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Congjun Rao
Researcher at Wuhan University of Technology
Publications - 16
Citations - 505
Congjun Rao is an academic researcher from Wuhan University of Technology. The author has contributed to research in topics: Procurement & Auction theory. The author has an hindex of 8, co-authored 16 publications receiving 373 citations. Previous affiliations of Congjun Rao include Huanggang Normal University & Huazhong University of Science and Technology.
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Location selection of city logistics centers under sustainability
TL;DR: A new evaluation system for the location selection of a CLC from a sustainability perspective using a fuzzy multi-attribute group decision making (FMAGDM) technique based on a linguistic 2-tuple to evaluate potential alternative CLC locations.
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Compound mechanism design of supplier selection based on multi-attribute auction and risk management of supply chain
TL;DR: A new two-stage compound mechanism for supplier selection based on multi-attribute auction and supply chain risk management may well improve the procurement efficiency of divisible goods and greatly reduce the procurement risk.
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2-stage modified random forest model for credit risk assessment of P2P network lending to “Three Rurals” borrowers
TL;DR: A 2-stage Syncretic Cost-sensitive Random Forest (SCSRF) model is proposed to classify the credit worthiness of the “Three Rurals” borrowers and validated against several established credit evaluation models.
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Decision Mechanism for Supplier Selection Under Sustainability
TL;DR: A new evaluation system for supplier selection from a sustainability perspective based on linguistic 2-tuple grey correlation degree is presented and an application example is presented to highlight the implementation, availability and feasibility of the proposed decision making mechanism.
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A hybrid multi-attribute group decision making method based on grey linguistic 2-tuple
TL;DR: A new grey hybrid multi-attribute group decision making method based on grey linguistic 2-tuple is presented to aggregate multiple decision makers' individual decision information into comprehensive decision information and to rank all alternatives and to select the winners.