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Population-based simulation optimization for urban mass rapid transit networks

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 simulation-based headway optimization for urban mass rapid transit networks. The underlying discrete event simulation model contains several stochastic elements, including time-dependent demand and turning maneuver times as well as direction-dependent vehicle travel and passenger transfer times. Passenger creation is a Poisson process that uses hourly origin–destination-matrices based on anonymous mobile phone and infrared count data. The numbers of passengers on platforms and within vehicles are subject to capacity restrictions. As a microscopic element, passenger distribution along platforms and within vehicles is considered. The bi-objective problem, involving cost reduction and service level improvement, is transformed into a single-objective optimization problem by normalization and scalarization. Population-based evolutionary algorithms and different solution encoding variants are applied. Computational experience is gained from test instances based on real-world data (i.e., the Viennese subway network). A covariance matrix adaptation evolution strategy performs best in most cases, and a newly developed encoding helps accelerate the optimization process by producing better short-term results.

Suggested Citation

  • David Schmaranzer & Roland Braune & Karl F. Doerner, 2020. "Population-based simulation optimization for urban mass rapid transit networks," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 767-805, December.
    • Handle: RePEc:spr:flsman:v:32:y:2020:i:4:d:10.1007_s10696-019-09352-9
    DOI: 10.1007/s10696-019-09352-9
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