Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate

Demand-responsive transit (DRT) offers on-demand service for comfortable and convenient trips. Despite these advantages, efficient DRT operation requires addressing several considerations. This study resolves the conflict between passengers wanting quick travel and operators seeking maximum revenue...

Full description

Saved in:
Bibliographic Details
Main Authors: Sang-Wook Han, Sedong Moon, Dong-Kyu Kim
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Journal of Public Transportation
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1077291X24000286
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850063638617915392
author Sang-Wook Han
Sedong Moon
Dong-Kyu Kim
author_facet Sang-Wook Han
Sedong Moon
Dong-Kyu Kim
author_sort Sang-Wook Han
collection DOAJ
description Demand-responsive transit (DRT) offers on-demand service for comfortable and convenient trips. Despite these advantages, efficient DRT operation requires addressing several considerations. This study resolves the conflict between passengers wanting quick travel and operators seeking maximum revenue by formulating a multi-objective mixed-integer nonlinear programming model (MINLP) to maximize revenue and minimize total travel time. Additionally, DRT operators should balance the benefits of accepted passengers, concerned about increased travel time from new passengers, and requesting passengers who intend to use DRT. To address this, unlike previous studies with fixed time windows, this study introduces the maximum time delay rate (MTR), setting a proportional threshold for each accepted passenger's travel time based on their scheduled travel time, incorporating behavioral economics principles. In this view, the utility of increased or decreased time varies according to the scheduled travel time, considered a sunk cost. When the increased travel time from a new request is within the allowable range, the request is accepted, then the passenger decides whether to choose DRT over other modes. We apply our methodology to dy namic passenger requests generated from taxi data in Incheon, South Korea. For each combination of operational parameters of DRT, we plot a Pareto optimal set of revenue and total travel time. The results demonstrate the substantial influence of MTR and minimum fare distance on passenger numbers and travel time in DRT operations. This study's methodology and results help DRT operators and the public find desirable operation strategies.
format Article
id doaj-art-e3bb7fb046864840948b1cd19183753d
institution DOAJ
issn 2375-0901
language English
publishDate 2024-01-01
publisher Elsevier
record_format Article
series Journal of Public Transportation
spelling doaj-art-e3bb7fb046864840948b1cd19183753d2025-08-20T02:49:32ZengElsevierJournal of Public Transportation2375-09012024-01-012610010810.1016/j.jpubtr.2024.100108Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rateSang-Wook Han0Sedong Moon1Dong-Kyu Kim2Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Republic of KoreaInstitute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Republic of KoreaDepartment of Civil and Environmental Engineering and Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Republic of Korea; Corresponding author.Demand-responsive transit (DRT) offers on-demand service for comfortable and convenient trips. Despite these advantages, efficient DRT operation requires addressing several considerations. This study resolves the conflict between passengers wanting quick travel and operators seeking maximum revenue by formulating a multi-objective mixed-integer nonlinear programming model (MINLP) to maximize revenue and minimize total travel time. Additionally, DRT operators should balance the benefits of accepted passengers, concerned about increased travel time from new passengers, and requesting passengers who intend to use DRT. To address this, unlike previous studies with fixed time windows, this study introduces the maximum time delay rate (MTR), setting a proportional threshold for each accepted passenger's travel time based on their scheduled travel time, incorporating behavioral economics principles. In this view, the utility of increased or decreased time varies according to the scheduled travel time, considered a sunk cost. When the increased travel time from a new request is within the allowable range, the request is accepted, then the passenger decides whether to choose DRT over other modes. We apply our methodology to dy namic passenger requests generated from taxi data in Incheon, South Korea. For each combination of operational parameters of DRT, we plot a Pareto optimal set of revenue and total travel time. The results demonstrate the substantial influence of MTR and minimum fare distance on passenger numbers and travel time in DRT operations. This study's methodology and results help DRT operators and the public find desirable operation strategies.http://www.sciencedirect.com/science/article/pii/S1077291X24000286Demand-responsive transitParatransitMode ChoiceTaxi DataMulti-objective Optimization
spellingShingle Sang-Wook Han
Sedong Moon
Dong-Kyu Kim
Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
Journal of Public Transportation
Demand-responsive transit
Paratransit
Mode Choice
Taxi Data
Multi-objective Optimization
title Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
title_full Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
title_fullStr Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
title_full_unstemmed Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
title_short Multi-objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
title_sort multi objective optimization of demand responsive transit operations based on dynamic passenger requests using maximum time delay rate
topic Demand-responsive transit
Paratransit
Mode Choice
Taxi Data
Multi-objective Optimization
url http://www.sciencedirect.com/science/article/pii/S1077291X24000286
work_keys_str_mv AT sangwookhan multiobjectiveoptimizationofdemandresponsivetransitoperationsbasedondynamicpassengerrequestsusingmaximumtimedelayrate
AT sedongmoon multiobjectiveoptimizationofdemandresponsivetransitoperationsbasedondynamicpassengerrequestsusingmaximumtimedelayrate
AT dongkyukim multiobjectiveoptimizationofdemandresponsivetransitoperationsbasedondynamicpassengerrequestsusingmaximumtimedelayrate