Latest revision as of 21:29, 22 March 2021

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.

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1007/s10696-019-09352-9 under the license https://creativecommons.org/licenses/by

• https://link.springer.com/content/pdf/10.1007/s10696-019-09352-9.pdf under the license https://creativecommons.org/licenses/by/4.0

• http://hdl.handle.net/11353/10.1073063,

http://dx.doi.org/10.1007/s10696-019-09352-9,

https://phaidra.univie.ac.at/o:1073063 under the license cc-by

• http://link.springer.com/content/pdf/10.1007/s10696-019-09352-9.pdf,

http://link.springer.com/article/10.1007/s10696-019-09352-9/fulltext.html,

http://dx.doi.org/10.1007/s10696-019-09352-9 under the license http://creativecommons.org/licenses/by/4.0/

• https://link.springer.com/article/10.1007/s10696-019-09352-9,

https://paperity.org/p/193531699/population-based-simulation-optimization-for-urban-mass-rapid-transit-networks,

https://academic.microsoft.com/#/detail/2944231947 under the license https://creativecommons.org/licenses/by/4.0