Multi-objective simulation optimization for complex urban mass rapid transit systems
- Autor(en)
- David Schmaranzer, Roland Braune, Karl Franz Dörner
- Abstrakt
In this paper, we present a multi-objective simulation-based headway optimization for complex urban mass rapid transit systems. Real-world applications often confront conflicting goals of cost versus service level. We propose a two-phase algorithm that combines the single-objective covariance matrix adaptation evolution strategy with a problem-specific multi-directional local search. With a computational study, we compare our proposed method against both a multi-objective covariance matrix adaptation evolution strategy and a non-dominated sorting genetic algorithm. The integrated discrete event simulation model has several stochastic elements. Fluctuating demand (i.e., creation of passengers) is driven by hourly origin-destination-matrices based on mobile phone and infrared count data. We also consider the passenger distribution along waiting platforms and within vehicles. Our two-phase optimization scheme outperforms the comparative approaches, in terms of both spread and the accuracy of the resulting Pareto front approximation.
- Organisation(en)
- Institut für Business Decisions and Analytics, Forschungsverbund Data Science
- Journal
- Annals of Operations Research
- Band
- 305
- Seiten
- 449-486
- Anzahl der Seiten
- 38
- ISSN
- 0254-5330
- DOI
- https://doi.org/10.1007/s10479-019-03378-w
- Publikationsdatum
- 09-2019
- Peer-reviewed
- Ja
- ÖFOS 2012
- 502052 Betriebswirtschaftslehre
- Schlagwörter
- ASJC Scopus Sachgebiete
- Decision Sciences(all), Management Science and Operations Research
- Link zum Portal
- https://ucris.univie.ac.at/portal/de/publications/multiobjective-simulation-optimization-for-complex-urban-mass-rapid-transit-systems(bfaa31bc-5771-48dc-981b-6872546df517).html