Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks
Table 2
Computational results and evaluation of routing plans in 4 delivery scenarios.
Instance specification
Vehicle number
Schedule timeb
Travel time
Failure number
Failure
CPU times (s)
Scenario
Number of Customers
Model
ratec
1
25
TD
4
43.76
22.44
5.5
22%
5.55
STD
5
47.35
23.61
0
0
5.27
25.00%
8.20%
5.21%
None
−22%
−5%
2
50
TD
7
60.24
29.98
11.4
22.8%
19.63
STD
9
65.62
31.20
0
0
17.08
28.57%
8.93%
4.07%
None
−22.8%
−13%
3
100
TD
15
116.97
47.98
20.3
20.3%
71.11
STD
17
126.89
53.25
0
0
66.58
13.33%
8.48%
10.98%
None
−20.3%
−6%
4
150
TD
20
179.15
88.61
31.4
20.9%
148.38
STD
23
202.99
98.08
0
0
137.88
15.00%
13.31%
10.69%
None
−20.9%
−7%
indicates relative percentage change between the two tests. bTotal schedule time is the sum of total travel time (TT), total waiting time (WT), and total service time (SVT). cFailure rate = failure number/number of customers.