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Transportation planning for sustainable supply chain network using big data technology · Study

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ArticleTransportation planning for sustainable supply chain network using big data technology

Jin Peng2022

Article2022

Transportation planning for sustainable supply chain network using big data technology

Jin Peng · Lin Chen · Bo Zhang

56 citations·0/0 files stored·Information Sciences

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Sustainable Supply Chain Management Supply Chain and Inventory Management Optimization and Mathematical Programming

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References

2012Green supply chain network design to reduce carbon emissions 2020Supply chain management in the era of circular economy: the moderating effect of big data 2020Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design 2017Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax 2021Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles 2020A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data 2019An integrated two-layer network model for designing a resilient green-closed loop supply chain of perishable products under disruption 2021A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

Cited by

2023Location–allocation problem for green efficient two-stage vehicle-based logistics system: A type-2 neutrosophic multi-objective modeling approach 2024Enhancing organizational sustainable innovation performance through organizational readiness for big data analytics 2024Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective

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Details

Year2022

Typearticle

Published2022-07-22

VenueInformation Sciences

ISSN-L0020-0255

Languageen

Citations56

Files0 public / 0

ShelfSustainable Supply Chain Management

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doi10.1016/j.ins.2022.07.112

openalex_workW4286564980

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