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Article: A novel excess commuting framework: Considering commuting efficiency and equity simultaneously
Title | A novel excess commuting framework: Considering commuting efficiency and equity simultaneously |
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Authors | |
Keywords | Excess commuting commuting frequency equity Genetic Algorithm smart card data |
Issue Date | 2021 |
Publisher | Sage Publications Ltd. The Journal's web site is located at http://journals.sagepub.com/home/epb |
Citation | Environment and Planning B: Urban Analytics and City Science, 2021, v. 48 n. 1, p. 151-168 How to Cite? |
Abstract | Excess commuting, which concerns the differences between the actual commute and the optimal (minimum) commute afforded by a given distribution of jobs and housing, i.e., urban form, has been extensively studied across disciplines. In the existing excess commuting framework, the optimal commute considers commuting efficiency but overlooks commuting equity, which is defined as the variation in commuting cost across workers before and after the optimisation. The framework also overlooks the variation in commuting frequency across workers for a period of interest, which also affects the overall commuting cost for the period. In this paper, we propose a novel excess commuting framework using a Greedy-Initialisation-based Genetic Algorithm, where the optimal commute accounts for commuting efficiency and equity and commuting-frequency variation simultaneously. We illustrate and calibrate the framework using one-month metro smart card data in Shanghai. Comparing with two other existing models, the Greedy-Initialisation-based Genetic Algorithm can generate a commuting pattern that balances commuting efficiency and commuting equity, which the existing commuting framework and corresponding algorithms cannot. |
Persistent Identifier | http://hdl.handle.net/10722/278829 |
ISSN | 2023 Impact Factor: 2.6 2023 SCImago Journal Rankings: 0.929 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Zhou, J | - |
dc.date.accessioned | 2019-10-21T02:14:48Z | - |
dc.date.available | 2019-10-21T02:14:48Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Environment and Planning B: Urban Analytics and City Science, 2021, v. 48 n. 1, p. 151-168 | - |
dc.identifier.issn | 2399-8083 | - |
dc.identifier.uri | http://hdl.handle.net/10722/278829 | - |
dc.description.abstract | Excess commuting, which concerns the differences between the actual commute and the optimal (minimum) commute afforded by a given distribution of jobs and housing, i.e., urban form, has been extensively studied across disciplines. In the existing excess commuting framework, the optimal commute considers commuting efficiency but overlooks commuting equity, which is defined as the variation in commuting cost across workers before and after the optimisation. The framework also overlooks the variation in commuting frequency across workers for a period of interest, which also affects the overall commuting cost for the period. In this paper, we propose a novel excess commuting framework using a Greedy-Initialisation-based Genetic Algorithm, where the optimal commute accounts for commuting efficiency and equity and commuting-frequency variation simultaneously. We illustrate and calibrate the framework using one-month metro smart card data in Shanghai. Comparing with two other existing models, the Greedy-Initialisation-based Genetic Algorithm can generate a commuting pattern that balances commuting efficiency and commuting equity, which the existing commuting framework and corresponding algorithms cannot. | - |
dc.language | eng | - |
dc.publisher | Sage Publications Ltd. The Journal's web site is located at http://journals.sagepub.com/home/epb | - |
dc.relation.ispartof | Environment and Planning B: Urban Analytics and City Science | - |
dc.rights | Environment and Planning B: Urban Analytics and City Science. Copyright © Sage Publications Ltd. | - |
dc.subject | Excess commuting | - |
dc.subject | commuting frequency | - |
dc.subject | equity | - |
dc.subject | Genetic Algorithm | - |
dc.subject | smart card data | - |
dc.title | A novel excess commuting framework: Considering commuting efficiency and equity simultaneously | - |
dc.type | Article | - |
dc.identifier.email | Zhou, J: zhoujp@hku.hk | - |
dc.identifier.authority | Zhou, J=rp02236 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1177/2399808319851517 | - |
dc.identifier.scopus | eid_2-s2.0-85066819126 | - |
dc.identifier.hkuros | 307755 | - |
dc.identifier.volume | 48 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 151 | - |
dc.identifier.epage | 168 | - |
dc.identifier.isi | WOS:000612136400010 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 2399-8083 | - |