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Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants.

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Title: Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants.
Authors: Wibowo, Budhi1 (AUTHOR) budhi.sholehwibowo@ugm.ac.id, Fransoo, Jan2 (AUTHOR)
Source: International Journal of Production Research. Jul2021, Vol. 59 Issue 13, p3935-3950. 16p. 3 Diagrams, 4 Charts, 7 Graphs.
Subjects: Phytochemicals, Chemical plants, Traffic congestion, Trucking, Trucks
Abstract: Numerous studies have proposed the use of a Truck Appointment System (TAS) to alleviate traffic congestion at logistics sites. Unfortunately, the implementation of such a system was often optimised based on the interest of a single stakeholder. Meanwhile, long truck queues have been observed in many chemical plants. This study aims to evaluate the TAS performances to mitigate traffic congestion in chemical plants from the multi-stakeholder perspective. We proposed a joint-optimization model to accommodate various interests on the site. An improved fluid-flow approximation was developed to estimate the time-dependent performance of the system. The results suggest that the benefit of TAS is mostly enjoyed by the site manager through the reduction of site overtime, while the benefits for trucking companies are found to be marginal. Through numerical experiments, we show that the proposed joint-optimization model is effective in redistributing the benefits of TAS across the stakeholders, while keeping the total logistics costs to a minimum. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants.
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  Data: <searchLink fieldCode="AR" term="%22Wibowo%2C+Budhi%22">Wibowo, Budhi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> budhi.sholehwibowo@ugm.ac.id</i><br /><searchLink fieldCode="AR" term="%22Fransoo%2C+Jan%22">Fransoo, Jan</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jul2021, Vol. 59 Issue 13, p3935-3950. 16p. 3 Diagrams, 4 Charts, 7 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Phytochemicals%22">Phytochemicals</searchLink><br /><searchLink fieldCode="DE" term="%22Chemical+plants%22">Chemical plants</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+congestion%22">Traffic congestion</searchLink><br /><searchLink fieldCode="DE" term="%22Trucking%22">Trucking</searchLink><br /><searchLink fieldCode="DE" term="%22Trucks%22">Trucks</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Numerous studies have proposed the use of a Truck Appointment System (TAS) to alleviate traffic congestion at logistics sites. Unfortunately, the implementation of such a system was often optimised based on the interest of a single stakeholder. Meanwhile, long truck queues have been observed in many chemical plants. This study aims to evaluate the TAS performances to mitigate traffic congestion in chemical plants from the multi-stakeholder perspective. We proposed a joint-optimization model to accommodate various interests on the site. An improved fluid-flow approximation was developed to estimate the time-dependent performance of the system. The results suggest that the benefit of TAS is mostly enjoyed by the site manager through the reduction of site overtime, while the benefits for trucking companies are found to be marginal. Through numerical experiments, we show that the proposed joint-optimization model is effective in redistributing the benefits of TAS across the stakeholders, while keeping the total logistics costs to a minimum. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1080/00207543.2020.1756505
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 16
        StartPage: 3935
    Subjects:
      – SubjectFull: Phytochemicals
        Type: general
      – SubjectFull: Chemical plants
        Type: general
      – SubjectFull: Traffic congestion
        Type: general
      – SubjectFull: Trucking
        Type: general
      – SubjectFull: Trucks
        Type: general
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      – TitleFull: Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants.
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              Text: Jul2021
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              Y: 2021
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