Population-based simulation optimization for urban mass rapid transit networks

David Schmaranzer, Roland Braune, Karl Franz Dörner

Publications: Contribution to journalArticlePeer Reviewed

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.

Original languageEnglish
Pages (from-to)767–805
Number of pages39
JournalFlexible Services and Manufacturing Journal
Volume32
Issue number4
Early online date10 May 2019
DOIs
Publication statusPublished - Dec 2020

Austrian Fields of Science 2012

  • 502052 Business administration

Keywords

  • MR
  • BWL
  • DESIGN
  • Headway optimization
  • TIME
  • MODEL
  • PUBLIC-TRANSIT
  • Public transportation
  • GENETIC ALGORITHM
  • DEMAND
  • Population-based metaheuristic
  • Transit network frequencies setting problem
  • FREQUENCY
  • HEADWAY
  • Simulation-based optimization

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