A Bi objective robust possibilistic programming metro timetabling in skip-stop pattern

Articles in Press

Document Type : Original Article

Authors

1 M.S in Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 Assistant Professor of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

10.22034/tri.2023.359971.3083

Abstract

In the case of a metro disruption, the planned timetable cannot be operated and a large number of passengers are left stranded in the stations. When the disruption is over, some stations may be skipped in the recovery period, which speeds up the circulation of trains and makes the number of stranded passengers reduce faster. Considering an over- crowded and time-dependent passenger flow, this paper proposes an optimization model to reschedule a metro line. To achieve a balance between theoretical validity and compu- tational convenience, the optimization model is decomposed, and an iterative algorithm is proposed to solve the model. Numerical experiments based on the Beijing Metro are carried out, the results of which verify the effectiveness and efficiency of our method. We used different types of robust possibilistic programming (RPP) approaches for coping with uncertain parameters and multi-choice goal programming for solving multi-objective problem. Robust possibilistic approaches can be classified into three groups: hard worst case robust programming, soft worst case robust programming and realistic robust programming. By solving numerical example the value of goal programming objective function is compared in different approaches. Evalution results illustrate the performance and applicability of the RPP models.

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Journal of Transportation Research

Articles in Press, Accepted Manuscript
Available Online from 09 April 2023

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