Business Intelligence for Gang Scheduling

Railway tracks wear down and thus need to be constantly maintained. Groups of maintenance workers, called gangs, are responsible for such maintenance tasks. Throughout a year, a gang works for a few days in a particular track section and then reallocates to another section. Railways incur significant expenses related to gangs. They range from the direct costs such as salary and travel allowance to indirect costs consisting primarily of the impact to operational disruptions. It is thus of vital importance to railways to schedule the gangs as efficiently as possible. In conjunction with the Norfolk Southern Corporation (herein called NS), we have started developing a gang scheduling information system based on business intelligence and state-of-the-art analytics. At the core of the system there will be a sophisticated optimization algorithm considering the multi-objective nature of the problem and all of the underlying complexities. The algorithm will be composed of initially constructing a schedule and then iteratively refining the schedule based on state-of-the-art mathematical programming techniques combined with very large neighborhood local search strategies. After initially rolling out the system at NS, we plan to repackage the software around the Software-as-a-Service business model and offer it to other railways.


  • English


  • Status: Completed
  • Funding: $67594.00
  • Contract Numbers:


  • Sponsor Organizations:

    Center for the Commercialization of Innovative Transportation Technology

    Northwestern University
    Evanston, IL  United States  60208
  • Principal Investigators:

    Klabjan, Diego

  • Start Date: 20090101
  • Expected Completion Date: 0
  • Actual Completion Date: 20120312
  • Source Data: RiP Project 22141

Subject/Index Terms

Filing Info

  • Accession Number: 01482655
  • Record Type: Research project
  • Source Agency: Center for the Commercialization of Innovative Transportation Technology
  • Contract Numbers: Y2-01
  • Files: UTC, RIP
  • Created Date: May 30 2013 1:01AM