
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@
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8776
I
n
t
J
I
n
f
&
C
o
m
m
u
n
T
e
c
hn
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,
Vo
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1
5
,
N
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4
,
D
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c
e
m
be
r
20
2
6
:
1929
-
194
3
1930
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ut
a
l
s
o
c
o
n
s
i
de
r
v
a
r
i
o
us
ot
h
e
r
f
a
c
t
o
r
s
s
uc
h
a
s
a
c
t
ua
l
t
r
a
v
e
l
t
i
m
e
,
c
o
n
ge
s
t
i
o
n
l
e
v
e
l
s
,
r
o
a
d
s
a
f
e
t
y
,
f
u
e
l
c
o
ns
u
m
pt
i
o
n
,
a
n
d
r
o
a
d
i
n
f
r
a
s
t
r
uc
t
ur
e
qua
l
i
t
y
.
F
ur
t
h
e
r
m
o
r
e
,
t
r
a
f
f
i
c
c
o
n
d
i
t
i
o
n
s
a
r
e
d
y
n
a
mi
c
a
n
d
c
a
n
c
h
a
n
ge
s
i
g
nif
i
c
a
n
t
l
y
i
n
a
m
a
t
t
e
r
o
f
mi
nut
e
s
due
to
c
o
n
ge
s
t
i
o
n
,
a
c
c
i
de
n
t
s
,
r
o
a
d
c
o
n
s
t
r
u
c
t
i
o
n
,
o
r
s
pe
c
i
a
l
e
v
e
n
t
s
[
1]
.
M
u
l
t
i
-
c
r
i
t
e
r
i
a
de
c
i
s
i
o
n
m
a
k
i
ng
(
M
C
DM
)
h
a
s
de
ve
lo
pe
d
a
s
a
p
o
we
r
f
u
l
a
ppr
o
a
c
h
t
o
h
a
n
d
l
i
ng
c
o
m
p
l
e
x
de
c
i
s
i
o
n
-
m
a
k
i
ng
pr
o
bl
e
m
s
i
nv
o
l
v
i
ng
m
u
l
t
i
p
l
e
c
r
i
t
e
r
i
a
t
h
a
t
a
r
e
o
f
t
e
n
c
o
nf
li
c
t
i
n
g.
T
h
e
w
e
i
g
h
t
e
d
s
u
m
m
e
t
h
o
d
(
W
S
M
)
a
n
d
we
i
g
h
t
e
d
p
r
o
duc
t
m
e
t
h
o
d
(
W
P
M
)
a
r
e
t
w
o
o
f
t
h
e
m
o
s
t
wi
de
ly
u
s
e
d
M
C
DM
t
e
c
hni
que
s
i
n
v
a
r
i
o
us
a
pp
l
i
c
a
t
i
o
ns
.
W
S
M
us
e
s
a
n
i
n
t
u
i
t
i
v
e
a
n
d
e
a
s
y
-
to
-
un
de
r
s
t
a
n
d
we
i
g
h
t
e
d
s
um
a
p
p
r
o
a
c
h
,
w
hil
e
W
P
M
us
e
s
we
i
g
h
t
e
d
m
u
l
t
i
p
l
i
c
a
t
i
o
n
,
whi
c
h
h
a
s
t
h
e
a
d
v
a
n
t
a
ge
o
f
ha
n
d
l
i
ng
c
r
i
t
e
r
i
a
w
i
t
h
d
i
f
f
e
r
e
n
t
m
e
a
s
ur
e
m
e
n
t
uni
t
s
a
n
d
i
s
m
o
r
e
s
e
ns
i
t
i
ve
to
c
h
a
n
ge
s
i
n
c
r
i
t
e
r
i
o
n
v
a
l
ue
s
.
H
owe
v
e
r
,
t
h
e
i
n
t
e
gr
a
t
i
o
n
o
f
M
C
DM
m
e
t
h
o
ds
wi
t
h
pa
t
h
s
e
a
r
c
h
a
l
go
r
i
t
hm
s
f
o
r
dy
n
a
m
i
c
r
o
u
t
e
o
p
t
i
mi
z
a
t
i
o
n
i
s
s
t
i
ll
a
n
a
r
e
a
o
f
o
n
go
i
n
g
r
e
s
e
a
r
c
h
[
2]
-
[
4]
.
S
e
v
e
r
a
l
s
t
udi
e
s
ha
v
e
a
tt
e
m
pt
e
d
to
i
n
t
e
gr
a
t
e
m
u
l
t
i
-
c
r
i
t
e
r
i
a
w
i
t
h
pa
t
h
s
e
a
r
c
h
a
l
go
r
i
t
hm
s
.
Ho
we
v
e
r
,
m
o
s
t
o
f
t
h
e
s
e
s
t
udi
e
s
s
t
i
ll
h
a
ve
l
im
i
t
a
t
i
o
ns
,
i
n
c
l
ud
in
g:
(
i
)
t
h
e
us
e
o
f
s
t
a
t
i
c
c
r
i
t
e
r
i
a
w
e
i
g
h
t
s
t
h
a
t
c
a
n
n
o
t
a
da
pt
to
c
h
a
n
g
i
ng
t
r
a
f
f
i
c
c
o
n
d
i
t
i
o
ns
,
(
ii
)
t
h
e
a
pp
l
i
c
a
t
i
o
n
o
f
o
nl
y
o
n
e
M
C
D
M
m
e
t
h
o
d
w
i
t
h
o
ut
u
t
i
li
z
i
n
g
t
h
e
c
o
m
p
l
e
m
e
n
t
a
r
y
a
dva
n
t
a
ge
s
o
f
d
i
f
f
e
r
e
n
t
m
e
t
h
o
ds
,
(
iii
)
l
a
c
k
o
f
i
n
t
e
gr
a
t
i
o
n
w
i
t
h
r
e
a
l
-
t
i
m
e
t
r
a
f
f
i
c
da
t
a
,
c
a
us
i
n
g
t
h
e
s
y
s
t
e
m
to
b
e
un
r
e
s
p
o
n
s
i
ve
t
o
c
h
a
n
g
i
ng
c
o
n
d
i
t
i
o
n
s
,
a
n
d
(
iv
)
hi
g
h
c
o
m
put
a
t
i
o
n
a
l
c
o
m
p
l
e
xi
t
y
,
m
a
k
i
n
g
i
t
im
pr
a
c
t
i
c
a
l
f
o
r
r
e
a
l
-
t
i
m
e
i
m
p
l
e
m
e
n
t
a
t
i
o
n
o
n
l
a
r
ge
-
s
c
a
l
e
r
o
a
d
n
e
t
w
o
r
ks
[
5]
.
B
a
s
e
d
o
n
t
h
e
b
a
c
kgr
o
un
d
de
s
c
r
i
b
e
d
a
b
o
v
e
,
t
hi
s
s
t
udy
f
o
r
m
u
l
a
t
e
s
s
e
v
e
r
a
l
pr
o
bl
e
m
s
a
s
f
o
l
l
o
w
s
:
[
6]
h
ow
t
o
m
o
d
i
f
y
t
h
e
D
ij
ks
t
r
a
a
l
go
r
i
t
hm
to
a
c
c
o
m
m
o
da
t
e
m
u
l
t
i
p
l
e
c
r
i
t
e
r
i
a
i
n
o
pt
i
m
a
l
r
o
u
t
e
s
e
a
r
c
h
by
c
o
n
s
i
de
r
i
n
g
r
e
a
l
-
t
i
m
e
t
r
a
f
f
i
c
c
o
n
d
i
t
i
o
ns
?
,
[
7]
h
o
w
to
i
n
t
e
gr
a
t
e
t
h
e
W
S
M
a
n
d
W
P
M
i
n
a
hy
br
i
d
mann
e
r
to
pr
o
duc
e
m
o
r
e
r
o
b
us
t
a
n
d
b
a
l
a
nc
e
d
r
o
u
t
i
n
g
de
c
i
s
io
n
s
?
,
[
8]
h
ow
c
a
n
a
n
a
da
pt
i
v
e
we
i
g
h
t
i
n
g
m
e
c
h
a
ni
s
m
b
e
de
v
e
l
o
pe
d
t
h
a
t
c
a
n
dy
na
m
i
c
a
ll
y
a
d
j
us
t
c
r
i
t
e
r
i
a
pr
i
o
r
i
t
i
e
s
b
a
s
e
d
o
n
a
c
t
ua
l
t
r
a
f
f
i
c
c
o
n
d
i
t
i
o
ns
?
,
[
9]
h
o
w
d
o
e
s
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
c
o
m
pa
r
e
to
t
h
e
c
o
n
v
e
n
t
i
o
n
a
l
D
ij
ks
t
r
a
a
l
go
r
i
t
hm
a
n
d
s
i
ng
l
e
M
C
DM
m
e
t
h
o
ds
i
n
v
a
r
i
o
us
t
r
a
f
f
i
c
s
c
e
n
a
r
i
o
s
?
,
a
n
d
[
10]
h
ow
e
f
f
i
c
i
e
n
t
i
s
t
h
e
c
o
m
put
a
t
i
o
n
o
f
t
h
e
pr
o
p
o
s
e
d
a
l
g
o
r
i
t
hm
to
e
ns
ur
e
i
t
s
f
e
a
s
i
b
il
i
t
y
f
o
r
i
m
p
l
e
m
e
n
t
a
t
i
o
n
i
n
r
e
a
l
-
t
i
me
n
a
vi
ga
t
i
o
n
s
y
s
t
e
m
s
?
[
11]
,
[
12]
.
T
hi
s
s
t
ud
y
a
im
s
t
o
:
[
12
]
de
v
e
l
o
p
a
m
o
d
i
f
i
e
d
D
ij
ks
t
r
a
’
s
a
l
go
r
i
t
h
m
c
a
pa
bl
e
o
f
i
n
t
e
gr
a
t
i
n
g
m
u
l
t
i
p
l
e
c
r
i
t
e
r
i
a
w
i
t
h
r
e
a
l
-
t
i
m
e
t
r
a
f
f
i
c
da
t
a
f
o
r
dy
na
m
i
c
r
out
e
o
p
t
i
mi
z
a
t
i
o
n
.
R
a
m
a
m
o
o
r
t
hy
e
t
al
.
[
13]
d
e
s
i
g
n
a
hy
b
r
i
d
W
S
M
-
W
P
M
f
r
a
m
e
wo
r
k
t
h
a
t
c
o
m
bi
ne
s
t
h
e
a
dv
a
n
t
a
ge
s
o
f
b
o
t
h
m
e
t
h
o
ds
to
pr
o
duc
e
a
m
o
r
e
b
a
l
a
n
c
e
d
a
n
d
r
o
b
us
t
r
o
u
t
i
n
g
s
o
l
u
t
i
o
n
.
Do
a
n
e
t
al
.
[
14]
i
m
p
l
e
m
e
nt
a
n
a
da
pt
i
v
e
we
i
g
h
t
i
n
g
m
e
c
h
a
ni
s
m
t
h
a
t
c
a
n
a
utom
a
t
i
c
a
ll
y
a
d
j
u
s
t
c
r
i
t
e
r
i
a
we
i
g
h
t
s
b
a
s
e
d
o
n
c
ur
r
e
n
t
t
r
a
f
f
i
c
c
o
n
d
i
t
i
o
n
s
.
S
a
va
da
t
t
i
e
t
al.
[
11]
c
o
n
duc
t
a
c
o
m
pr
e
h
e
ns
i
ve
e
v
a
l
ua
t
i
o
n
o
f
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
’
s
p
e
r
f
o
r
m
a
nc
e
t
h
r
o
ugh
e
x
p
e
r
im
e
n
t
s
o
n
r
e
a
l
ur
ba
n
r
o
a
d
n
e
t
w
or
ks
w
i
t
h
v
a
r
i
o
us
t
r
a
f
f
i
c
s
c
e
n
a
r
i
o
s
.
B
a
ne
r
j
e
e
e
t
al.
[
15
]
a
n
a
l
y
z
e
d
t
h
e
c
o
m
put
a
t
i
o
n
a
l
e
f
f
i
c
i
e
nc
y
a
n
d
s
c
a
l
a
bil
it
y
o
f
t
h
e
a
l
go
r
i
t
hm
t
o
v
a
l
i
da
t
e
i
t
s
f
e
a
s
i
b
il
i
t
y
f
o
r
i
m
p
l
e
m
e
n
t
a
ti
o
n
i
n
r
e
a
l
-
t
i
m
e
i
n
t
e
l
li
g
e
n
t
t
r
a
n
s
po
r
t
a
t
i
o
n
s
y
s
t
e
m
s
(
I
T
S
)
.
T
hi
s
s
tudy
i
nv
e
s
t
i
ga
t
e
d
t
h
e
e
f
f
e
c
t
s
o
f
a
ppl
y
i
ng
t
h
e
a
d
a
p
t
i
v
e
M
C
DM
a
n
d
m
o
di
f
i
e
d
Di
j
ks
t
r
a
m
e
t
h
ods
.
Am
o
n
g
t
h
e
c
o
m
po
n
e
n
t
s
e
x
a
m
i
n
e
d
we
r
e
s
t
a
t
i
c
or
s
i
n
g
l
e
-
c
r
i
t
e
r
i
o
n
r
o
u
t
e
s
t
h
a
t
p
r
o
v
i
de
d
r
e
a
l
-
t
i
m
e
t
r
a
f
f
i
c
r
e
s
p
o
n
s
e
s
b
y
o
p
t
i
m
i
z
i
n
g
a
da
p
t
i
v
e
we
i
gh
t
s
-
s
pe
c
i
f
i
c
a
l
l
y
d
i
s
t
a
n
c
e
,
t
i
m
e
,
c
o
n
ge
s
t
i
o
n
,
a
n
d
c
o
s
t.
Ne
x
t
i
s
i
m
pr
o
vi
n
g
t
h
e
r
e
s
p
o
n
s
i
v
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De
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
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hn
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I
S
S
N:
2252
-
8776
A
dapti
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r
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2
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1.
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8776
I
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3
1932
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kor
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l
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1
[
35]
,
[
36]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
I
n
f
&
C
o
m
m
u
n
T
e
c
hn
o
l
I
S
S
N:
2252
-
8776
A
dapti
v
e
w
e
ight
e
d
multi
-
c
r
it
e
r
ia
de
c
is
ion
mak
ing
us
ing
modif
ied
dij
k
s
tr
a’
s
algor
it
hm
…
(
B
as
or
udi
n
)
1933
Al
go
r
i
t
hm
1.
M
o
di
f
i
e
d
D
ijk
st
r
a
wi
t
h
hy
br
i
d
W
S
M
-
W
P
M
f
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r
dy
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m
i
c
r
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e
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p
t
i
mi
z
a
t
i
o
n
Input: G = (V, E)
—
weighted graph; source s; destination d;
criteria weights W = {w_dist, w_time, w_cong, w_safe};
hybrid parameter λ
∈
[0,1]; real
-
time traffic data T
Output: Optima
l
path P* and composite score Score*
1. W ← AdaptiveWeights(T, W) // Adjust weights by traffic conditions
2. dist[v] ← ∞ for all v
∈
V; dist[s] ← 0
3. PQ ← MinPriorityQueue(); PQ.insert(s, 0)
4. WHILE PQ is not empty DO
5. u ← PQ.extract
Mi
n()
6. IF u = d THEN BREAK
7. FOR each neighbor v of u DO
8. C(u,v) ← GetRealTimeCriteria(u, v, T) // {dist, time, cong, safe}
9. C_norm ← Normalize(C(u,v)) // Min
-
max normalization per criterion
10. WSM_score ←
Σ
(W
[j] × C_norm[j]) // Eq. (1)
11. WPM_score ← Π(C_norm[j]^W[j]) // Eq. (2)
12. edge_cost ← λ × WSM_score + (1
-
λ) × WPM_score // Eq. (3)
13. alt ← dist[u] + edge_cost
14. IF alt < dist[v] THEN
15. dist[v
]
← alt; prev[v] ← u
16. PQ.decreaseKey(v, alt)
17. END IF
18. END FOR
19. END WHILE
20. P* ← ReconstructPath(prev, s, d); RETURN P*, dist[d]
Al
go
r
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t
hm
1
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o
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l
p
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(
P*
)
t
h
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t
b
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s
d
i
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tr
a
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.
3.
RE
S
UL
T
S
AN
D
DI
S
CU
S
S
I
ON
3.
1.
Ne
t
wor
k
vis
u
a
l
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z
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ion
wit
h
o
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im
al
p
at
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F
i
gur
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s
h
o
ws
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t
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t
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o
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t
wor
k
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t
h
14
n
o
de
s
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h
e
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m
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pa
t
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o
un
d
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ng
m
o
d
i
f
i
e
d
D
i
j
ks
t
r
a
wi
t
h
h
y
br
i
d
W
S
M
-
W
P
M
.
T
h
e
o
p
t
i
m
a
l
p
a
t
h
i
de
n
t
i
f
i
e
d
i
s
:
V1
→
V2
→
V5
→
V8
→
V12
→
V14
w
i
t
h
a
tot
a
l
d
i
s
t
a
n
c
e
o
f
22.
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k
m
a
n
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a
tr
a
v
e
l
t
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m
e
o
f
25
m
i
n
ut
e
s
.
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i
gur
e
3
.
M
o
di
f
i
e
d
D
ij
ks
t
r
a
+
Hy
b
r
i
d
W
S
M
-
W
P
M
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
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8776
I
n
t
J
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l
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4
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D
e
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m
be
r
20
2
6
:
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194
3
1934
3.
2.
Com
p
ar
is
on
of
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t
im
i
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m
e
t
h
od
s
F
ur
t
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m
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r
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i
gur
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4
pr
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ly
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t
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o
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t
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f
f
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s
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i
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l
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m
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ds
.
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h
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e
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m
o
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d
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i
j
k
s
t
r
a
(
h
y
b
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i
d
W
S
M
-
W
P
M
)
w
i
t
h
P
a
t
h
:
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2→V5→V
8→V12→V
14
wi
t
h
a
s
c
o
r
e
o
f
19.
4906,
s
t
a
n
da
r
d
Di
j
k
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r
a
(
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s
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a
n
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o
nl
y
)
,
wi
t
h
P
a
t
h
:
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2→V5→V
8→V12→V
14
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t
h
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f
22.
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h
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nl
y
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wi
t
h
P
a
t
h
:
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2→V5→V
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i
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0000,
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=
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t
h
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t
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3.
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igh
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c
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igu
r
at
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it
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y
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al
ys
is
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ne
x
t
s
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y
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s
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v
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l
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s
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g
f
i
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g
h
t
c
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nf
i
gur
a
t
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o
ns
t
o
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p
l
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h
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e
f
f
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t
o
f
c
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r
i
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n
pr
i
o
r
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s
o
n
t
h
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o
p
t
i
mi
z
a
t
i
o
n
r
e
s
u
l
t
s
,
a
s
s
h
o
wn
i
n
po
i
n
t
s
1
to
5.
a)
S
h
o
ws
d
i
s
t
a
nc
e
pr
i
o
r
i
t
y
(w
d
=
0.
6,
w
t
=
0.
2,
w
c
=
0.
1,
w
s
=
0.
1)
.
b)
S
h
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ws
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i
m
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pr
i
o
r
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y
(w
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w
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1,
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c)
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w
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,
w
c
=0
.
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.
d)
I
n
d
i
c
a
t
e
s
c
o
n
ge
s
t
i
o
n
a
v
o
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t
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c
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s
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.
e)
I
n
d
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s
b
a
l
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e
d
s
t
a
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,
w
t
=
0.
25
,
w
c
=
0.
25,
w
s
=
0.
25)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
I
n
f
&
C
o
m
m
u
n
T
e
c
hn
o
l
I
S
S
N:
2252
-
8776
A
dapti
v
e
w
e
ight
e
d
multi
-
c
r
it
e
r
ia
de
c
is
ion
mak
ing
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ied
dij
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s
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a’
s
algor
it
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…
(
B
as
or
udi
n
)
1935
T
h
e
c
o
nf
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gur
a
t
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f
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l
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o
w
i
ng
a
l
t
e
r
n
a
t
i
v
e
r
out
e
(
V1→V
3→V6→V
9→V12→V
14)
wi
t
h
a
l
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n
g
e
r
di
s
t
a
nc
e
(
43.
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km
)
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gur
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o
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s
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a
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t
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s
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s
.
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ll
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m
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t
r
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s
t
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pr
o
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d
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i
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br
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M
–
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P
M
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r
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m
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k
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s
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t
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we
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g
h
t
a
dj
u
s
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s
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e
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f
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c
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o
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r
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l
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d
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s
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t
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s
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pr
o
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y
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o
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t
i
o
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d
y
na
mi
c
r
o
a
d
n
e
two
r
ks
.
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i
gur
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.
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e
n
s
i
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i
vi
t
y
a
n
a
ly
s
i
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t
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e
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m
pa
c
t
o
f
we
i
g
h
t
c
o
n
f
i
gur
a
t
i
o
n
o
n
r
o
u
t
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o
p
t
i
mi
z
a
t
i
o
n
I
n
t
h
e
s
i
m
u
l
a
t
i
o
n
,
we
us
e
d
24
h
o
ur
s
wi
t
h
a
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t
a
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d
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r
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,
whi
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r
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a
n
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o
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gr
a
t
i
n
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r
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a
l
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n
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o
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n
a
vi
ga
t
i
o
n
s
y
s
t
e
m
.
Guo
e
t
al
.
[
26
]
t
r
a
v
e
l
t
i
me
dur
i
n
g
pe
a
k
h
o
ur
s
a
t
8:00
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.
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.
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a
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r
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a
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m
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nut
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s
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r
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7
]
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n
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5:00
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.
An
d
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ur
t
i
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t
al.
[
28
]
o
p
t
i
m
a
l
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r
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9:00
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r
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[
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t
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s
[
29
]
t
h
e
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s
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e
m
a
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[
30
]
t
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