2 years, 5 months ago
FedCSIS 2022 Challenge: Predicting the Costs of Forwarding Contracts
FedCSIS 2022 Challenge: Predicting the Costs of Forwarding Contracts is the 8th data mining competition organized in association with Conference on Computer Science and Intelligence Systems (https://fedcsis.org/). At this year's competition, the task is to predict the costs related to the execution of forwarding contracts. The challenge is sponsored by Control System Software (https://controlsystem.com.pl/).
The topic of this year's data mining competition is the prediction of the costs related to the execution of forwarding contracts. The data sets made available to participants contain 6 years of history of orders appearing on the transport exchange, along with details such as the type of order, basic characteristics of the shipped goods (e.g., dimensions, special requirements), as well as the expected route that a driver will have to cover. The task for the competition participants is to develop a predictive model that assesses the actual costs of individual orders as accurately as possible. Such a model will be used in the future to support Freight Forwarders in selecting profitable contracts. The sponsor of the competition is Control System Software – a software company that has been delivering solutions for the Transportation, Spedition, and Logistics industry for 20 years.
Special session at FedCSIS 2022: As in previous years, a special session devoted to the competition will be held at the conference. We will invite authors of selected challenge reports to extend them for publication in the conference proceedings (after reviews by Organizing Committee members) and presentation at the conference. The papers will be indexed by the IEEE Digital Library and Web of Science. The invited teams will be chosen based on their final rank, innovativeness of their approach, and quality of the submitted report.
Rank | Team Name | Is Report | Preliminary Score | Final Score | Submissions | |
---|---|---|---|---|---|---|
1 | Dymitr |
True | True | 0.1398 | 0.138300 | 619 |
2 | Cyan |
True | True | 0.1402 | 0.139100 | 181 |
3 | hieuvq |
True | True | 0.1396 | 0.140700 | 159 |
4 | Lord of the Machine Learning |
True | True | 0.1434 | 0.142000 | 147 |
5 | baseline |
True | True | 0.1491 | 0.147500 | 5 |
6 | kubapok |
True | True | 0.1502 | 0.149400 | 32 |
7 | DeepIf |
True | True | 0.1500 | 0.149800 | 28 |
8 | Stan |
True | True | 0.1529 | 0.151900 | 131 |
9 | Artur Budzyński |
True | True | 0.1549 | 0.152000 | 45 |
10 | Nindza Zhelki |
True | True | 0.1567 | 0.157300 | 36 |
11 | flail1123 |
True | True | 0.1628 | 0.159600 | 24 |
12 | MEM |
True | True | 0.1615 | 0.161000 | 42 |
13 | HBKU CS |
True | True | 0.1653 | 0.162500 | 42 |
14 | Paweł Putra |
True | True | 0.1715 | 0.170100 | 31 |
15 | Alex-POLSL |
True | True | 0.1712 | 0.170400 | 20 |
16 | Vexam |
True | True | 0.1743 | 0.171400 | 22 |
17 | kz |
True | True | 0.1736 | 0.172700 | 10 |
18 | fabiolapereira |
True | True | 0.1783 | 0.174700 | 11 |
19 | Maksymilian Grochowski |
True | True | 0.1858 | 0.181700 | 12 |
20 | Łukasz Orlikowski |
True | True | 0.2103 | 0.210100 | 5 |
21 | team |
True | True | 0.2122 | 0.212800 | 7 |
22 | SJIR |
True | True | 0.2385 | 0.233600 | 7 |
23 | SoloTeam |
True | True | 0.4474 | 0.444100 | 1 |
24 | Cake |
True | True | 1.4975 | 1.494100 | 6 |
25 | DenseDropout |
False | True | 0.1505 | No report file found or report rejected. | 10 |
26 | krzmip |
False | True | 0.1509 | No report file found or report rejected. | 133 |
27 | aaaaacacsacs |
False | True | 0.1650 | No report file found or report rejected. | 11 |
28 | Mario |
False | True | 0.1660 | No report file found or report rejected. | 12 |
29 | Adma |
False | True | 0.1699 | No report file found or report rejected. | 2 |
30 | hawkz |
False | True | 0.1731 | No report file found or report rejected. | 27 |
31 | Aidan |
False | True | 0.1735 | No report file found or report rejected. | 5 |
32 | rdeggau |
False | True | 0.1757 | No report file found or report rejected. | 32 |
33 | Siasio |
False | True | 0.1758 | No report file found or report rejected. | 3 |
34 | lov505 |
False | True | 0.1813 | No report file found or report rejected. | 6 |
35 | Choraden |
False | True | 0.1819 | No report file found or report rejected. | 13 |
36 | michalm |
False | True | 0.1824 | No report file found or report rejected. | 2 |
37 | rllaskowski |
False | True | 0.1836 | No report file found or report rejected. | 16 |
38 | Bart |
False | True | 0.1866 | No report file found or report rejected. | 3 |
39 | DeepSpeditor |
False | True | 0.1867 | No report file found or report rejected. | 6 |
40 | KaLambda |
False | True | 0.1894 | No report file found or report rejected. | 12 |
41 | WhyNot |
False | True | 0.1938 | No report file found or report rejected. | 2 |
42 | Jakub Panasiuk |
False | True | 0.2203 | No report file found or report rejected. | 30 |
43 | Delavock |
False | True | 0.2256 | No report file found or report rejected. | 13 |
44 | csy |
False | True | 0.2312 | No report file found or report rejected. | 10 |
45 | Gr4g45 |
False | True | 0.2386 | No report file found or report rejected. | 9 |
46 | rkli |
False | True | 0.4200 | No report file found or report rejected. | 12 |
47 | RamazanY |
False | True | 0.5035 | No report file found or report rejected. | 1 |
48 | yoggo |
False | True | 0.5670 | No report file found or report rejected. | 10 |
49 | Maciejs |
False | True | 0.6990 | No report file found or report rejected. | 4 |
50 | blablabla |
False | True | 0.8367 | No report file found or report rejected. | 2 |
51 | Zyndri123 |
False | True | 1.0738 | No report file found or report rejected. | 1 |
The FedCSIS 2022 Challenge: Predicting the Costs of Forwarding Contracts challenge has come to an end. 135 teams from 24 countries from all over the world competed to predict the costs related to the execution of forwarding contracts. 1945 correctly formatted solutions were sent.
Congratulations to everyone who took up the challenge and submitted their solutions!
We are pleased to announce the winners of the competition:
- 1s place: Dymitr team - Dymitr Ruta, David Ming Liu, Ling Cen from the United Arab Emirates
- 2nd place: Cyan team - Haitao Xiao, Yuling Liu, Dan Du, Zhigang Lu from China
- 3rd place: hieuvq team - Quang Hieu Vu from Vietnam
The results of their work will be presented during a special session at the 17th Conference on Computer Science and Intelligence Systems, FedCSIS 2022.
We are also happy to announce that the additional prize for the most practical solution has been awarded to Sławomir Piroński from the Lord of the Machine Learning team!
This year's edition of the competition was organized by FedCSIS in cooperation with PTI and QED Software. The sponsor of the competition was Control System Software.
The task in this challenge is to design an accurate method for predicting costs associated with forwarding contracts, based on contract data and planned routes. The available training data sets describe a five-year history of contracts accepted by a large Polish company. In particular, the training data consist of two tables: css_main_training.csv and css_routes_training.csv. The first one contains basic information about the contracts, and the second one describes the main sections of the planned routes associated with each contract. In both tables, the first column (i.e., id_contract) contains identifiers that allow matching records from css_main_training.csv and css_routes_training.csv files. Additionally, the second column in the css_main_training.csv file (i.e., expenses) contains information about the prediction target. Values in this column are available only for the training data. Short descriptions of data columns will be available in separate files in the Data files section.
Additionally, for the convenience of participants, we provide an additional data table containing historical wholesale fuel prices for the period of training and test data.
Solution format: the test data is also divided into two separate tables, i.e., css_main_test.csv and css_routes_test.csv. They have the same format as the corresponding training files but values from the column expenses are missing in css_main_test.csv.
Solutions in this competition should be submitted to the online evaluation system as text files with predictions for test instances. Each row of the solution file should contain exactly one prediction. The ordering of the predictions should be the same as the ordering of instances from the css_main_test.csv file. In total, the solution file should contain exactly 72452 predictions.
Evaluation: the quality of submissions will be evaluated using the RMSE measure. Solutions will be evaluated online and the preliminary results will be published on the public leaderboard. The preliminary score will be computed on a small subset of the test records, fixed for all participants. The final evaluation will be performed after the completion of the competition using the remaining part of the test records. Those results will also be published online. It is important to note that only teams which submit a report describing their approach before the end of the challenge will qualify for the final evaluation.
- May 27, 2022 (23:59 GMT): deadline for submitting the predictions
- May 29, 2022 (23:59 GMT): deadline for sending the reports, end of the competition
- June 03, 2022: online publication of the final results, sending invitations for submitting short papers for the special session at FedCSIS'22
- July 01, 2022: deadline for submitting invited papers
- July 08, 2022: notification of paper acceptance
- July 21, 2022: camera-ready of accepted papers, and registration for the conference are due
Authors of the top-ranked solutions (based on the final evaluation scores) will be awarded prizes funded by our sponsors:
- 1,000 USD for the winning solution (+ the cost of one FedCSIS 2022 registration)
- 500 USD for the 2nd place solution (+ the cost of one FedCSIS 2022 registration)
- 250 USD for the 3rd place solution (+ the cost of one FedCSIS 2022 registration)
Moreover, Control System Software may award an additional prize (250 USD + the cost of one FedCSIS 2022 registration) to the team that develops the most practical solution to the task.
- Antoni Jamiołkowski, QED Software
- Andrzej Janusz, QED Software & University of Warsaw
- Rafał Tyl, QED Software
- Jacek Kamiński, QED Software
- Michał Okulewicz, Control System Software
- Juliusz Taniewski, Control System Software
In case of any questions please post on the competition forum or write an email at contact {at} knowledgepit.ml
Discussion | Author | Replies | Last post | |
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when is the deadline to merge teams? | M | 2 | by M Saturday, May 14, 2022, 18:23:46 |
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Test cases with no predictions | Artur | 2 | by Artur Wednesday, April 27, 2022, 21:05:54 |
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the backend evaluation program stopped since evening around 10:30pm 22 April 2022 | M | 4 | by M Saturday, April 23, 2022, 14:17:08 |
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Schedule update | Andrzej | 0 | by Andrzej Thursday, April 07, 2022, 15:02:44 |
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Error reading csv files | Debojit | 2 | by Debojit Wednesday, March 30, 2022, 10:05:19 |
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Route end datetime is earlier than route start datetime | Henry | 2 | by Henry Friday, March 25, 2022, 14:09:35 |
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Important announcement | Andrzej | 0 | by Andrzej Friday, March 18, 2022, 10:51:05 |
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Welcome to the FedCSIS 2022 Challenge | Andrzej | 0 | by Andrzej Tuesday, March 08, 2022, 16:24:43 |