Ranking for Benchmark ID KS2:JB1:USA_US101-12_1_T-1:2018b

In this ranking, we compare the costs of each submission for with respect to the best solution so far. To get a detailed report on the costs for each submission, click on the respective solution.

Rank User Country Organization Method Algorithm Submission Date CPU Processing Time
(ms)
Relative Cost
1 edmond320 Germany Technical University of Munich 2019/11/13 08:49 100.00 %
2 PeterKocsis Germany TUM 2019/12/15 17:47 109.86 %
3 PeterKocsis Germany TUM 2019/12/15 17:56 111.27 %
4 PeterKocsis Germany TUM 2019/12/15 17:49 114.08 %
5 PeterKocsis Germany TUM 2019/12/15 17:52 114.08 %
6 PeterKocsis Germany TUM 2019/12/15 17:57 6938.43 %
7 PeterKocsis Germany TUM 2019/12/15 17:49 9669.04 %
8 PeterKocsis Germany TUM 2019/12/15 17:52 13160.82 %
9 PeterKocsis Germany TUM 2019/12/15 17:55 13160.82 %
10 tk Hong Kong TUM 2019/12/11 16:17 13533.72 %
11 ge82gan Germany TUM 2019/12/07 11:30 42673.39 %
12 Vegetable Nord Korea TUM 2019/12/02 17:30 44325.35 %
13 Vegetable Nord Korea TUM 2019/12/05 21:36 44325.35 %
14 Vegetable Nord Korea TUM 2019/12/08 13:46 44325.35 %
15 PeterKocsis Germany TUM 2019/12/15 17:46 46628.84 %
16 PeterKocsis Germany TUM 2019/12/05 19:05 46795.36 %
17 PeterKocsis Germany TUM 2019/12/15 17:52 46795.36 %
18 Country_roads DE TUM 2019/12/08 03:40 47055.67 %
19 ge82diw China TUM 2019/12/07 10:42 51860.31 %
20 GottCoder Germany TUM 2019/12/13 14:37 51860.31 %
21 tana germany TUM 2019/12/05 21:16 67060.72 %
22 Radex Bavaria TUM 2019/12/04 23:17 71476.31 %
23 Radex Bavaria TUM 2019/12/08 15:46 71476.31 %
24 Radex Bavaria TUM 2019/12/08 15:51 71476.31 %
25 Radex Bavaria TUM 2019/12/08 15:53 71476.31 %
26 tana germany TUM 2019/11/30 22:29 85994.42 %
27 NanoCanterino Italy TUM 2019/12/06 14:36 88898.31 %
28 valentincervieri Germany TUM 2019/12/07 23:26 88898.31 %
29 NanoCanterino Italy TUM 2019/12/09 14:16 88898.31 %
30 valentincervieri Germany TUM 2019/12/09 20:33 88898.31 %
31 qianqian_chai Germany Technische Universität München 2019/12/14 11:49 88898.31 %
32 NanoCanterino Italy TUM 2019/12/14 20:29 88898.31 %
33 holtmannm Germany TUM 2019/12/15 22:39 88898.31 %
34 qianqian_chai Germany Technische Universität München 2019/12/06 23:25 105227.64 %
35 Michael_Hauer Deutschland TUM 2019/12/08 17:34 115941.18 %
36 PeterKocsis Germany TUM 2019/12/15 17:46 120430.95 %
37 PeterKocsis Germany TUM 2019/12/15 16:52 120597.52 %
38 PeterKocsis Germany TUM 2019/12/15 17:56 120597.52 %
39 PeterKocsis Germany TUM 2019/12/15 17:50 132397.95 %
40 PeterKocsis Germany TUM 2019/12/15 16:53 132571.88 %
41 PeterKocsis Germany TUM 2019/12/15 17:49 132571.88 %
42 PeterKocsis Germany TUM 2019/12/15 16:55 162600.81 %
43 PeterKocsis Germany TUM 2019/12/15 17:42 162600.81 %
44 sebkas Technische Universität München 2018/12/19 22:05 696600.76 %
45 yifengdong Technische Universität München 2019/02/15 16:33 2467108.23 %
46 PeterKocsis Germany TUM 2019/12/15 18:01 10845070.42 %
47 PeterKocsis Germany TUM 2019/12/15 17:46 10985915.49 %
48 PeterKocsis Germany TUM 2019/12/15 17:51 11267605.63 %
49 PeterKocsis Germany TUM 2019/12/15 18:00 11267605.63 %

Normalized processing times: To provide comparable values for the processing times that were required to calculate each solution, we normalize processing times depending on the CPU that was used. If a user supplies CPU and processing time, the normalized time will be shown in green whereas the actual calculation time can be found in the brackets. We base the normalization on up-to-date data from www.cpubenchmark.net.