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A good or a bad timetable: Do different evaluation functions agree?

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Listed:
  • Hartleb, J.
  • Schmidt, M.E.
  • Friedrich, M.
  • Huisman, D.

Abstract

We compare different evaluation functions that are all designed to mea- sure the quality of a timetable from passengers’ perspective. Already in small examples fundamentally different timetables can be preferred by evaluation functions that seem to be similar. To investigate this effect in practice, we design a set of evaluation functions as representatives for a wide range of commonly used evaluation functions in optimization models, evaluation applications, or choice models. These functions are compared by analyzing their evaluation values of multiple timetables in three case studies. To investigate to what extent these evaluation functions agree on a good or a bad timetable, we apply cluster analysis as well as a novel methodology to quantify the similarity of pairs of evaluation functions based on the values they yield on different timetables. We empirically show that the choice of the evaluation function can have a significant impact on the assessed quality of timetables, and thus also on which timetable is considered optimal, even though all evaluation functions are meant to evaluate the same - the quality of a timetable from passengers’ perspective. Due to the structure of the designed evaluation functions, it is further possible to identify which components of the func- tions influence the results of an evaluation and under which conditions they this is most pronounced. This can be very beneficial when designing timetable evaluation functions for passengers.

Suggested Citation

  • Hartleb, J. & Schmidt, M.E. & Friedrich, M. & Huisman, D., 2019. "A good or a bad timetable: Do different evaluation functions agree?," ERIM Report Series Research in Management ERS-2019-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:115831
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    References listed on IDEAS

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    2. de Jong, Gerard & Daly, Andrew & Pieters, Marits & van der Hoorn, Toon, 2007. "The logsum as an evaluation measure: Review of the literature and new results," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 874-889, November.
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    6. Robenek, Tomáš & Maknoon, Yousef & Azadeh, Shadi Sharif & Chen, Jianghang & Bierlaire, Michel, 2016. "Passenger centric train timetabling problem," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 107-126.
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    Cited by:

    1. Julius Pätzold, 2021. "Finding robust periodic timetables by integrating delay management," Public Transport, Springer, vol. 13(2), pages 349-374, June.
    2. Hartleb, J. & Schmidt, M.E., 2019. "Railway timetabling with integrated passenger distribution," ERIM Report Series Research in Management ERS-2019-012-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Hartleb, Johann & Schmidt, Marie, 2022. "Railway timetabling with integrated passenger distribution," European Journal of Operational Research, Elsevier, vol. 298(3), pages 953-966.
    4. Polinder, Gert-Jaap & Schmidt, Marie & Huisman, Dennis, 2021. "Timetabling for strategic passenger railway planning," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 111-135.
    5. Polinder, G.-J. & Cacchiani, V. & Schmidt, M.E. & Huisman, D., 2020. "An iterative heuristic for passenger-centric train timetabling with integrated adaption times," ERIM Report Series Research in Management ERS-2020-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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