Data-Driven Transit Network Design at Scale
<jats:p> Mass transit remains the most efficient way to service a densely packed commuter population. However, reliability issues and increasing competition in the transportation space have led to declining ridership across the United States, and transit agencies must also operate under tight...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Institute for Operations Research and the Management Sciences (INFORMS)
2022
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| Online Access: | https://hdl.handle.net/1721.1/144080 |
| _version_ | 1811092809518678016 |
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| author | Bertsimas, Dimitris Ng, Yee Sian Yan, Julia |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Bertsimas, Dimitris Ng, Yee Sian Yan, Julia |
| author_sort | Bertsimas, Dimitris |
| collection | MIT |
| description | <jats:p> Mass transit remains the most efficient way to service a densely packed commuter population. However, reliability issues and increasing competition in the transportation space have led to declining ridership across the United States, and transit agencies must also operate under tight budget constraints. Recent attempts at using bus network redesign to improve ridership have attracted attention from various transit authorities. However, the analysis seems to rely on ad hoc methods, for example, considering each line in isolation and using manual incremental adjustments with backtracking. We provide a holistic approach to designing a transit network using column generation. Our approach scales to hundreds of stops, and we demonstrate its usefulness on a case study with real data from Boston. </jats:p> |
| first_indexed | 2024-09-23T15:27:25Z |
| format | Article |
| id | mit-1721.1/144080 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:27:25Z |
| publishDate | 2022 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/1440802023-06-12T17:35:00Z Data-Driven Transit Network Design at Scale Bertsimas, Dimitris Ng, Yee Sian Yan, Julia Sloan School of Management Massachusetts Institute of Technology. Operations Research Center <jats:p> Mass transit remains the most efficient way to service a densely packed commuter population. However, reliability issues and increasing competition in the transportation space have led to declining ridership across the United States, and transit agencies must also operate under tight budget constraints. Recent attempts at using bus network redesign to improve ridership have attracted attention from various transit authorities. However, the analysis seems to rely on ad hoc methods, for example, considering each line in isolation and using manual incremental adjustments with backtracking. We provide a holistic approach to designing a transit network using column generation. Our approach scales to hundreds of stops, and we demonstrate its usefulness on a case study with real data from Boston. </jats:p> 2022-07-27T16:54:50Z 2022-07-27T16:54:50Z 2021 2022-07-27T16:49:15Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/144080 Bertsimas, Dimitris, Ng, Yee Sian and Yan, Julia. 2021. "Data-Driven Transit Network Design at Scale." Operations Research, 69 (4). en 10.1287/OPRE.2020.2057 Operations Research Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) MIT web domain |
| spellingShingle | Bertsimas, Dimitris Ng, Yee Sian Yan, Julia Data-Driven Transit Network Design at Scale |
| title | Data-Driven Transit Network Design at Scale |
| title_full | Data-Driven Transit Network Design at Scale |
| title_fullStr | Data-Driven Transit Network Design at Scale |
| title_full_unstemmed | Data-Driven Transit Network Design at Scale |
| title_short | Data-Driven Transit Network Design at Scale |
| title_sort | data driven transit network design at scale |
| url | https://hdl.handle.net/1721.1/144080 |
| work_keys_str_mv | AT bertsimasdimitris datadriventransitnetworkdesignatscale AT ngyeesian datadriventransitnetworkdesignatscale AT yanjulia datadriventransitnetworkdesignatscale |