Estimating the Railway Network Capacity Utilization with Mixed Train Routes and Stopping Patterns: A Multiobjective Optimization Approach

Table 5

Computational performance comparison between Gurobi and LR heuristic (100 iterations) without -constraint.

Instance	Init. obj. (# trains)		Best obj. (# trains)		Opt. gap (%)		Computational time (sec)
	Gurobi	LR heuristic	Gurobi	LR heuristic	Gurobi	LR heuristic	Gurobi	LR heuristic
HSR-60	31	30	31	31	0.00	1.33	7	72
HSR-120	61	60	60	60	0.00	5.62	88	141
HSR-180	92	86	92	91	0.81	6.90	300	205
HSR-240	—	136	—	142	—	19.32	300	281
HSR-300	—	161	—	174	—	33.16	300	300
IC-60	48	40	48	46	0.00	3.32	13	84
IC-120	89	85	89	92	7.35	4.86	107	172
IC-180	—	131	—	138	—	13.88	300	257
IC-240	—	157	—	172	—	26.90	300	300
IC-300	—	216	—	230	—	38.52	300	300

—: cannot get any nonzero feasible solution within 300 seconds.