Population-based simulation optimization for urban mass rapid transit networks

David Schmaranzer (), Roland Braune () and Karl F. Doerner ()
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David Schmaranzer: University of Vienna
Roland Braune: University of Vienna
Karl F. Doerner: University of Vienna

Flexible Services and Manufacturing Journal, 2020, vol. 32, issue 4, No 2, 767-805

Abstract: 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.

Keywords: Simulation-based optimization; Public transportation; Headway optimization; Transit network frequencies setting problem; Population-based metaheuristic (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10696-019-09352-9

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