A systematic review of machine learning in logistics and supply chain management: current trends and future directions
M Akbari, TNA Do - Benchmarking: An International Journal, 2021 - emerald.com
Purpose This paper presents a review of the existing state-of-the-art literature on machine
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
A systematic review of machine learning in logistics and supply chain management: current trends and future directions
M Akbari, T Do - Benchmarking: An International …, 2021 - researchrepository.rmit.edu.au
Purpose: This paper presents a review of the existing state-of-the-art literature on machine
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
A systematic review of machine learning in logistics and supply chain management: current trends and future directions
M Akbari, TNA Do - Benchmarking, 2021 - researchonline.jcu.edu.au
Purpose–This paper presents a review of the existing state-of-the-art literature on machine
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
A systematic review of machine learning in logistics and supply chain management: current trends and future directions
M Akbari, TNA Do - Benchmarking: An International Journal, 2021 - ingentaconnect.com
PurposeThis paper presents a review of the existing state-of-the-art literature on machine
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …
learning (ML) in logistics and supply chain management (LSCM) by analyzing the current …