Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming

Nowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling Nonetheless, suc...

Full description

Bibliographic Details
Main Authors: Haris Ballis, Loukas Dimitriou
Format: Article
Language:English
Published: TU Delft Open 2020-10-01
Series:European Journal of Transport and Infrastructure Research
Online Access:https://journals.open.tudelft.nl/ejtir/article/view/5303
id doaj-8472a5f72a7640bb88a1470c8b4714ca
record_format Article
spelling doaj-8472a5f72a7640bb88a1470c8b4714ca2021-07-26T08:30:55ZengTU Delft OpenEuropean Journal of Transport and Infrastructure Research1567-71412020-10-0120412110.18757/ejtir.2020.20.4.53034714Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programmingHaris Ballis0Loukas Dimitriou1Department of Civil and Environmental Engineering, University of CyprusDepartment of Civil and Environmental Engineering, University of CyprusNowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling Nonetheless, such approaches usually require significant amounts of detailed and fine-grained data which are not always easily accessible. The methodology presented in this paper aims to generate individual home-based trip-chains (i.e. tours) utilising aggregated sources of information, primarily, typical Origin-Destination matrices (ODs) and secondarily travel surveys. A suitable framework able to optimally identify ‘hidden’ tours in typical ODs is proposed and evaluated through its application on a set of multi-period OD matrices, covering an urban area of realistic size. This novel methodological framework synthesises the individual tours by combining and elevating advanced graph theory and integer programming concepts. The performance of the proposed methodology proves particularly encouraging since high estimation accuracy (greater than 85%) was achieved even for the most challenging examined test-case. The presented results provide positive evidence that information regarding travel behaviour on an individual level can be produced based on aggregated data sources such as OD matrices. This element is particularly valuable towards the analysis of mobility at the person-level, especially within the framework of agent-based modelling.https://journals.open.tudelft.nl/ejtir/article/view/5303
collection DOAJ
language English
format Article
sources DOAJ
author Haris Ballis
Loukas Dimitriou
spellingShingle Haris Ballis
Loukas Dimitriou
Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
European Journal of Transport and Infrastructure Research
author_facet Haris Ballis
Loukas Dimitriou
author_sort Haris Ballis
title Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
title_short Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
title_full Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
title_fullStr Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
title_full_unstemmed Optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
title_sort optimal synthesis of tours from multi-period origin-destination matrices using elements from graph theory and integer programming
publisher TU Delft Open
series European Journal of Transport and Infrastructure Research
issn 1567-7141
publishDate 2020-10-01
description Nowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling Nonetheless, such approaches usually require significant amounts of detailed and fine-grained data which are not always easily accessible. The methodology presented in this paper aims to generate individual home-based trip-chains (i.e. tours) utilising aggregated sources of information, primarily, typical Origin-Destination matrices (ODs) and secondarily travel surveys. A suitable framework able to optimally identify ‘hidden’ tours in typical ODs is proposed and evaluated through its application on a set of multi-period OD matrices, covering an urban area of realistic size. This novel methodological framework synthesises the individual tours by combining and elevating advanced graph theory and integer programming concepts. The performance of the proposed methodology proves particularly encouraging since high estimation accuracy (greater than 85%) was achieved even for the most challenging examined test-case. The presented results provide positive evidence that information regarding travel behaviour on an individual level can be produced based on aggregated data sources such as OD matrices. This element is particularly valuable towards the analysis of mobility at the person-level, especially within the framework of agent-based modelling.
url https://journals.open.tudelft.nl/ejtir/article/view/5303
work_keys_str_mv AT harisballis optimalsynthesisoftoursfrommultiperiodorigindestinationmatricesusingelementsfromgraphtheoryandintegerprogramming
AT loukasdimitriou optimalsynthesisoftoursfrommultiperiodorigindestinationmatricesusingelementsfromgraphtheoryandintegerprogramming
_version_ 1721282112108101632