Multi-objective simulation optimization for complex urban mass rapid transit systems

Author(s)
David Schmaranzer, Roland Braune, Karl Franz Dörner
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.

Organisation(s)
Department of Business Decisions and Analytics, Research Network Data Science
Journal
Annals of Operations Research
Volume
305
Pages
449-486
No. of pages
38
ISSN
0254-5330
DOI
https://doi.org/10.1007/s10479-019-03378-w
Publication date
09-2019
Peer reviewed
Yes
Austrian Fields of Science 2012
502052 Business administration
Keywords
ASJC Scopus subject areas
Decision Sciences(all), Management Science and Operations Research
Portal url
https://ucris.univie.ac.at/portal/en/publications/multiobjective-simulation-optimization-for-complex-urban-mass-rapid-transit-systems(bfaa31bc-5771-48dc-981b-6872546df517).html