A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation
Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passen...
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sg-ntu-dr.10356-1639022022-12-21T06:57:47Z A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation Li, Feng Guo, Xin Zhou, Li Wu, Jianjun Li, Tongfei School of Civil and Environmental Engineering Engineering::Civil engineering Time-Dependent Scheduling Capacity Matching Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passenger revenue over a longer period. Considering the collaborative urban public transport services achieve a seamless movement for both passengers and goods, and could reduce the adverse effects of the existing urban public transport systems. Therefore, a mixed-integer linear programming model introducing the concept of capacity matching is proposed to assist this collaborative urban freight service network in minimising total freight transport time at station hubs and not affecting passenger transportation in this paper. Moreover, an efficient improved optimisation algorithm based on the Artificial Bee Colony Algorithm (ABC) is designed, and the numerical examples and real cases are illustrated to demonstrate the feasibility and effectiveness of the proposed model and algorithm. The performance evaluations suggest that the coordinated operating strategy of the collaborative freight transportation system supports increasing mobility demands for freight, resulting in declining congestion levels and reducing transport emissions, while no influence in passenger transport, notably in urban areas. This work was supported by the Fundamental Research Funds for the Central Universities [grant number 2021JBM014], the National Natural Science Foundation of China [grant numbers 72101013, 71890972/71890970, 71621001], the Beijing Intelligent Logistics System Collaborative Innovation Centre [grant number BILSCIC-2019KF-11], and the 111 Project (No. B20071). 2022-12-21T06:57:46Z 2022-12-21T06:57:46Z 2022 Journal Article Li, F., Guo, X., Zhou, L., Wu, J. & Li, T. (2022). A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation. International Journal of Production Research, 60(20), 6303-6328. https://dx.doi.org/10.1080/00207543.2021.1991021 0020-7543 https://hdl.handle.net/10356/163902 10.1080/00207543.2021.1991021 2-s2.0-85123725449 20 60 6303 6328 en International Journal of Production Research © 2022 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. |
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Engineering::Civil engineering Time-Dependent Scheduling Capacity Matching Li, Feng Guo, Xin Zhou, Li Wu, Jianjun Li, Tongfei A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
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Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passenger revenue over a longer period. Considering the collaborative urban public transport services achieve a seamless movement for both passengers and goods, and could reduce the adverse effects of the existing urban public transport systems. Therefore, a mixed-integer linear programming model introducing the concept of capacity matching is proposed to assist this collaborative urban freight service network in minimising total freight transport time at station hubs and not affecting passenger transportation in this paper. Moreover, an efficient improved optimisation algorithm based on the Artificial Bee Colony Algorithm (ABC) is designed, and the numerical examples and real cases are illustrated to demonstrate the feasibility and effectiveness of the proposed model and algorithm. The performance evaluations suggest that the coordinated operating strategy of the collaborative freight transportation system supports increasing mobility demands for freight, resulting in declining congestion levels and reducing transport emissions, while no influence in passenger transport, notably in urban areas. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Li, Feng Guo, Xin Zhou, Li Wu, Jianjun Li, Tongfei |
format |
Article |
author |
Li, Feng Guo, Xin Zhou, Li Wu, Jianjun Li, Tongfei |
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Li, Feng |
title |
A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
title_short |
A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
title_full |
A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
title_fullStr |
A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
title_full_unstemmed |
A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
title_sort |
capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation |
publishDate |
2022 |
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https://hdl.handle.net/10356/163902 |
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1753801166204960768 |