Equity-Oriented Train Timetabling with Collaborative Passenger Flow Control: A Spatial Rebalance of Service on an Oversaturated Urban Rail Transit Line
Table 4
Performance comparison of Gurobi and TS + Gurobi
Instances
Method
Objective
CPU time (s)
Gap (%)
I-60-10
Gurobi
0.4954
2.3
—
TS + Gurobi
0.4954
36.0
0.00
I-60-16
Gurobi
0.5174
59.5
—
TS + Gurobi
0.5196
142.1
0.43
I-120-10
Gurobi
0.4721
30.4
—
TS + Gurobi
0.4724
43.9
0.06
I-120-16
Gurobi
0.4230
2300.3
—
TS + Gurobi
0.4233
247.3
0.07
I-180-13
Gurobi
0.3578
3600/36.2%
—
TS + Gurobi
0.3330
76.5
−6.93
I-240-13
Gurobi
0.4596
3600/44.4%
—
TS + Gurobi
0.3935
99.4
−14.38
I-240-16
Gurobi
0.5617
3600/54.2%
—
TS + Gurobi
0.3882
192.7
−30.89
I-240-19
Gurobi
0.8901
3600/45.9%
—
TS + Gurobi
0.7809
442.7
−12.27
The value with is the MIPGap of Gurobi solver in a given time limit 3600 s. MIPGap is an internal index of the Gurobi solver that evaluates the relative difference of the current solution with the possible optimal solution. The gap is calculated by .).
