Titel
Population-based simulation optimization for urban mass rapid transit networks
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.
Stichwort
Simulation-based optimizationPublic transportationHeadway optimizationTransit network frequencies setting problemPopulation-based metaheuristic
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:1073063
Erschienen in
Titel
Flexible Services and Manufacturing Journal
Verlag
Springer Science and Business Media LLC
Erscheinungsdatum
2019
Zugänglichkeit
Rechteangabe
© The Author(s) 2019

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