Publication: Heuristic route adjustment for balanced working time in urban logistics with driver experience and time-dependent traffic information
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Issued Date
2020-10-02
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ISSN
20763417
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2-s2.0-85092695441
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Mahidol University
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SCOPUS
Bibliographic Citation
Applied Sciences (Switzerland). Vol.10, No.20 (2020), 1-18
Suggested Citation
Tipaluck Krityakierne, Wasakorn Laesanklang Heuristic route adjustment for balanced working time in urban logistics with driver experience and time-dependent traffic information. Applied Sciences (Switzerland). Vol.10, No.20 (2020), 1-18. doi:10.3390/app10207156 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/59920
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Title
Heuristic route adjustment for balanced working time in urban logistics with driver experience and time-dependent traffic information
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Abstract
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article proposes a method to reduce working time violations of a real-world courier service in the urban logistics with time-dependent traffic information. The challenge is to reduce working time violation without creating significant changes to the urban logistics plan which provides city coverage to each driver. Furthermore, courier businesses require time-dependent traffic information to have an integrated traffic routing plan. This process will require very long enquiry time as the traffic information is available online, but a good decision must be made as soon as possible. To tackle the problem, we first propose a heuristic method for route adjustment using a particular traffic time instance (single traffic time). The route solution obtained from the single traffic time is subsequently transferred to the time-dependent traffic scenario. Computational results demonstrate that the heuristic route adjustment algorithm could decrease working time violations and create a balanced working time solution. We include also in-depth analyses on the optimal working time, and the effect of using a single traffic time solution in the time-dependent traffic information environment. The obtained results illustrate the effectiveness of our approach in solving the real applications of time-dependent vehicle routing in urban logistics.