Train Scheduling Optimization for an Urban Rail Transit Line: A Simulated-Annealing Algorithm Using a Large Neighborhood Search Metaheuristic

Table 3

Comparison of values under an optimized irregular schedule and the current regular schedule.

Station index	Length (m)	DT1 (s)	DT2 (s)	Gap1 (%)	LR1	LR2	Gap3 (%)
1	657	40	38	−5.0	0.173	0.171	−1.2
2	1361	30	28	−6.7	0.380	0.375	−1.3
3	857	35	32	−8.6	0.506	0.498	−1.6
4	1425	35	34	−2.9	0.578	0.561	−2.9
5	1602	55	58	+5.5	0.872	0.844	−3.2
6	1744	30	29	−3.3	0.818	0.789	−3.5
7	1146	50	48	−4.0	0.802	0.775	−3.4
8	1074	30	26	−13.3	0.774	0.746	−3.6
9	1303	35	33	−5.7	0.749	0.725	−3.2
10	1587	45	42	−6.7	0.647	0.629	−2.8
11	1183	30	29	−3.3	0.632	0.613	−3.0
12	1085	30	28	−6.7	0.625	0.606	−3.0
13	874	30	30	0	0.588	0.569	−3.2
14	1199	45	41	−8.9	0.605	0.587	−3.0
15	860	30	29	−3.3	0.593	0.574	−3.2
16	1023	30	28	−6.7	0.560	0.541	−3.4
17	1435	40	37	−7.5	0.541	0.523	−3.3
18	1908	30	27	−10.0	0.487	0.472	−3.1
19	6924	50	46	−8.0	0.629	0.611	−2.9
20	1784	35	33	−5.7	0.507	0.489	−3.6
21	3361	25	23	−8.0	0.455	0.440	−3.3
22	1894	30	29	−3.3	0.401	0.389	−3.0
23	1540	40	35	−12.5	0.329	0.319	−3.0
24	5895	30	28	−6.7	0.186	0.181	−2.7
25	437	40	37	−7.5	—	—	—
SUM	44158	900	848	−5.8	—	—	—