Soumen Atta1, 2, Goutam Sen3
1Indian Institute of Information Technology (IIIT) Vadodara, Gandhinagar Campus, Sector 28, Gandhinagar, Gujarat-382028, India
2Faculty of Informatics, Masaryk University, Botanicka´ 68a, Brno 602 00, Czech Republic
E-mail: soumen_atta@iiitvadodara.ac.in; atta@fi.muni.cz (Corresponding author)
3Industrial and Systems Engineering, Indian Institute of Technology (IIT) Kharagpur, Kharagpur-721302, West Bengal, India
E-mail: gsen@iem.iitkgp.ernet.in
The instances for the single allocation p-hub location problem (SApHLP) with ring backbone network mentioned in this page are generated from the real world movie data set known as MovieLens 100K data set (Harper and Konstan, 2016) available at https://grouplens.org/datasets/movielens/100k/. Thirty five different size instances are generated for SApHLP. All the instances are given in the table shown below where n, f, p and α denote the number of users, number of files, number of hubs and discount factor per unit inter-hub flow respectively. Each instance consists of the query matrix (Q) and the distance matrix (D). In the table shown below, the column "Solution" denotes the structure of of the backbone ring network (R) and the assignment of the segments to the hubs (S). For example, R = (0, 3, 7, 4, 5) denotes that the ring is formed with the nodes 0, 3, 7, 4, 5, and S = (0, 1, 3, 2, 4) denotes that data segments s0, s1, s3, s2 and s4 are assigned to the hub-nodes 0, 3, 7, 4 and 5 respectively. Each of the instances can be separately downloaded by clicking on the respective serial number (Sl. No.) of the instance.
Cite as: Soumen Atta, Goutam Sen. A new variant of the p-hub location problem with a ring backbone network for content placement in VoD services. Computers & Industrial Engineering, Elsevier, Vol. 159, pp. 107432, 2021.
Click here to download all the instances as a single zip file.
| Sl. No. | n | f | p | α | Solution | Cost |
|
10 |
100 |
5 |
0.2 |
R = (0, 3, 7, 4, 5), S = (0, 1, 3, 2, 4) |
553104.47☆ |
|
|
10 |
100 |
5 |
0.4 |
R = (2, 0, 5, 4, 6), S = (1, 0, 4, 2, 3) |
936261.71☆ |
|
|
10 |
100 |
5 |
0.6 |
R = (0, 2, 3, 4, 5), S = (0, 1, 3, 2, 4) |
1309206.30☆ |
|
|
10 |
100 |
5 |
0.8 |
R = (0, 2, 3, 4, 5), S = (0, 1, 3, 2, 4) |
1652135.01☆ |
|
|
10 |
100 |
5 |
1.0 |
R = (0, 2, 3, 4, 5), S = (0, 1, 3, 2, 4) |
1988500.34☆ |
|
|
20 |
100 |
5 |
0.2 |
R = (0, 15, 19, 4, 5), S = (4, 0, 1, 3, 2) |
1227525.44☆ |
|
|
20 |
100 |
5 |
0.4 |
R = (15, 0, 17, 9, 19), S = (0, 2, 3, 1, 4) |
1861434.59☆ |
|
|
20 |
100 |
5 |
0.6 |
R = (13, 12, 0, 15, 19), S = (1, 3, 2, 0, 4) |
2435536.17☆ |
|
|
20 |
100 |
5 |
0.8 |
R = (3, 13, 0, 15, 19), S = (2, 1, 3, 4, 0) |
2935572.40☆ |
|
|
20 |
100 |
5 |
1.0 |
R = (8, 18, 15, 19, 3), S = (3, 2, 4, 0, 1) |
3203332.89☆ |
|
|
30 |
100 |
5 |
0.2 |
R = (0, 17, 22, 19, 28), S = (1, 3, 4, 0, 2) |
1794292.89☆ |
|
|
30 |
100 |
5 |
0.4 |
R = (0, 15, 3, 22, 17), S = (1, 2, 0, 4, 3) |
2675722.01☆ |
|
|
30 |
100 |
5 |
0.6 |
R = (0, 17, 22, 2, 19), S = (1, 3, 4, 0, 2) |
3419104.85☆ |
|
|
30 |
100 |
5 |
0.8 |
R = (0, 19, 11, 22, 27), S = (3, 0, 2, 4, 1) |
4063632.38☆ |
|
|
30 |
100 |
5 |
1.0 |
R = (3, 8, 18, 15, 19), S = (2, 1, 3, 4, 0) |
4363138.09☆ |
|
|
40 |
100 |
5 |
0.2 |
R = (0, 17, 22, 19, 13), S = (4, 3, 2, 1, 0) |
2272505.88 |
|
|
40 |
100 |
5 |
0.4 |
R = (17, 38, 22, 19, 39), S = (4, 3, 2, 1, 0) |
3291205.53 |
|
|
40 |
100 |
5 |
0.6 |
R = (2, 39, 17, 38, 22), S = (1, 0, 4, 3, 2) |
4182210.73 |
|
|
40 |
100 |
5 |
0.8 |
R = (2, 20, 35, 22, 38), S = (1, 0, 2, 3, 4) |
4772493.40☆ |
|
|
40 |
100 |
5 |
1.0 |
R = (15, 18, 31, 19, 32), S = (3, 4, 0, 1, 2) |
5107719.96☆ |
|
|
50 |
100 |
5 |
0.2 |
R = (39, 19, 34, 17, 0), S = (4, 0, 2, 3, 1) |
2659882.50 |
|
|
50 |
100 |
5 |
0.4 |
R = (47, 41, 39, 17, 38), S = (2, 0, 4, 3, 1) |
3718916.92 |
|
|
50 |
100 |
5 |
0.6 |
R = (47, 41, 39, 17, 38), S = (2, 0, 4, 3, 1) |
4542755.11 |
|
|
50 |
100 |
5 |
0.8 |
R = (47, 38, 39, 3, 41), S = (2, 3, 1, 4, 0) |
5217895.03 |
|
|
50 |
100 |
5 |
1.0 |
R = (20, 2, 43, 41, 19), S = (1, 4, 0, 2, 3) |
5628658.34 |
|
|
100 |
100 |
5 |
0.2 |
R = (38, 77, 13, 41, 63), S = (4, 3, 2, 0, 1) |
6029245.45 |
|
|
100 |
100 |
5 |
0.4 |
R = (13, 53, 47, 70, 52), S = (4, 3, 2, 0, 1) |
8090363.57 |
|
|
100 |
100 |
5 |
0.6 |
R = (47, 38, 39, 2, 62), S = (0, 3, 4, 2, 1) |
9605985.94 |
|
|
100 |
100 |
5 |
0.8 |
R = (70, 41, 52, 3, 38), S = (0, 1, 2, 3, 4) |
10769559.94 |
|
|
100 |
100 |
5 |
1.0 |
R = (97, 43, 2, 64, 62), S = (2, 3, 4, 0, 1) |
11284598.19 |
|
|
150 |
100 |
5 |
0.2 |
R = (77, 85, 40, 70, 11), S = (2, 3, 4, 0, 1) |
8819803.26 |
|
|
150 |
100 |
5 |
0.4 |
R = (47, 108, 77, 23, 41), S = (4, 3, 2, 1, 0) |
11580700.91 |
|
|
150 |
100 |
5 |
0.6 |
R = (62, 47, 53, 39, 2), S = (0, 1, 2, 3, 4) |
13769200.46 |
|
|
150 |
100 |
5 |
0.8 |
R = (52, 41, 38, 3, 59), S = (0, 1, 2, 3, 4) |
15439142.73 |
|
|
150 |
100 |
5 |
1.0 |
R = (62, 113, 2, 140, 64), S = (0, 1, 2, 3, 4) |
16093943.16 |
Reference:
Harper FM, Konstan JA (2016) The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis) 5(4):19
This page was created on October 08, 2020.