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How to use no-code artificial intelligence to predict and minimize the inventory distortions for resilient supply chains

Jauhar, Sunil Kumar; Jani, Shashank Mayurkumar; Kamble, … - In: International journal of production research 62 (2024) 15, pp. 5510-5534

Persistent link: https://www.econbiz.de/10015053702

Data-driven newsvendor problems regularized by a profit risk constraint

Lin, Shaochong; Chen, Youhua; Li, Yanzhi; Shen, Zuo-Jun - In: Production and operations management : the flagship … 31 (2022) 4, pp. 1630-1644

Persistent link: https://www.econbiz.de/10013273810

Managing inventory in global supply chains facing port-of-entry disruption risks

Lewis, Brian M.; Erera, Alan L.; Nowak, Maciek A.; … - In: Transportation science : a journal of the Institute for … 47 (2013) 2, pp. 162-180

Persistent link: https://www.econbiz.de/10009751573

System dynamics modelling for the chemical supply chain : a case study

Khan, Azeen Shahna; Hebbar, Sunith - In: International journal of services and operations … 38 (2021) 3, pp. 441-465

Persistent link: https://www.econbiz.de/10012522429

Increasing supply chain robustness through process flexibility and inventory

Simchi-Levi, David; Wang, He; Wei, Yehua - In: Production and operations management : the flagship … 27 (2018) 8, pp. 1476-1491

Persistent link: https://www.econbiz.de/10011969962

Supply Chain Management Strategies and Methodologies : Experiences from Latin America

García-Alcaraz, Jorge Luis (ed.); … - 2023

Part 1. Supply Chain Procurement -- Chapter 1. Supply Chain Strategies and Methodologies - A Bibliometric Review -- Chapter 2. Using Meta-Learning in Automatic Demand Forecast with Large Number of Products -- Chapter 3. Economic development and high-value supply chains -- Chapter 4. Artificial...

Persistent link: https://www.econbiz.de/10014286479

Integration of machine learning in the supply chain for decision making : a systematic literature review

Polo-Triana, Sonia; Gutierrez, Juan Camilo; … - In: Journal of industrial engineering and management : JIEM 17 (2024) 2, pp. 344-372

Purpose: This study presents a systematic literature review that provides a broad and holistic view of how machine learning can be used and integrated to enhance decision-making in various areas of the supply chain, highlighting its combination with other techniques and models....

Persistent link: https://www.econbiz.de/10015375505

A smart DDMRP model using machine learning techniques

Aguilar, Jose; Dos Santos Guillén, Ricardo José; … - In: International journal of value chain management : IJVCM 14 (2023) 2, pp. 107-142

Persistent link: https://www.econbiz.de/10014310016

Digital inventory powered by drones and robots

Yearling, Matt - In: Journal of supply chain management, logistics and … 1 (2018) 1, pp. 41-47

Persistent link: https://www.econbiz.de/10012127897

A hybrid LSTM method for forecasting demands of medical items in humanitarian operations

Hasni, Marwa; Babai, M. Zied; Rostami-Tabar, Bahman - In: International journal of production research 62 (2024) 17, pp. 6046-6063

Persistent link: https://www.econbiz.de/10015053762