Service-oriented collaborative optimization for train timetabling and stop pattern planning on urban rail transit lines

This study proposes a collaborative optimization framework for train timetabling and stop pattren planning on urban rail transit lines considering time-dependent passenger demand. By embedding the constraints of train stop pattern into the train timetabling optimization process, the authors particularly aim to minimize the total passenger travel time on an urban rail transit line. The theoretical analysis indicates that the proposed optimization model is in essence large-scale for real large-scale applications. Therefore, a binary variable determination (BVD) method, which can transform complicated linear constraints into simple logical constraints, is proposed to calculate the binary variables rapidly and easily. Then a genetic algorithm (GA) based on the BVD method is developed to solve the proposed model for real cases. A case study of Batong line in Beijing subway network is adopted to evaluate the proposed model and algorithm. This study can provide rail transit operators beneficial advice to improve the operational service level on urban rail transit lines.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AP065 Standing Committee on Rail Transit Systems.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Shang, Pan
    • Li, Ruimin
    • Yang, Liya
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 19p

Subject/Index Terms

Filing Info

  • Accession Number: 01697657
  • Record Type: Publication
  • Report/Paper Numbers: 19-02671
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:33AM