A Bi-Objective Optimization Model for Fare Structure Design in Public Transport

Philine Schiewe*, Anita Schöbel*, Reena Urban*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Abstract

Fare planning in public transport is important from the view of passengers as well as of operators. In this paper, we propose a bi-objective model that maximizes the revenue as well as the number of attracted passengers. The potential demand per origin-destination pair is divided into demand groups that have their own willingness how much to pay for using public transport, i.e., a demand group is only attracted as public transport passengers if the fare does not exceed their willingness to pay. We study the bi-objective problem for flat and distance tariffs and develop specialized algorithms to compute the Pareto front in quasilinear or cubic time, respectively. Through computational experiments on structured data sets we evaluate the running time of the developed algorithms in practice and analyze the number of non-dominated points and their respective efficient solutions.

Original languageEnglish
Title of host publication24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2024
EditorsPaul C. Bouman, Spyros C. Kontogiannis
PublisherSchloss Dagstuhl - Leibniz-Zentrum für Informatik
Pages1-19
Number of pages19
ISBN (Electronic)9783959773508
DOIs
Publication statusPublished - 7 Oct 2024
MoE publication typeA4 Conference publication
EventSymposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems - London, United Kingdom
Duration: 5 Sept 20246 Sept 2024
Conference number: 24

Publication series

NameOpenAccess Series in Informatics
Volume123
ISSN (Print)2190-6807

Conference

ConferenceSymposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems
Abbreviated titleATMOS
Country/TerritoryUnited Kingdom
CityLondon
Period05/09/202406/09/2024

Keywords

  • algorithm
  • bi-objective
  • fare structure design
  • modeling
  • Public transport

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