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Article: A novel excess commuting framework: Considering commuting efficiency and equity simultaneously

TitleA novel excess commuting framework: Considering commuting efficiency and equity simultaneously
Authors
KeywordsExcess commuting
commuting frequency
equity
Genetic Algorithm
smart card data
Issue Date2019
PublisherSage 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, 2019 How to Cite?
AbstractExcess 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 Identifierhttp://hdl.handle.net/10722/278829
ISSN
2017 Impact Factor: 2.046

 

DC FieldValueLanguage
dc.contributor.authorZhang, Y-
dc.contributor.authorZhang, Y-
dc.contributor.authorZhou, J-
dc.date.accessioned2019-10-21T02:14:48Z-
dc.date.available2019-10-21T02:14:48Z-
dc.date.issued2019-
dc.identifier.citationEnvironment and Planning B: Urban Analytics and City Science, 2019-
dc.identifier.issn2399-8083-
dc.identifier.urihttp://hdl.handle.net/10722/278829-
dc.description.abstractExcess 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.languageeng-
dc.publisherSage Publications Ltd. The Journal's web site is located at http://journals.sagepub.com/home/epb-
dc.relation.ispartofEnvironment and Planning B: Urban Analytics and City Science-
dc.rightsEnvironment and Planning B: Urban Analytics and City Science. Copyright © Sage Publications Ltd.-
dc.subjectExcess commuting-
dc.subjectcommuting frequency-
dc.subjectequity-
dc.subjectGenetic Algorithm-
dc.subjectsmart card data-
dc.titleA novel excess commuting framework: Considering commuting efficiency and equity simultaneously-
dc.typeArticle-
dc.identifier.emailZhou, J: zhoujp@hku.hk-
dc.identifier.authorityZhou, J=rp02236-
dc.description.naturepostprint-
dc.identifier.doi10.1177/2399808319851517-
dc.identifier.scopuseid_2-s2.0-85066819126-
dc.identifier.hkuros307755-
dc.identifier.spage239980831985151-
dc.identifier.epage239980831985151-
dc.publisher.placeUnited Kingdom-

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