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Multi-objective simulation optimization for complex urban mass rapid transit systems

Author

Listed:
  • David Schmaranzer

    (University of Vienna
    University of Vienna)

  • Roland Braune

    (University of Vienna)

  • Karl F. Doerner

    (University of Vienna
    University of Vienna
    University of Vienna)

Abstract

In this paper, we present a multi-objective simulation-based headway optimization for complex urban mass rapid transit systems. Real-world applications often confront conflicting goals of cost versus service level. We propose a two-phase algorithm that combines the single-objective covariance matrix adaptation evolution strategy with a problem-specific multi-directional local search. With a computational study, we compare our proposed method against both a multi-objective covariance matrix adaptation evolution strategy and a non-dominated sorting genetic algorithm. The integrated discrete event simulation model has several stochastic elements. Fluctuating demand (i.e., creation of passengers) is driven by hourly origin-destination-matrices based on mobile phone and infrared count data. We also consider the passenger distribution along waiting platforms and within vehicles. Our two-phase optimization scheme outperforms the comparative approaches, in terms of both spread and the accuracy of the resulting Pareto front approximation.

Suggested Citation

  • David Schmaranzer & Roland Braune & Karl F. Doerner, 2021. "Multi-objective simulation optimization for complex urban mass rapid transit systems," Annals of Operations Research, Springer, vol. 305(1), pages 449-486, October.
    • Handle: RePEc:spr:annopr:v:305:y:2021:i:1:d:10.1007_s10479-019-03378-w
    DOI: 10.1007/s10479-019-03378-w
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