| Asset-balanced network design |
Results for R
Instances |
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| Lowe Bound / Upper Bound |
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| Year |
2017 |
2017 |
2009 |
2009 |
2011 |
2013 |
2015 |
2015 |
2016 |
2018 |
2018 |
|
| Problem |
Optimal/ Lower Bound/ Giurobi7/ 60h |
Upper Bound/ Giurobi7/ 60h |
Tabu Search |
Parallel Tabu Search |
MIP Tabu Search |
Three-Stage Metaheuristic |
Capacity Scaling and Restricted Branch-and-Bound
Matheuristic |
Capacity Scaling and Local Branch Matheuristic |
Cutting-Plane Matheuristic |
Capacity Scaling and MIP Neighborhood Search |
Capacity Scaling and MIP Neighborhood Search Tuned |
|
| r13.1 |
147349 |
147349 |
147837 |
147349 |
148494 |
147349 |
147349 |
147349 |
148494 |
147349 |
147349 |
|
| r13.2 |
277891 |
277891 |
281668 |
281668 |
281087 |
279389 |
277891 |
277891 |
298494 |
277891 |
277891 |
|
| r13.3 |
385396 |
385396 |
404434 |
400656 |
403596 |
385396 |
388408 |
385396 |
417877 |
385396 |
385396 |
|
| r13.4 |
155887 |
155887 |
159852 |
156585 |
155887 |
156616 |
156386 |
155887 |
155887 |
155887 |
155887 |
|
| r13.5 |
295180 |
295180 |
311209 |
307180 |
301729 |
295180 |
296556 |
295180 |
298582 |
295480 |
295180 |
|
| r13.6 |
431140 |
431140 |
470034 |
437396 |
442410 |
434383 |
433117 |
431140 |
454625 |
432424 |
431140 |
|
| r13.7 |
218787 |
218787 |
225339 |
223541 |
219975 |
218787 |
221091 |
218787 |
224632 |
218787 |
218787 |
|
| r13.8 |
491560 |
491560 |
512027 |
510887 |
497325 |
492959 |
495090 |
491603 |
497877 |
491603 |
491560 |
|
| r13.9 |
782049 |
782049 |
875984 |
839174 |
792096 |
791213 |
796897 |
782049 |
798947 |
782049 |
782049 |
|
| r14.1 |
422709 |
422709 |
431562 |
427872 |
423538 |
422709 |
422709 |
422709 |
423538 |
422709 |
422709 |
|
| r14.2 |
784626 |
784626 |
811102 |
811102 |
797767 |
784626 |
785754 |
784626 |
812423 |
784626 |
784626 |
|
| r14.3 |
1119569 |
1119569 |
1193950 |
1157500 |
1207090 |
1137820 |
1126879 |
1120185 |
1156950 |
1120185 |
1120185 |
|
| r14.4 |
452591 |
452591 |
465762 |
458240 |
455054 |
453434 |
452591 |
452591 |
457421 |
452997 |
452591 |
|
| r14.5 |
883051 |
883051 |
942678 |
917832 |
890673 |
891138 |
887334 |
883051 |
890673 |
884673 |
883051 |
|
| r14.6 |
1296477 |
1296477 |
1401880 |
1356910 |
1308890 |
1307770 |
1303528 |
1296477 |
1336490 |
1296477 |
1296477 |
|
| r14.7 |
702614 |
702614 |
720882 |
720494 |
706661 |
702614 |
704203 |
702614 |
708444 |
702781 |
702614 |
|
| r14.8 |
1688981 |
1688981 |
1795650 |
1795650 |
1708510 |
1693240 |
1692473 |
1688981 |
1706840 |
1697260 |
1689942 |
|
| r14.9 |
2755700 |
2755700 |
2997290 |
2997290 |
2804980 |
2769360 |
2786173 |
2755700 |
2772750 |
2791988 |
2763803 |
|
| r15.1 |
1017740 |
1017740 |
1039440 |
1032640 |
1020910 |
1017740 |
1018193 |
1017740 |
1019180 |
1018166 |
1017740 |
|
| r15.2 |
2008206 |
2008206 |
2170310 |
2082990 |
2023750 |
2055803 |
2012100 |
2008206 |
2028140 |
2017550 |
2011260 |
|
| r15.3 |
2958161 |
2958161 |
3194270 |
3116770 |
3003990 |
2971500 |
2985328 |
2966146 |
3003990 |
2985536 |
2958161 |
|
| r15.4 |
1174518 |
1174518 |
1205790 |
1191440 |
1176990 |
1174520 |
1174959 |
1174518 |
1182020 |
1175476 |
1174518 |
|
| r15.5 |
2553657 |
2553657 |
2698680 |
2698680 |
2581910 |
2561060 |
2553657 |
2553657 |
2574700 |
2558238 |
2557434 |
|
| r15.6 |
4010444 |
4010444 |
4447950 |
4310340 |
4121320 |
4045030 |
4041669 |
4010444 |
4176330 |
4091074 |
4048109 |
|
| r15.7 |
2401115 |
2401115 |
2472860 |
2465650 |
2403970 |
2408210 |
2402126 |
2401115 |
2403330 |
2405234 |
2403384 |
|
| r15.8 |
5795320 |
5795320 |
6067350 |
5969370 |
5797170 |
5796510 |
5797171 |
5795320 |
5797170 |
5810709 |
5795320 |
|
| r15.9 |
9105014 |
9105014 |
10263600 |
9304650 |
9115830 |
9129360 |
9105014 |
9105014 |
9115830 |
9105954 |
9105954 |
|
| r16.1 |
140082 |
140082 |
142692 |
140149 |
140787 |
140082 |
140082 |
140082 |
142797 |
140082 |
140082 |
|
| r16.2 |
248703 |
248703 |
261775 |
261775 |
261049 |
248703 |
253681 |
248703 |
277712 |
248703 |
248703 |
|
| r16.3 |
340641 |
340641 |
374819 |
360884 |
349476 |
350958 |
348522 |
340641 |
359648 |
340641 |
340641 |
|
| r16.4 |
142381 |
142381 |
145266 |
143921 |
143689 |
142605 |
142507 |
142381 |
159168 |
142381 |
142381 |
|
| r16.5 |
259313 |
259313 |
277307 |
273024 |
271795 |
260822 |
259313 |
259313 |
285509 |
259313 |
259313 |
|
| r16.6 |
361626 |
361626 |
391386 |
387601 |
376019 |
368572 |
367947 |
361626 |
376114 |
363999 |
361626 |
|
| r16.7 |
179639 |
179639 |
187176 |
185397 |
181216 |
180228 |
184624 |
179639 |
183475 |
179639 |
179639 |
|
| r16.8 |
387360 |
387360 |
423320 |
419945 |
392189 |
388180 |
394679 |
387360 |
393541 |
387360 |
387360 |
|
| r16.9 |
596660 |
596660 |
649121 |
647212 |
610267 |
598835 |
612353 |
596660 |
610267 |
603278 |
596660 |
|
| r17.1 |
364784 |
364784 |
374016 |
365913 |
367439 |
365788 |
364784 |
364784 |
368841 |
364784 |
364784 |
|
| r17.2 |
675029 |
675029 |
718135 |
702957 |
707822 |
676528 |
678282 |
675029 |
717089 |
675294 |
675294 |
|
| r17.3 |
947172 |
947172 |
1041450 |
1026040 |
1045940 |
966116 |
969046 |
947172 |
991205 |
967888 |
950018 |
|
| r17.4 |
382593 |
382593 |
393608 |
389249 |
385807 |
384579 |
383076 |
382593 |
388625 |
382593 |
382593 |
|
| r17.5 |
734117 |
734117 |
786198 |
786198 |
740298 |
741744 |
738944 |
734117 |
744146 |
734117 |
734117 |
|
| r17.6 |
1066292 |
1066292 |
1162290 |
1159440 |
1105240 |
1086640 |
1066292 |
1066292 |
1126380 |
1077972 |
1066292 |
|
| r17.7 |
528923 |
528923 |
539817 |
539817 |
535474 |
529876 |
529395 |
528923 |
535474 |
529877 |
528923 |
|
| r17.8 |
1222318 |
1222318 |
1348750 |
1323330 |
1229770 |
1230910 |
1228640 |
1224001 |
1241990 |
1225838 |
1224044 |
|
| r17.9 |
1995845 |
1995845 |
2227780 |
2207590 |
2036760 |
1999950 |
2007426 |
1996006 |
2064630 |
2000323 |
2000323 |
|
| r18.1 |
844211 |
844211 |
864425 |
864425 |
845748 |
844260 |
846124 |
844211 |
848636 |
849559 |
844211 |
|
| r18.2 |
1572707 |
1572707 |
1640200 |
1627700 |
1615730 |
1588890 |
1575173 |
1572707 |
1615730 |
1590858 |
1574191 |
|
| r18.3 |
2229722 |
2229722 |
2399230 |
2366280 |
2280820 |
2264470 |
2258224 |
2229722 |
2286290 |
2255415 |
2233090 |
|
| r18.4 |
940628 |
940628 |
962402 |
962402 |
947131 |
944708 |
942127 |
940628 |
945562 |
942127 |
941527 |
|
| r18.5 |
1871293 |
1871293 |
1958160 |
1958160 |
1909340 |
1883870 |
1879801 |
1873989 |
1904830 |
1875827 |
1872996 |
|
| r18.6 |
2766158 |
2789018 |
2986000 |
2986000 |
2810300 |
2806020 |
2801704 |
2793317 |
2809030 |
2799565 |
2792629 |
|
| r18.7 |
1532002 |
1532002 |
1617320 |
1613790 |
1537320 |
1542500 |
1535768 |
1533403 |
1547430 |
1538544 |
1537152 |
|
| r18.8 |
3961277 |
3961277 |
4268580 |
4268580 |
3961280 |
4039410 |
3974512 |
3961277 |
3961280 |
4010652 |
3986083 |
|
| r18.9 |
6550763 |
6550763 |
7440780 |
7194120 |
6618400 |
6603500 |
6579400 |
6554029 |
6602450 |
6597654 |
6589950 |
|
| Average |
1428851 |
1429275 |
1542433 |
1505218 |
1448124 |
1438934 |
1435687 |
1429685 |
1450916 |
1436903 |
1431995 |
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|
| Gaps(%) |
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|
| Problem |
Optimal/
Lower Bound/ Giurobi7/ 60h |
Upper Bound/
Giurobi7/ 60h |
Tabu Search |
Parallel
Tabu Search |
MIP Tabu
Search |
Three-Stage
Metaheuristic |
Capacity
Scaling and Restricted Branch-and-Bound Matheuristic |
Capacity
Scaling and Local Branch Matheuristic |
Cutting-Plane
Matheuristic |
Capacity
Scaling and MIP Neighborhood Search |
Capacity
Scaling and MIP Neighborhood Search Tuned |
|
| r13.1 |
|
0.00% |
0.33% |
0.00% |
0.78% |
0.00% |
0.00% |
0.00% |
0.78% |
0.00% |
0.00% |
|
| r13.2 |
|
0.00% |
1.36% |
1.36% |
1.15% |
0.54% |
0.00% |
0.00% |
7.41% |
0.00% |
0.00% |
|
| r13.3 |
|
0.00% |
4.94% |
3.96% |
4.72% |
0.00% |
0.78% |
0.00% |
8.43% |
0.00% |
0.00% |
|
| r13.4 |
|
0.00% |
2.54% |
0.45% |
0.00% |
0.47% |
0.32% |
0.00% |
0.00% |
0.00% |
0.00% |
|
| r13.5 |
|
0.00% |
5.43% |
4.07% |
2.22% |
0.00% |
0.47% |
0.00% |
1.15% |
0.10% |
0.00% |
|
| r13.6 |
|
0.00% |
9.02% |
1.45% |
2.61% |
0.75% |
0.46% |
0.00% |
5.45% |
0.30% |
0.00% |
|
| r13.7 |
|
0.00% |
2.99% |
2.17% |
0.54% |
0.00% |
1.05% |
0.00% |
2.67% |
0.00% |
0.00% |
|
| r13.8 |
|
0.00% |
4.16% |
3.93% |
1.17% |
0.28% |
0.72% |
0.01% |
1.29% |
0.01% |
0.00% |
|
| r13.9 |
|
0.00% |
12.01% |
7.30% |
1.28% |
1.17% |
1.90% |
0.00% |
2.16% |
0.00% |
0.00% |
|
| r14.1 |
|
0.00% |
2.09% |
1.22% |
0.20% |
0.00% |
0.00% |
0.00% |
0.20% |
0.00% |
0.00% |
|
| r14.2 |
|
0.00% |
3.37% |
3.37% |
1.67% |
0.00% |
0.14% |
0.00% |
3.54% |
0.00% |
0.00% |
|
| r14.3 |
|
0.00% |
6.64% |
3.39% |
7.82% |
1.63% |
0.65% |
0.06% |
3.34% |
0.06% |
0.06% |
|
| r14.4 |
|
0.00% |
2.91% |
1.25% |
0.54% |
0.19% |
0.00% |
0.00% |
1.07% |
0.09% |
0.00% |
|
| r14.5 |
|
0.00% |
6.75% |
3.94% |
0.86% |
0.92% |
0.49% |
0.00% |
0.86% |
0.18% |
0.00% |
|
| r14.6 |
|
0.00% |
8.13% |
4.66% |
0.96% |
0.87% |
0.54% |
0.00% |
3.09% |
0.00% |
0.00% |
|
| r14.7 |
|
0.00% |
2.60% |
2.54% |
0.58% |
0.00% |
0.23% |
0.00% |
0.83% |
0.02% |
0.00% |
|
| r14.8 |
|
0.00% |
6.32% |
6.32% |
1.16% |
0.25% |
0.21% |
0.00% |
1.06% |
0.49% |
0.06% |
|
| r14.9 |
|
0.00% |
8.77% |
8.77% |
1.79% |
0.50% |
1.11% |
0.00% |
0.62% |
1.32% |
0.29% |
|
| r15.1 |
|
0.00% |
2.13% |
1.46% |
0.31% |
0.00% |
0.04% |
0.00% |
0.14% |
0.04% |
0.00% |
|
| r15.2 |
|
0.00% |
8.07% |
3.72% |
0.77% |
2.37% |
0.19% |
0.00% |
0.99% |
0.47% |
0.15% |
|
| r15.3 |
|
0.00% |
7.98% |
5.36% |
1.55% |
0.45% |
0.92% |
0.27% |
1.55% |
0.93% |
0.00% |
|
| r15.4 |
|
0.00% |
2.66% |
1.44% |
0.21% |
0.00% |
0.04% |
0.00% |
0.64% |
0.08% |
0.00% |
|
| r15.5 |
|
0.00% |
5.68% |
5.68% |
1.11% |
0.29% |
0.00% |
0.00% |
0.82% |
0.18% |
0.15% |
|
| r15.6 |
|
0.00% |
10.91% |
7.48% |
2.76% |
0.86% |
0.78% |
0.00% |
4.14% |
2.01% |
0.94% |
|
| r15.7 |
|
0.00% |
2.99% |
2.69% |
0.12% |
0.30% |
0.04% |
0.00% |
0.09% |
0.17% |
0.09% |
|
| r15.8 |
|
0.00% |
4.69% |
3.00% |
0.03% |
0.02% |
0.03% |
0.00% |
0.03% |
0.27% |
0.00% |
|
| r15.9 |
|
0.00% |
12.72% |
2.19% |
0.12% |
0.27% |
0.00% |
0.00% |
0.12% |
0.01% |
0.01% |
|
| r16.1 |
|
0.00% |
1.86% |
0.05% |
0.50% |
0.00% |
0.00% |
0.00% |
1.94% |
0.00% |
0.00% |
|
| r16.2 |
|
0.00% |
5.26% |
5.26% |
4.96% |
0.00% |
2.00% |
0.00% |
11.66% |
0.00% |
0.00% |
|
| r16.3 |
|
0.00% |
10.03% |
5.94% |
2.59% |
3.03% |
2.31% |
0.00% |
5.58% |
0.00% |
0.00% |
|
| r16.4 |
|
0.00% |
2.03% |
1.08% |
0.92% |
0.16% |
0.09% |
0.00% |
11.79% |
0.00% |
0.00% |
|
| r16.5 |
|
0.00% |
6.94% |
5.29% |
4.81% |
0.58% |
0.00% |
0.00% |
10.10% |
0.00% |
0.00% |
|
| r16.6 |
|
0.00% |
8.23% |
7.18% |
3.98% |
1.92% |
1.75% |
0.00% |
4.01% |
0.66% |
0.00% |
|
| r16.7 |
|
0.00% |
4.20% |
3.21% |
0.88% |
0.33% |
2.78% |
0.00% |
2.14% |
0.00% |
0.00% |
|
| r16.8 |
|
0.00% |
9.28% |
8.41% |
1.25% |
0.21% |
1.89% |
0.00% |
1.60% |
0.00% |
0.00% |
|
| r16.9 |
|
0.00% |
8.79% |
8.47% |
2.28% |
0.36% |
2.63% |
0.00% |
2.28% |
1.11% |
0.00% |
|
| r17.1 |
|
0.00% |
2.53% |
0.31% |
0.73% |
0.28% |
0.00% |
0.00% |
1.11% |
0.00% |
0.00% |
|
| r17.2 |
|
0.00% |
6.39% |
4.14% |
4.86% |
0.22% |
0.48% |
0.00% |
6.23% |
0.04% |
0.04% |
|
| r17.3 |
|
0.00% |
9.95% |
8.33% |
10.43% |
2.00% |
2.31% |
0.00% |
4.65% |
2.19% |
0.30% |
|
| r17.4 |
|
0.00% |
2.88% |
1.74% |
0.84% |
0.52% |
0.13% |
0.00% |
1.58% |
0.00% |
0.00% |
|
| r17.5 |
|
0.00% |
7.09% |
7.09% |
0.84% |
1.04% |
0.66% |
0.00% |
1.37% |
0.00% |
0.00% |
|
| r17.6 |
|
0.00% |
9.00% |
8.74% |
3.65% |
1.91% |
0.00% |
0.00% |
5.64% |
1.10% |
0.00% |
|
| r17.7 |
|
0.00% |
2.06% |
2.06% |
1.24% |
0.18% |
0.09% |
0.00% |
1.24% |
0.18% |
0.00% |
|
| r17.8 |
|
0.00% |
10.34% |
8.26% |
0.61% |
0.70% |
0.52% |
0.14% |
1.61% |
0.29% |
0.14% |
|
| r17.9 |
|
0.00% |
11.62% |
10.61% |
2.05% |
0.21% |
0.58% |
0.01% |
3.45% |
0.22% |
0.22% |
|
| r18.1 |
|
0.00% |
2.39% |
2.39% |
0.18% |
0.01% |
0.23% |
0.00% |
0.52% |
0.63% |
0.00% |
|
| r18.2 |
|
0.00% |
4.29% |
3.50% |
2.74% |
1.03% |
0.16% |
0.00% |
2.74% |
1.15% |
0.09% |
|
| r18.3 |
|
0.00% |
7.60% |
6.12% |
2.29% |
1.56% |
1.28% |
0.00% |
2.54% |
1.15% |
0.15% |
|
| r18.4 |
|
0.00% |
2.31% |
2.31% |
0.69% |
0.43% |
0.16% |
0.00% |
0.52% |
0.16% |
0.10% |
|
| r18.5 |
|
0.00% |
4.64% |
4.64% |
2.03% |
0.67% |
0.45% |
0.14% |
1.79% |
0.24% |
0.09% |
|
| r18.6 |
|
0.83% |
7.95% |
7.95% |
1.60% |
1.44% |
1.29% |
0.98% |
1.55% |
1.21% |
0.96% |
|
| r18.7 |
|
0.00% |
5.57% |
5.34% |
0.35% |
0.69% |
0.25% |
0.09% |
1.01% |
0.43% |
0.34% |
|
| r18.8 |
|
0.00% |
7.76% |
7.76% |
0.00% |
1.97% |
0.33% |
0.00% |
0.00% |
1.25% |
0.63% |
|
| r18.9 |
|
0.00% |
13.59% |
9.82% |
1.03% |
0.81% |
0.44% |
0.05% |
0.79% |
0.72% |
0.60% |
|
| Average |
|
0.02% |
5.98% |
4.43% |
1.77% |
0.64% |
0.63% |
0.03% |
2.63% |
0.36% |
0.10% |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| Computation
Time (seconds) |
|
|
|
|
|
|
|
|
|
|
|
| Problem |
Optimal/
Lower Bound/ Giurobi7/ 60h |
Upper Bound/
Giurobi7/ 60h |
Tabu Search |
Parallel
Tabu Search |
MIP Tabu
Search |
Three-Stage
Metaheuristic |
Capacity
Scaling and Restricted Branch-and-Bound Matheuristic |
Capacity
Scaling and Local Branch Matheuristic |
Cutting-Plane
Matheuristic |
Capacity
Scaling and MIP Neighborhood Search |
Capacity
Scaling and MIP Neighborhood Search Tuned |
|
| r13.1 |
0 |
0 |
3600 |
3600 |
3600 |
3720 |
|
|
1 |
1 |
1 |
|
| r13.2 |
9 |
9 |
3600 |
3600 |
3600 |
3780 |
|
|
39 |
35 |
29 |
|
| r13.3 |
12 |
12 |
3600 |
3600 |
3600 |
3780 |
|
|
57 |
69 |
37 |
|
| r13.4 |
3 |
3 |
3600 |
3600 |
3600 |
3720 |
|
|
2 |
6 |
2 |
|
| r13.5 |
14 |
14 |
3600 |
3600 |
3600 |
3780 |
|
|
38 |
45 |
35 |
|
| r13.6 |
262 |
262 |
3600 |
3600 |
3600 |
3780 |
|
|
44 |
152 |
99 |
|
| r13.7 |
42 |
42 |
3600 |
3600 |
3600 |
3720 |
|
|
6 |
87 |
55 |
|
| r13.8 |
1231 |
1231 |
3600 |
3600 |
3600 |
4260 |
|
|
14 |
248 |
190 |
|
| r13.9 |
424 |
424 |
3600 |
3600 |
3600 |
3780 |
|
|
21 |
250 |
189 |
|
| r14.1 |
9 |
9 |
3600 |
3600 |
3600 |
4140 |
|
|
21 |
24 |
14 |
|
| r14.2 |
297 |
297 |
3600 |
3600 |
3600 |
3900 |
|
|
251 |
129 |
123 |
|
| r14.3 |
4844 |
4844 |
3600 |
3600 |
3600 |
4380 |
|
|
3672 |
295 |
210 |
|
| r14.4 |
14 |
14 |
3600 |
3600 |
3600 |
3900 |
|
|
20 |
27 |
19 |
|
| r14.5 |
2744 |
2744 |
3600 |
3600 |
3600 |
5700 |
|
|
121 |
262 |
435 |
|
| r14.6 |
12133 |
12133 |
3600 |
3600 |
3600 |
5100 |
|
|
243 |
348 |
271 |
|
| r14.7 |
197 |
197 |
3600 |
3600 |
3600 |
6420 |
|
|
33 |
195 |
169 |
|
| r14.8 |
13106 |
13106 |
3600 |
3600 |
3600 |
6480 |
|
|
434 |
299 |
443 |
|
| r14.9 |
3529 |
3529 |
3600 |
3600 |
3600 |
10140 |
|
|
545 |
331 |
410 |
|
| r15.1 |
169 |
169 |
3600 |
3600 |
3600 |
4020 |
|
|
159 |
141 |
194 |
|
| r15.2 |
17333 |
17333 |
3600 |
3600 |
3600 |
6840 |
|
|
1199 |
320 |
294 |
|
| r15.3 |
143247 |
143247 |
3600 |
3600 |
3600 |
7500 |
|
|
4399 |
353 |
358 |
|
| r15.4 |
470 |
470 |
3600 |
3600 |
3600 |
5220 |
|
|
431 |
160 |
436 |
|
| r15.5 |
48914 |
48914 |
3600 |
3600 |
3600 |
8760 |
|
|
1364 |
354 |
433 |
|
| r15.6 |
214023 |
214023 |
3600 |
3600 |
3600 |
10200 |
|
|
645 |
396 |
299 |
|
| r15.7 |
566 |
566 |
3600 |
3600 |
3600 |
7020 |
|
|
482 |
21 |
23 |
|
| r15.8 |
85 |
85 |
3600 |
3600 |
3600 |
8940 |
|
|
178 |
34 |
30 |
|
| r15.9 |
39 |
39 |
3600 |
3600 |
3600 |
5100 |
|
|
59 |
23 |
22 |
|
| r16.1 |
1 |
1 |
3600 |
3600 |
3600 |
3720 |
|
|
8 |
8 |
3 |
|
| r16.2 |
16 |
16 |
3600 |
3600 |
3600 |
3780 |
|
|
146 |
47 |
41 |
|
| r16.3 |
60 |
60 |
3600 |
3600 |
3600 |
3780 |
|
|
916 |
148 |
112 |
|
| r16.4 |
2 |
2 |
3600 |
3600 |
3600 |
3840 |
|
|
9 |
10 |
7 |
|
| r16.5 |
54 |
54 |
3600 |
3600 |
3600 |
3780 |
|
|
165 |
98 |
77 |
|
| r16.6 |
311 |
311 |
3600 |
3600 |
3600 |
4020 |
|
|
766 |
155 |
144 |
|
| r16.7 |
147 |
147 |
3600 |
3600 |
3600 |
3960 |
|
|
8 |
245 |
162 |
|
| r16.8 |
5405 |
5405 |
3600 |
3600 |
3600 |
3840 |
|
|
45 |
276 |
192 |
|
| r16.9 |
10235 |
10235 |
3600 |
3600 |
3600 |
4380 |
|
|
42 |
255 |
268 |
|
| r17.1 |
20 |
20 |
3600 |
3600 |
3600 |
4260 |
|
|
42 |
15 |
15 |
|
| r17.2 |
3959 |
3959 |
3600 |
3600 |
3600 |
7980 |
|
|
486 |
306 |
255 |
|
| r17.3 |
11446 |
11446 |
3600 |
3600 |
3600 |
7860 |
|
|
8579 |
311 |
317 |
|
| r17.4 |
34 |
34 |
3600 |
3600 |
3600 |
4800 |
|
|
48 |
42 |
38 |
|
| r17.5 |
1767 |
1767 |
3600 |
3600 |
3600 |
3960 |
|
|
695 |
283 |
221 |
|
| r17.6 |
17531 |
17531 |
3600 |
3600 |
3600 |
5400 |
|
|
1321 |
331 |
426 |
|
| r17.7 |
8959 |
8959 |
3600 |
3600 |
3600 |
6900 |
|
|
139 |
281 |
295 |
|
| r17.8 |
42394 |
42394 |
3600 |
3600 |
3600 |
11220 |
|
|
159 |
265 |
354 |
|
| r17.9 |
163607 |
163607 |
3600 |
3600 |
3600 |
8220 |
|
|
170 |
414 |
383 |
|
| r18.1 |
1070 |
1070 |
3600 |
3600 |
3600 |
8160 |
|
|
320 |
162 |
288 |
|
| r18.2 |
6636 |
6636 |
3600 |
3600 |
3600 |
5760 |
|
|
5677 |
286 |
352 |
|
| r18.3 |
48961 |
48961 |
3600 |
3600 |
3600 |
4320 |
|
|
10184 |
354 |
363 |
|
| r18.4 |
20803 |
20803 |
3600 |
3600 |
3600 |
13140 |
|
|
831 |
249 |
351 |
|
| r18.5 |
131542 |
131542 |
3600 |
3600 |
3600 |
5460 |
|
|
2428 |
277 |
401 |
|
| r18.6 |
216000 |
216000 |
3600 |
3600 |
3600 |
8400 |
|
|
2787 |
473 |
414 |
|
| r18.7 |
147755 |
147755 |
3600 |
3600 |
3600 |
7620 |
|
|
827 |
261 |
364 |
|
| r18.8 |
10289 |
10289 |
3600 |
3600 |
3600 |
7680 |
|
|
1191 |
152 |
169 |
|
| r18.9 |
8790 |
8790 |
3600 |
3600 |
3600 |
4080 |
|
|
1756 |
151 |
129 |
|
| Average |
24472 |
24472 |
3600 |
3600 |
3600 |
5711 |
251 |
5074 |
1004 |
194 |
203 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| Optimal/Lower
Bound/Giurobi751/30h |
|
|
N. Katayama, Working paper, 2018. |
|
|
|
|
|
|
| Upper
Bound/Giurobi7.51/30h |
|
|
N. Katayama, Working paper, 2018. |
|
|
|
|
|
|
| Tabu Search |
|
|
|
M.B. Pedersen, T.G. Crainic, and O.B.G.Madsen.
Models and tabu search metaheuristics for service network design with
asset-balance requirements. Transportation Science, Vol. 43, pp. 158–177,
2009. |
| Parallel Tabu Search |
|
|
|
M.B. Pedersen, T.G. Crainic, and O.B.G.Madsen.
Models and tabu search metaheuristics for service network design with
asset-balance requirements. Transportation Science, Vol. 43, pp. 158–177,
2009. |
| MIP Tabu Search |
|
|
|
M. Chouman and T. G. Crainic. MIP-based tabu
search for service network design with design-balanced requirements.
Technical Report CIRRELT-2011-68, Centrede recherche sur les
transports,Universit'e de Montr'eal, 2011. |
| Three-Stage
Metaheuristic |
|
|
V.D. Minh,T.G. Crainic,M. Toulouse, A
three-stage metaheuristic for the capacitated multi-commodity fixed-cost
network design with design-balance constraints, J. Heuristics, 19, 757–795,
2013.
|
| Capacity
Scaling and Restricted Branch-and-Bound Matheuristic |
N. Katayama, A combined matheuristics for
service network design problem", The International Federation of
Logistics and SCM Systems, Vol.8, pp11-20, 2015. |
| Capacity
Scaling and Local Branch Matheuristic 20-2000 |
N. Katayama, A combined matheuristics for
service network design problem", The International Federation of
Logistics and SCM Systems, Vol.8, pp11-20, 2015. |
| Cutting-Plane
Matheuristic |
|
|
M. Choumann and T.G. Crainic, Cutting-plane matheuristic for service
network design with design-balanced requirements, Transportation Science,
Vol.49, pp99-113, 2016. |
| Capacity
Scaling and MIP Neighborhood |
|
N. Katayama, Working paper, 2018. |
|
|
|
|
|
|
| Capacity
Scaling and MIP Neighborhood Search Tuned |
N. Katayama, Working paper, 2018. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|