Home Cover Printing
Instances
Contact
Details
David Romero
Universidad Nacional Autónoma de
México (UNAM)
Email:
davidr@matcuer.unam.mx

UNAM
|
|
Contents:
1. Instances Format
2. Solutions Format
3. Datasets
3.1 Instances from several sources
3.2 Instances without costs
3.3 Instances with known optima
3.4 Random instances from [1]
3.5 Random instances from [14]
1. Instances Format The instance files have the following format.
All numbers,
with the exception of
the cost per impression and cost per grid are always integers, all intra-line
separators are spaces.
First line:
Number of covers;
Second line:
Grid size;
One line for each cover:
Demand of cover;
Last line:
Cost per impression; Cost per grid;
For example, for an instance having three covers with demand 4500, 9000 and
16000, respectively, with a grid size of 4, with an impression cost 13.44 and a
grid cost 18676, the file would have
the following format:
3
4
4500
9000
16000
13.44 18676
2. Solutions Format
The solution file has the following format. All numbers, excepting
the total cost are always integers (all intra-line
separators are spaces). The files have the extension .out and a plain
text format.
First line:
Number of grids (Ng);
One line for each grid:
Grid composition, namely, and m-vector whose elements are non-negative
integers summing up to t (gridsize), all integers separated by spaces.
Next line:
Number of imprints of each grid; Ng integers separated by
spaces.
This line has a vector of size Ng, the first integer
is the number of imprints of the first grid, the second integer is the number
of imprints of the second grid, and so on.
Last line:
Total cost, computed as the total number of imprints times the impression cost, plus the number of grids multiplied by the grid cost.
As an example takes the above input file with 3 covers, then a possible solution in the output file could be:
2
0 1 3
2 2 0
5334 2250
139280.96
The first line indicates that in this solution two grids are to be
composed. The second and third lines describe the composition of the first
and second grids, respectively; namely the first grid is composed by one plate
of the second cover and three plates of the third cover. the second grid is
composed by two plates of the first cover and two plates of the second
cover. The fourth line indicates that the first grid is to be printed 5334
times and the second grid 2250 times. The total cost is:
Tc = 13.44 * (5334 + 2250) + 2 * 18676 = 101928.93 + 37352 =
139280.96
which is the last line in the file.
3. Datasets
The source for instances below is indicated in brackets. All
files instances have extension .in and plain text format. You can download
all instances here: Download all instances.
This page contains five sets of instances, each in one separate table. The first set
comes from several sources.
The second set corresponds to cases where no cost is given
because the objective function is to minimize the paper wasted. The
third set of instances was generated with known optimal solutions. The
fourth set contains random instances from [1], and the fifth set contains
random
instances from [14].
3.1 Instances from several sources
The next table provides thirteen instances where m is the number of covers and
t is the gridsize. The first column contains the instance file and
the source in brackets. The second and third columns contain the size of m
and t, respectively. In the fourth column, we give in brackets the
source for the best known solutions, and an asterisk (*) indicates that the value
corresponds to the global optimum. The fifth column contains the solution
file.
Instance |
m |
t |
Best known solution |
Solution file |
I001.in [12] |
3 |
4 |
136,472*
[1,10,12,14] |
I001.out |
I002.in
[12] |
4 |
4 |
247,916*
[1,3,10,12,14] |
I002.out |
I003.in
[12] |
5 |
4 |
1,851,948*
[1,14] |
I003.out |
I004.in
[12] |
8 |
4 |
264,348*
[1,3,12,14] |
I004.out |
I005.in
[8] |
12 |
4 |
269,584*
[1,14] |
I005.out |
I006.in
[12] |
15 |
4 |
515,256*
[1,14] |
I006.out |
I007.in
[15] |
9 |
8 |
5,283.53* [1] |
I007.out |
I008.in
[15] |
17 |
8 |
11,475.52 [1] |
I008.out |
I009.in
[15] |
18 |
7 |
11,191.6 [1] |
I009.out |
I013.in
[14] |
30 |
4 |
1,759,240
[14] |
I013.out |
I014.in
[14] |
40 |
4 |
2,575,832
[1] |
I014.out |
I015.in
[14] |
50 |
4 |
6,534,556
[1] |
I015.out |
I016.in [1] |
100 |
25 |
265,918
[1] |
I016.out |
3.2 Instances without costs The next table
provides
eight instances where the cost per impression and the cost
per grid are unknown. In these instances one looks for minimizing the paper waste
for a prescribed number of grids. The waste is computed as one hundred multiplied by
the total
surplus divided by the total demand. In these instances the solution
file contains the percentage of waste
instead of the total cost. The first column contains the instance file and
the source in brackets. The second and third columns contain the size
of m and t, respectively. The fourth column is the prescribed
number of grids. In the fifth column of this table, the brackets indicated the source where the best solutions
were obtained, an asterisk (*) indicates that the value corresponds to the
global optimum.
3.3 Instances with known
optima This table contains 60 instances generated in
[1], and whose optimal solutions were previously
determined. See [1] for a description of the optimal solutions. These
instances were heuristically solved as it is described in [1], yielding the
results shown in the last three columns of the table. The fourth column
corresponds to the
optimal cost.
Instance |
m |
t |
Optimal cost |
Obtained cost [1] |
CPU Time (seconds) |
Solution file |
E001.in |
13 |
6 |
51,750 |
54,750 |
1 |
E001.out |
E002.in |
13 |
6 |
51,606 |
54,606 |
1 |
E002.out |
E003.in |
13 |
6 |
56,686 |
56,686 |
1 |
E003.out |
E004.in |
13 |
6 |
51,257 |
54,257 |
1 |
E004.out |
E005.in |
13 |
6 |
56,322 |
56,322 |
1 |
E005.out |
E006.in |
13 |
6 |
51,803 |
54,803 |
2 |
E006.out |
E007.in |
13 |
6 |
56,272 |
59,272 |
2 |
E007.out |
E008.in |
13 |
6 |
59,104 |
59,104 |
1 |
E008.out |
E009.in |
13 |
6 |
52,855 |
52,855 |
1 |
E009.out |
E010.in |
13 |
6 |
53,778 |
53,778 |
1 |
E010.out |
E011.in |
25 |
8 |
80,749 |
84,005 |
5 |
E011.out |
E012.in |
25 |
8 |
78,369 |
78,684 |
0 |
E012.out |
E013.in |
25 |
8 |
83,369 |
83,704 |
1 |
E013.out |
E014.in |
25 |
8 |
71,417 |
77,494 |
3 |
E014.out |
E015.in |
25 |
8 |
75,762 |
81,464 |
4 |
E015.out |
E016.in |
25 |
8 |
82,608 |
88,970 |
0 |
E016.out |
E017.in |
25 |
8 |
85,839 |
86,134 |
0 |
E017.out |
E018.in |
25 |
8 |
74,488 |
78,311 |
4 |
E018.out |
E019.in |
25 |
8 |
77,548 |
83,991 |
3 |
E019.out |
E020.in |
25 |
8 |
77,670 |
84,019 |
0 |
E020.out |
E021.in |
41 |
10 |
110,779 |
117,319 |
33 |
E021.out |
E022.in |
41 |
10 |
115,729 |
122,591 |
29 |
E022.out |
E023.in |
41 |
10 |
112,568 |
116,775 |
28 |
E023.out |
E024.in |
41 |
10 |
118,169 |
124,564 |
29 |
E024.out |
E025.in |
41 |
10 |
103,499 |
106,863 |
23 |
E025.out |
E026.in |
41 |
10 |
100,873 |
105,407 |
18 |
E026.out |
E027.in |
41 |
10 |
105,308 |
111,470 |
22 |
E027.out |
E028.in |
41 |
10 |
106,658 |
110,383 |
26 |
E028.out |
E029.in |
41 |
10 |
98,331 |
104,552 |
21 |
E029.out |
E030.in |
41 |
10 |
109,138 |
112,839 |
25 |
E030.out |
E031.in |
61 |
12 |
145,705 |
153,481 |
98 |
E031.out |
E032.in |
61 |
12 |
149,415 |
158,751 |
67 |
E032.out |
E033.in |
61 |
12 |
143,983 |
150,500 |
69 |
E033.out |
E034.in |
61 |
12 |
143,305 |
147,910 |
102 |
E034.out |
E035.in |
61 |
12 |
138,134 |
144,670 |
66 |
E035.out |
E036.in |
61 |
12 |
151,318 |
157,823 |
75 |
E036.out |
E037.in |
61 |
12 |
142,725 |
152,127 |
59 |
E037.out |
E038.in |
61 |
12 |
138,358 |
141,690 |
65 |
E038.out |
E039.in |
61 |
12 |
142,520 |
148,396 |
70 |
E039.out |
E040.in |
61 |
12 |
143,932 |
150,316 |
91 |
E040.out |
E041.in |
85 |
14 |
184,266 |
188,739 |
174 |
E041.out |
E042.in |
85 |
14 |
181,953 |
188,797 |
162 |
E042.out |
E043.in |
85 |
14 |
180,216 |
187,595 |
9 |
E043.out |
E044.in |
85 |
14 |
187,387 |
194,373 |
263 |
E044.out |
E045.in |
85 |
14 |
162,654 |
169,008 |
150 |
E045.out |
E046.in |
85 |
14 |
177,954 |
185,086 |
10 |
E046.out |
E047.in |
85 |
14 |
183,011 |
189,472 |
204 |
E047.out |
E048.in |
85 |
14 |
188,604 |
190,223 |
50 |
E048.out |
E049.in |
85 |
14 |
190,843 |
194,012 |
102 |
E049.out |
E050.in |
85 |
14 |
175,522 |
182,728 |
212 |
E050.out |
E051.in |
113 |
16 |
230,934 |
239,792 |
22 |
E051.out |
E052.in |
113 |
16 |
216,732 |
224,021 |
178 |
E052.out |
E053.in |
113 |
16 |
239,502 |
247,076 |
19 |
E053.out |
E054.in |
113 |
16 |
217,150 |
221,105 |
20 |
E054.out |
E055.in |
113 |
16 |
220,353 |
222,348 |
18 |
E055.out |
E056.in |
113 |
16 |
218,323 |
224,692 |
22 |
E056.out |
E057.in |
113 |
16 |
209,618 |
215,806 |
213 |
E057.out |
E058.in |
113 |
16 |
220,605 |
227,740 |
29 |
E058.out |
E059.in |
113 |
16 |
232,452 |
240,263 |
24 |
E059.out |
E060.in |
113 |
16 |
232,409 |
240,615 |
31 |
E060.out |
3.4 Random
instances from [1]
The next table corresponds to 120 random instances generated in [1].
These instances were heuristically solved as it is described in [1],
yielding the results shown in the last three columns of the table.
Instance |
m |
t |
Obtained cost [1] |
CPU Time (seconds) |
Solution
file |
R001.in |
10 |
6 |
112,431 |
0 |
R001.out |
R002.in |
10 |
6 |
95,990 |
2 |
R002.out |
R003.in |
10 |
6 |
89,566 |
0 |
R003.out |
R004.in |
10 |
6 |
91,024 |
1 |
R004.out |
R005.in |
10 |
6 |
124,168 |
0 |
R005.out |
R006.in |
10 |
6 |
95,290 |
0 |
R006.out |
R007.in |
10 |
6 |
89,476 |
1 |
R007.out |
R008.in |
10 |
6 |
64,539 |
1 |
R008.out |
R009.in |
10 |
6 |
107,766 |
0 |
R009.out |
R010.in |
10 |
6 |
106,115 |
0 |
R010.out |
R011.in |
10 |
8 |
82,792 |
1 |
R011.out |
R012.in |
10 |
8 |
87,978 |
0 |
R012.out |
R013.in |
10 |
8 |
78,361 |
0 |
R013.out |
R014.in |
10 |
8 |
77,106 |
0 |
R014.out |
R015.in |
10 |
8 |
66,712 |
0 |
R015.out |
R016.in |
10 |
8 |
76,878 |
0 |
R016.out |
R017.in |
10 |
8 |
62,817 |
0 |
R017.out |
R018.in |
10 |
8 |
74,172 |
0 |
R018.out |
R019.in |
10 |
8 |
88,894 |
0 |
R019.out |
R020.in |
10 |
8 |
76,921 |
0 |
R020.out |
R021.in |
25 |
12 |
128,601 |
0 |
R021.out |
R022.in |
25 |
12 |
124,816 |
1 |
R022.out |
R023.in |
25 |
12 |
120,665 |
1 |
R023.out |
R024.in |
25 |
12 |
134,819 |
3 |
R024.out |
R025.in |
25 |
12 |
132,306 |
0 |
R025.out |
R026.in |
25 |
12 |
127,978 |
2 |
R026.out |
R027.in |
25 |
12 |
116,859 |
0 |
R027.out |
R028.in |
25 |
12 |
122,974 |
1 |
R028.out |
R029.in |
25 |
12 |
139,761 |
3 |
R029.out |
R030.in |
25 |
12 |
152,855 |
6 |
R030.out |
R031.in |
25 |
16 |
101,560 |
1 |
R031.out |
R032.in |
25 |
16 |
107,327 |
2 |
R032.out |
R033.in |
25 |
16 |
108,926 |
0 |
R033.out |
R034.in |
25 |
16 |
117,534 |
1 |
R034.out |
R035.in |
25 |
16 |
90,293 |
1 |
R035.out |
R036.in |
25 |
16 |
92,473 |
1 |
R036.out |
R037.in |
25 |
16 |
92,256 |
1 |
R037.out |
R038.in |
25 |
16 |
106,009 |
0 |
R038.out |
R039.in |
25 |
16 |
107,913 |
2 |
R039.out |
R040.in |
25 |
16 |
96,324 |
0 |
R040.out |
R041.in |
50 |
16 |
189,253 |
21 |
R041.out |
R042.in |
50 |
16 |
195,627 |
22 |
R042.out |
R043.in |
50 |
16 |
196,666 |
13 |
R043.out |
R044.in |
50 |
16 |
201,876 |
12 |
R044.out |
R045.in |
50 |
16 |
222,999 |
17 |
R045.out |
R046.in |
50 |
16 |
186,412 |
11 |
R046.out |
R047.in |
50 |
16 |
185,067 |
13 |
R047.out |
R048.in |
50 |
16 |
184,252 |
12 |
R048.out |
R049.in |
50 |
16 |
210,386 |
12 |
R049.out |
R050.in |
50 |
16 |
202,643 |
10 |
R050.out |
R051.in |
50 |
20 |
145,113 |
13 |
R051.out |
R052.in |
50 |
20 |
151,544 |
16 |
R052.out |
R053.in |
50 |
20 |
145,687 |
20 |
R053.out |
R054.in |
50 |
20 |
162,260 |
14 |
R054.out |
R055.in |
50 |
20 |
172,883 |
16 |
R055.out |
R056.in |
50 |
20 |
145,464 |
15 |
R056.out |
R057.in |
50 |
20 |
145,331 |
15 |
R057.out |
R058.in |
50 |
20 |
169,324 |
16 |
R058.out |
R059.in |
50 |
20 |
167,109 |
14 |
R059.out |
R060.in |
50 |
20 |
159,751 |
15 |
R060.out |
R061.in |
100 |
12 |
501,975 |
87 |
R061.out |
R062.in |
100 |
12 |
484,739 |
92 |
R062.out |
R063.in |
100 |
12 |
532,763 |
136 |
R063.out |
R064.in |
100 |
12 |
483,623 |
136 |
R064.out |
R065.in |
100 |
12 |
549,673 |
93 |
R065.out |
R066.in |
100 |
12 |
499,255 |
95 |
R066.out |
R067.in |
100 |
12 |
527,716 |
138 |
R067.out |
R068.in |
100 |
12 |
503,971 |
138 |
R068.out |
R069.in |
100 |
12 |
531,249 |
115 |
R069.out |
R070.in |
100 |
12 |
492,351 |
155 |
R070.out |
R071.in |
100 |
16 |
383,644 |
193 |
R071.out |
R072.in |
100 |
16 |
385,382 |
172 |
R072.out |
R073.in |
100 |
16 |
350,177 |
223 |
R073.out |
R074.in |
100 |
16 |
393,316 |
142 |
R074.out |
R075.in |
100 |
16 |
377,347 |
199 |
R075.out |
R076.in |
100 |
16 |
384,201 |
203 |
R076.out |
R077.in |
100 |
16 |
362,790 |
136 |
R077.out |
R078.in |
100 |
16 |
383,286 |
249 |
R078.out |
R079.in |
100 |
16 |
380,421 |
146 |
R079.out |
R080.in |
100 |
16 |
408,601 |
398 |
R080.out |
R081.in |
100 |
25 |
254,163 |
242 |
R081.out |
R082.in |
100 |
25 |
255,910 |
252 |
R082.out |
R083.in |
100 |
25 |
265,873 |
285 |
R083.out |
R084.in |
100 |
25 |
260,092 |
321 |
R084.out |
R085.in |
100 |
25 |
251,314 |
267 |
R085.out |
R086.in |
100 |
25 |
233,874 |
269 |
R086.out |
R087.in |
100 |
25 |
253,448 |
249 |
R087.out |
R088.in |
100 |
25 |
246,531 |
306 |
R088.out |
R089.in |
100 |
25 |
246,524 |
210 |
R089.out |
R090.in |
100 |
25 |
249,321 |
295 |
R090.out |
R091.in |
25 |
8 |
195,326 |
2 |
R091.out |
R092.in |
25 |
8 |
183,406 |
0 |
R092.out |
R093.in |
25 |
8 |
192,144 |
0 |
R093.out |
R094.in |
25 |
8 |
213,047 |
2 |
R094.out |
R095.in |
25 |
8 |
154,142 |
2 |
R095.out |
R096.in |
25 |
8 |
184,489 |
0 |
R096.out |
R097.in |
25 |
8 |
212,729 |
0 |
R097.out |
R098.in |
25 |
8 |
172,726 |
2 |
R098.out |
R099.in |
25 |
8 |
195,025 |
2 |
R099.out |
R100.in |
25 |
8 |
207,749 |
1 |
R100.out |
R101.in |
50 |
12 |
259,020 |
22 |
R101.out |
R102.in |
50 |
12 |
259,208 |
26 |
R102.out |
R103.in |
50 |
12 |
246,165 |
9 |
R103.out |
R104.in |
50 |
12 |
255,621 |
11 |
R104.out |
R105.in |
50 |
12 |
257,999 |
14 |
R105.out |
R106.in |
50 |
12 |
245,518 |
11 |
R106.out |
R107.in |
50 |
12 |
273,008 |
27 |
R107.out |
R108.in |
50 |
12 |
281,626 |
29 |
R108.out |
R109.in |
50 |
12 |
255,731 |
24 |
R109.out |
R110.in |
50 |
12 |
275,057 |
25 |
R110.out |
R111.in |
100 |
20 |
298,734 |
320 |
R111.out |
R112.in |
100 |
20 |
306,723 |
166 |
R112.out |
R113.in |
100 |
20 |
327,041 |
256 |
R113.out |
R114.in |
100 |
20 |
293,234 |
177 |
R114.out |
R115.in |
100 |
20 |
299,499 |
197 |
R115.out |
R116.in |
100 |
20 |
296,731 |
203 |
R116.out |
R117.in |
100 |
20 |
314,614 |
214 |
R117.out |
R118.in |
100 |
20 |
327,867 |
213 |
R118.out |
R119.in |
100 |
20 |
286,527 |
205 |
R119.out |
R120.in |
100 |
20 |
313,083 |
296 |
R120.out |
3.5 Random
instances from [14]
The next table contains 75 random instances, kindly provided and
heuristically solved [14] by Daniel Tuyttens of the University of Mons,
Faculté Polytechnique, Belgium. The fourth column is the obtained cost in
[14], the fifth and sixth columns are the obtained cost in [1] and the
needed CPU time, respectively. The seventh column indicates the file containing the best
known solution.
Instance |
m |
t |
Obtained cost [14] |
Obtained cost [1] |
CPU Time (seconds) |
File of the best solution |
T001.in |
30 |
4 |
2,268,224 |
2,252,096 |
1 |
T001.out |
T002.in |
30 |
4 |
2,164,736 |
2,145,920 |
1 |
T002.out |
T003.in |
30 |
4 |
2,408,000 |
2,413,376 |
1 |
T003.out |
T004.in |
30 |
4 |
2,977,856 |
2,937,536 |
1 |
T004.out |
T005.in |
30 |
4 |
3,116,288 |
3,082,688 |
2 |
T005.out |
T006.in |
40 |
4 |
4,956,448 |
4,931,696 |
1 |
T006.out |
T007.in |
40 |
4 |
4,287,136 |
4,235,504 |
3 |
T007.out |
T008.in |
40 |
4 |
4,937,632 |
4,863,824 |
2 |
T008.out |
T009.in |
40 |
4 |
6,137,824 |
6,097,168 |
1 |
T009.out |
T010.in |
40 |
4 |
5,789,168 |
5,717,936 |
3 |
T010.out |
T011.in |
50 |
4 |
6,911,632 |
6,863,248 |
2 |
T011.out |
T012.in |
50 |
4 |
8,683,248 |
8,655,024 |
1 |
T012.out |
T013.in |
50 |
4 |
9,748,144 |
9,607,920 |
6 |
T013.out |
T014.in |
50 |
4 |
10,351,712 |
10,255,168 |
7 |
T014.out |
T015.in |
50 |
4 |
10,832,080 |
10,673,040 |
13 |
T015.out |
T016.in |
30 |
4 |
1,969,408 |
1,950,312 |
1 |
T016.out |
T017.in |
30 |
4 |
1,860,264 |
1,833,384 |
1 |
T017.out |
T018.in |
30 |
4 |
2,109,184 |
2,103,528 |
1 |
T018.out |
T019.in |
30 |
4 |
2,676,072 |
2,626,736 |
1 |
T019.out |
T020.in |
30 |
4 |
2,768,920 |
2,741,648 |
1 |
T020.out |
T021.in |
40 |
4 |
4,569,712 |
4,520,824 |
2 |
T021.out |
T022.in |
40 |
4 |
3,857,392 |
3,824,632 |
3 |
T022.out |
T023.in |
40 |
4 |
4,467,848 |
4,407,368 |
2 |
T023.out |
T024.in |
40 |
4 |
5,679,576 |
5,611,592 |
1 |
T024.out |
T025.in |
40 |
4 |
5,322,352 |
5,268,872 |
2 |
T025.out |
T026.in |
50 |
4 |
6,355,328 |
6,327,104 |
2 |
T026.out |
T027.in |
50 |
4 |
8,122,968 |
8,070,272 |
2 |
T027.out |
T028.in |
50 |
4 |
9,750,776 |
9,047,640 |
5 |
T028.out |
T029.in |
50 |
4 |
9,711,520 |
9,655,632 |
7 |
T029.out |
T030.in |
50 |
4 |
10,158,792 |
10,082,240 |
13 |
T030.out |
T031.in |
30 |
4 |
1,804,656 |
1,778,056 |
1 |
T031.out |
T032.in |
30 |
4 |
1,684,648 |
1,662,929 |
1 |
T032.out |
T033.in |
30 |
4 |
1,931,132 |
1,915,004 |
1 |
T033.out |
T034.in |
30 |
4 |
2,452,464 |
2,436,476 |
1 |
T034.out |
T035.in |
30 |
4 |
2,563,484 |
2,549,372 |
2 |
T035.out |
T036.in |
40 |
4 |
4,298,700 |
4,275,320 |
2 |
T036.out |
T037.in |
40 |
4 |
3,594,444 |
3,569,244 |
2 |
T037.out |
T038.in |
40 |
4 |
4,182,976 |
4,148,172 |
2 |
T038.out |
T039.in |
40 |
4 |
5,396,468 |
5,368,524 |
2 |
T039.out |
T040.in |
40 |
4 |
5,021,492 |
5,001,612 |
1 |
T040.out |
T041.in |
50 |
4 |
6,056,512 |
6,028,288 |
3 |
T041.out |
T042.in |
50 |
4 |
7,800,744 |
7,771,456 |
2 |
T042.out |
T043.in |
50 |
4 |
8,770,692 |
8,720,040 |
4 |
T043.out |
T044.in |
50 |
4 |
9,336,516 |
9,317,840 |
8 |
T044.out |
T045.in |
50 |
4 |
9,766,596 |
9,725,744 |
13 |
T045.out |
T046.in |
30 |
4 |
1,692,600 |
1,678,558 |
1 |
T046.out |
T047.in |
30 |
4 |
1,585,080 |
1,569,549 |
1 |
T047.out |
T048.in |
30 |
4 |
1,818,866 |
1,810,200 |
1 |
T048.out |
T049.in |
30 |
4 |
2,338,994 |
2,326,296 |
1 |
T049.out |
T050.in |
30 |
4 |
2,445,170 |
2,437,778 |
2 |
T050.out |
T051.in |
40 |
4 |
4,155,732 |
4,144,588 |
1 |
T051.out |
T052.in |
40 |
4 |
3,451,546 |
3,429,174 |
2 |
T052.out |
T053.in |
40 |
4 |
4,033,428 |
4,008,102 |
2 |
T053.out |
T054.in |
40 |
4 |
5,236,308 |
5,220,992 |
2 |
T054.out |
T055.in |
40 |
4 |
4,862,746 |
4,858,784 |
3 |
T055.out |
T056.in |
50 |
4 |
5,873,224 |
5,859,784 |
2 |
T056.out |
T057.in |
50 |
4 |
7,625,870 |
7,615,048 |
1 |
T057.out |
T058.in |
50 |
4 |
8,571,836 |
8,551,956 |
4 |
T058.out |
T059.in |
50 |
4 |
9,140,418 |
9,124,962 |
9 |
T059.out |
T060.in |
50 |
4 |
9,570,288 |
9,538,984 |
13 |
T060.out |
T061.in |
30 |
4 |
1,634,521 |
1,626,492 |
1 |
T061.out |
T062.in |
30 |
4 |
1,529,052 |
1,522,668 |
1 |
T062.out |
T063.in |
30 |
4 |
1,757,462 |
1,752,121 |
1 |
T063.out |
T064.in |
30 |
4 |
2,274,902 |
2,267,545 |
1 |
T064.out |
T065.in |
30 |
4 |
2,381,008 |
2,374,358 |
2 |
T065.out |
T066.in |
40 |
4 |
4,071,690 |
4,067,658 |
2 |
T066.out |
T067.in |
40 |
4 |
3,370,689 |
3,359,139 |
2 |
T067.out |
T068.in |
40 |
4 |
3,949,386 |
3,938,067 |
3 |
T068.out |
T069.in |
40 |
4 |
5,151,559 |
5,141,514 |
1 |
T069.out |
T070.in |
40 |
4 |
4,779,908 |
4,771,879 |
2 |
T070.out |
T071.in |
50 |
4 |
5,777,086 |
5,766,404 |
2 |
T071.out |
T072.in |
50 |
4 |
7,532,987 |
7,521,668 |
3 |
T072.out |
T073.in |
50 |
4 |
8,465,723 |
8,455,006 |
4 |
T073.out |
T074.in |
50 |
4 |
9,033,458 |
9,026,843 |
9 |
T074.out |
T075.in |
50 |
4 |
9,458,232 |
9,441,467 |
12 |
T075.out |
References
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Printing Problem, submitted to Elsevier
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algorithms for set multicover and multiset multicover problems, Theoretical
Computer Science 411 (2010) 2467--2474.
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1986.
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1994.
[8] G. Fasbender, A branch and price algorithm for the
book cover printing problem, Graduate Thesis, Université Libre de Bruxelles, Belgium, 2000.
[9] L.E. Carrera, Algoritmo para encontrar el óptimo a
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problem, Computers and Operations Research 34 (2007), 2576-2588
[12] S. Elaoud, J. Teghem, B. Bouaziz, Genetic algorithm to solve the
cover printing problem, Computers & Operations Research 34
(2007), 3346-3361.
[13] S.R. Mohan, S.K. Neogy, A. Seth, N.K. Garg, S. Mittal, An
optimization model to determine master designs and runs for advertisement
printing, Journal of Mathematical Modelling and Algorithms 6
(2007), 259-271.
[14] D. Tuyttens, A. Vandaele, Using a greedy random adaptative search
procedure to solve the cover printing problem, Computers & Operations
Research, Volume 37, (2010) Issue 4, 640-648.
[15] L. Trilling, Personal Communication, 2006.
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