A Simulated Annealing Approach for the Train Design Optimization Problem

Table 6

Average results—objective function value rounded to nearest integer—of ten runs for instance Data Set 2. Time shown in seconds and italics.

	0.70	0.75	0.80	0.85	0.90	0.95	0.99
500	3,209,687	3,210,058	3,212,176	3,209,065	3,205,954	3,195,864	3,185,775
	2,790	2,226	2,446	2,666	2,783	3,934	10,877
1,000	3,205,775	3,204,303	3,203,858	3,200,948	3,201,772	3,191,151	3,184,551
	2,459	2,593	2,771	3,351	4,259	5,181	19,899
1,500	3,200,260	3,201,520	3,192,792	3,190,837	3,187,281	3,190,916	3,173,312
	2,605	2,634	2,901	3,450	4,355	7,264	29,082
2,000	3,201,157	3,196,194	3,192,166	3,195,499	3,188,878	3,188,311	3,175,760
	3,070	2,890	2,540	4,332	4,997	9,066	36,945
4,000	3,195,857	3,187,514	3,187,182	3,185,158	3,184,931	3,176,745	3,173,650
	3,808	4,771	5,339	6,844	8,904	16,043	76,952
6,000	3,192,045	3,189,039	3,185,947	3,180,655	3,181,356	3,175,733	3,169,176
	5,857	5,976	7,398	8,711	16,026	25,530	116,304
8,000	3,188,106	3,185,158	3,184,032	3,181,325	3,179,988	3,172,099	3,167,935
	6,741	6,844	9,216	12,206	18,319	37,695	153,931
10,000	3,186,663	3,184,824	3,182,085	3,178,864	3,176,411	3,168,984	3,164,844
	7,466	8,622	10,846	14,772	21,081	42,862	218,506