A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics

Shuaian Wang; Ran Yan

doi:10.1016/j.clscn.2022.100062

A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics

Shuaian Wang
, Ran Yan

Research output: Journal article publication › Journal article › Academic research › peer-review

Original language	English
Article number	100062
Journal	Cleaner Logistics and Supply Chain
Volume	4
DOIs	https://doi.org/10.1016/j.clscn.2022.100062
Publication status	Published - Jul 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

Management of Technology and Innovation
Industrial and Manufacturing Engineering
Management, Monitoring, Policy and Law
Environmental Science (miscellaneous)

More information

10.1016/j.clscn.2022.100062

http://hdl.handle.net/10397/99013

Cite this

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title = "A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics",

author = "Shuaian Wang and Ran Yan",

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T1 - A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics

AU - Wang, Shuaian

AU - Yan, Ran

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UR - https://www.scopus.com/pages/publications/85135393429

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DO - 10.1016/j.clscn.2022.100062

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AN - SCOPUS:85135393429

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A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics

UN SDGs

ASJC Scopus subject areas

More information

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Cite this