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Cited by 9Vehicle emissions and performanceVehicle Routing Optimization MethodsRailways and European Transport Policy

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The green fleet optimization model for a low-carbon economy: A prescriptive analytics

Wu, Pei-Ju, Yang, Chun-Kai·2017·2017 International Conference on Applied System Innovation (ICASI)
DOI 10.1109/icasi.2017.7988358
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Abstract

The rising awareness of environment protection has increased the need for a transformation of current transport systems to help achieve a low-carbon economy. Hence, this paper aims to develop an optimization model to seek a feasible combination of environmental alternatives that minimizes the emissions of transport fleets. The analytical results of a prescriptive analytics in Taichung city demonstrate that green fleets with eco-driving training can effectively achieve a low-carbon economy. The implications of these findings are also discussed.

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Crossref · 10.1109/icasi.2017.7988358

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1 of 1 references verified0 citation errors · 0 not checkable

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  • Linear integer programming has been used in prescriptive analytics for finding a feasible combination of environmental alternatives that minimizes emissions of transport fleets.

    “Specifically, the linear integer programming model has been used in the context of prescriptive analytics for finding a feasible combination of environmental alternatives that minimizes the emissions of transport fleets (Wu & Yang, 2017)”

    From Prescriptive analytics: Literature review and research challenges (2020) · cites this paper as Wu & Yang, 2017

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 20

  1. 10.1016/j.rser.2016.05.019 · DOI · Paper page
  2. 10.1016/j.energy.2015.12.041 · DOI
  3. 10.1016/j.trpro.2014.10.092 · DOI
  4. 10.1016/j.sbspro.2012.09.722 · DOI
  5. 10.1016/j.sbspro.2012.09.740 · DOI
  6. 10.1016/j.sbspro.2013.08.124 · DOI
  7. 10.1016/j.sbspro.2014.01.105 · DOI
  8. 10.1016/j.tra.2017.01.019 · DOI
  9. 10.1016/j.egypro.2015.07.348 · DOI
  10. fu, 2016, Laboratory investigation on the properties of asphalt mixtures modified with double-adding admixtures and sensitivity analytics, J Traffic Transp Eng Engl Ed, 3, 412
  11. 10.1016/j.sbspro.2016.06.097 · DOI
  12. 10.1016/j.egypro.2016.10.207 · DOI
  13. 10.1016/j.trpro.2016.05.049 · DOI
  14. 10.1016/j.rser.2017.01.181 · DOI
  15. 10.1016/j.apenergy.2015.01.058 · DOI
  16. 10.1016/j.sbspro.2016.05.456 · DOI
  17. 10.1016/j.proeng.2016.01.314 · DOI
  18. 10.1016/j.proeng.2015.08.455 · DOI
  19. 10.1016/j.ress.2017.02.002 · DOI
  20. 10.1016/j.egypro.2016.12.157 · DOI

Cited by

Sorted by citations

  • Prescriptive analytics: Literature review and research challenges

    Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.04.003 · Cited by 501

    “…context of prescriptive analytics for finding a feasible combination of environmental alternatives that minimizes the emissions of transport fleets (Wu & Yang, 2017) and for planning sales force assignments on the basis of predictions about the sales impact (von Bischhoffshausen, Paatsch, Reuter,…”

Metadata

Authors
Wu, P.-J., & Yang, C.-K.
Affiliations
Feng Chia University (TW)
ORCID
Wu, Pei-Ju
Venue
2017 International Conference on Applied System Innovation (ICASI)
Publisher
IEEE
Published
2017-05
Volume
3
Pages
107-110
DOI
10.1109/icasi.2017.7988358
OpenAlex
W2737371601
Cited by
9
References
1
Citations by year
2024: 3 · 2022: 1 · 2021: 1 · 2019: 4
FWCI
1.22
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Applied System Innovation (publishedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Vehicle Routing Optimization Methods
  • Social Sciences › Transportation › Railways and European Transport Policy
Keywords
low-carbon economy, transport emissions, prescriptive analytics, optimization model, environmental alternatives, Taichung

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