Macro Scale Models for Freight Railroad Terminals

This project has developed a yard capacity model for macro-level analysis. The authors developed optimization models to investigate three sequencing decisions at the areas inspection, hump, and assembly. The optimization considers multiple engines and inspection groups. The model can be solved by existing commercial optimization solvers for one typical planning horizon, such as 24 hour. Numerical experiments and case study based on historical data from a U.S. Class I railroad demonstrate that the proposed solution method yields better sequences and schedules, as measured by the total dwell time, compared with the practice of static sequencing. Furthermore, the results indicate that the handling capacity should be balanced among different classification steps to maximize the overall yard capacity. Furthermore, the research considers dynamic railcar planning in railroad classification yards. The plan decides the assignment of railcars from inbound trains to outbound trains under various size limitations of outbound trains and allows dynamic sequencing of inbound train classification and outbound train assembly. A mixed-integer program is presented for the problem along with a heuristic algorithm based on the harmony search strategy. Generic simulation models have been built for classification yards to understand the macro-level relationship between volumes and dwell times at yards and define yard capacity. The simulation model has been verified by the historical data from about 10 classification yards with various parameters, such as the number of tracks in each area, humps, hump engines and pull engines. The simulation mode is then used to create a large dataset to fit a general capacity model with the minimum mean square errors.


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; References; Tables;
  • Pagination: 30p

Subject/Index Terms

Filing Info

  • Accession Number: 01599229
  • Record Type: Publication
  • Report/Paper Numbers: NURail2012-UTK-R04
  • Contract Numbers: DTRT12-G-UTC18
  • Created Date: Apr 26 2016 1:39PM