A novel multi-phase hierarchical forecasting approach with machine learning in supply chain management-Reference-Cited by-同舟云学术

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A novel multi-phase hierarchical forecasting approach with machine learning in supply chain management

Published:2023-09 Issue: Volume:3 Page:100032
ISSN:2949-8635
Container-title:Supply Chain Analytics
language:en
Short-container-title:Supply Chain Analytics

Author:

Taghiyeh Sajjad^ORCID,Lengacher David C.,Sadeghi Amir Hossein^ORCID,Sahebi-Fakhrabad Amirreza^ORCID,Handfield Robert B.^ORCID

Publisher

Elsevier BV

Reference91 articles.

1. A mixed-integer linear formulation for a dynamic modified stochastic p-median problem in a competitive supply chain network design;Sadeghi;Logistics,2023

2. Optimal combination forecasts for hierarchical time series;Hyndman;Comput. Stat. Data Anal.,2011

3. Forecasting with temporal hierarchies;Athanasopoulos;Eur. J. Oper. Res.,2017

4. Constrained forecasting: some implementation guidelines;Fliedner;Decis. Sci.,1992

5. Designing an integrated decision support system to link supply chain processes performance with time to market;Khan;Int. J. Manag. Sci. Eng. Manag.,2022

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1. Improving smart deals system to secure human-centric consumer applications: Internet of things and Markov logic network approaches;Electronic Commerce Research;2023-12-12

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