Data and Archive of Previous Problem Solving Competition

Problem Repository

This effort is targeted at increasing awareness about difficult railroad problems for the OR community, so that railroad industry can benefit from increased research activity. Complete details of the repository, processes and first problem were presented at the RAS business meeting in Charlotte in 2011.

The objective of this problem repository is to facilitate a platform where:

  1. Reallife railroad application problems are presented along with dataset(s) and solutions publicly available for anyone to research, develop and test solution approaches.
  2. Researchers may showcase their results, engage in questions, answers and discussions and measure the performance of different solution approaches.

All information that is available on RAS website is public. Neither RAS, nor the company/entity (who provided the problem/data to the repository) may claim intellectual property rights on the outcome of the research by someone who used the data/problem description. RAS is open to suggestions - please contact any of the officers if you have any suggestions or start a discussion on our LinkedIn page.

Problem Name

Contact Information

Details

Designing real-time traffic management

Problem chair: Marc Meketon (Oliver Wyman) & Nicola Coviello (TrenoLab)
Problem Owner: Giorgio Medeossi (TrenoLab)

Predictive ETA Modeling

Problem chair: Hyeong Suk Na (South Dakota School of Mines & Technology)
Problem owner: Stephen Ecker (Trinity Rail)

railwayapplicationssection@gmail.com


Train Travel-Time Estimation Problem chair: Jay Baillargeon (U.S. DOT)
Problem owner: Krishna Jha (Optym)
railwayapplicationssection@gmail.com
Integrated train blocking and shipment path optimization (TBSP) Problem chair: Andrea Arias Llorenty (BNSF)

Problem owners: Boliang Lin (BJTU) and Xuesong Zhou (ASU)
 railwayapplicationssection@gmail.com

Predicting Near Term Train Schedule Performance and Delay Michael F. Gorman
University of Dayton
railwayapplicationssection@gmail.com
Data Analytics for Railroad Empty-to-Load
Peak Kips Prediction
Clark Cheng
Norfolk Southern
Clark.Cheng@nscorp.com

Routing Trains through a Railway Network

Francesco Corman
Delft University of Technology
F.Corman@tudelft.nl

Track geometry analytics

Francesco Corman
Delft University of Technology
F.Corman@tudelft.nl

Railroad Hump Yard Block-to-Track Assignment

Xiaopeng Li
Mississippi State University
xli@cee.msstate.edu

Modeling Railroad Yard Capacity

Sandra D. Eksioglu
Clemson University
seksiog@clemson.edu

Movement Planner Algorithm Design For Dispatching On Multi-Track Territories

Train Design Optimization Problem

Jagadish Jampani
CSX Transportation, Inc.
Jagadish_Jampani@csx.com

Locomotive Refueling Problem

Homarjun Agrahari
BNSF Railway
Homarjun.Agrahari@bnsf.com