Data

Transit Network Planning Problem data

Queensland University of Technology
Rosentreter, Joshua ; Corry, Paul
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25912/RDF_1731289726146&rft.title=Transit Network Planning Problem data&rft.identifier=10.25912/RDF_1731289726146&rft.publisher=Queensland University of Technology&rft.description=This dataset contains research output from studying the Transit Network Design Problem (TNDP). At a high level, the dataset includes: a novel transit network based on the Brisbane transport infrastructure, and results from the testing of new methods on the Brisbane network and existing benchmark networks (Mandl and Mumford). This dataset contains four subsets of data, and are related to Joshua Rosentreter's PhD Thesis. These are outlined below: Transit Network Dataset: A novel transit network for researchers to use when addressing the Transit Network Planning Problem. The network is based on the Brisbane City transportation infrastructure. MIP Model for TNFSP: Evaluations of existing solutions to the TNDP and TNDFSP using a variety of existing methods and a proposed mixed integer programming (MIP) model. Meta-Heuristic Method for TNDFSP: Results from a novel (adapted from existing) method designed to target the hub-and- spoke style structure of the demand within a metropolitan city based network. Hybrid Method for TNDFSP: Results from a novel method created through the hybridisation of the MIP model and meta-heuristic method. Further descriptions of the data are contained in the subfolders within. &rft.creator=Rosentreter, Joshua &rft.creator=Corry, Paul &rft.date=2024&rft.coverage=153.317870,-26.996845 152.668523,-26.996845 152.668523,-27.767441 153.317870,-27.767441 153.317870,-26.996845&rft_rights=© Queensland University of Technology, 2024.&rft_rights=Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/4.0/&rft_subject=Operations research&rft_subject=Applied mathematics&rft_subject=MATHEMATICAL SCIENCES&rft_subject=Statistics&rft_subject=Optimisation&rft_subject=Numerical and computational mathematics&rft_subject=Other mathematical sciences&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/4.0/

© Queensland University of Technology, 2024.

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Contact Information

Postal Address:
Mr Joshua Rosentreter

j.rosentreter@qut.edu.au

Full description

This dataset contains research output from studying the Transit Network Design Problem (TNDP). At a high level, the dataset includes: a novel transit network based on the Brisbane transport infrastructure, and results from the testing of new methods on the Brisbane network and existing benchmark networks (Mandl and Mumford).

This dataset contains four subsets of data, and are related to Joshua Rosentreter's PhD Thesis. These are outlined below:

  • Transit Network Dataset: A novel transit network for researchers to use when addressing the Transit Network Planning Problem. The network is based on the Brisbane City transportation infrastructure.
  • MIP Model for TNFSP: Evaluations of existing solutions to the TNDP and TNDFSP using a variety of existing methods and a proposed mixed integer programming (MIP) model.
  • Meta-Heuristic Method for TNDFSP: Results from a novel (adapted from existing) method designed to target the hub-and- spoke style structure of the demand within a metropolitan city based network.
  • Hybrid Method for TNDFSP: Results from a novel method created through the hybridisation of the MIP model and meta-heuristic method.

Further descriptions of the data are contained in the subfolders within.

Data time period: 05 2023 to 24 09 2024

This dataset is part of a larger collection

Click to explore relationships graph

153.31787,-26.99685 152.66852,-26.99685 152.66852,-27.76744 153.31787,-27.76744 153.31787,-26.99685

152.9931965,-27.382143

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