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Multi-objective simulation optimization for complex urban mass rapid transit systems.
- Source :
-
Annals of Operations Research . Oct2021, Vol. 305 Issue 1/2, p449-486. 38p. - Publication Year :
- 2021
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02545330
- Volume :
- 305
- Issue :
- 1/2
- Database :
- Academic Search Index
- Journal :
- Annals of Operations Research
- Publication Type :
- Academic Journal
- Accession number :
- 152445748
- Full Text :
- https://doi.org/10.1007/s10479-019-03378-w