Artificial intelligence and prescriptive analytics for supply chain resilience: a systematic literature review and research agenda-Reference-Cited by-同舟云学术

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Artificial intelligence and prescriptive analytics for supply chain resilience: a systematic literature review and research agenda

Published:2024-04-23 Issue: Volume: Page:1-25
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Smyth Conn¹,Dennehy Denis²,Fosso Wamba Samuel³,Scott Murray¹,Harfouche Antoine⁴

Affiliation:

1. Business Information Systems Department, University of Galway, Galway, Ireland

2. School of Management, Swansea University, Swansea, UK

3. Department of Information, Operations and Management Sciences, TBS Business School, Toulouse, France

4. CEROS, University Paris Nanterre, Paris, France

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2024.2341415

Reference155 articles.

1. Color image segmentation with genetic algorithm in a raisin sorting system based on machine vision in variable conditions

2. Predicting solutions of large-scale optimization problems via machine learning: A case study in blood supply chain management

3. Supplier selection and performance evaluation in just-in-time production environments

4. Big data and disaster management: a systematic review and agenda for future research

5. Enhancing Information Retrieval through Statistical Natural Language Processign: A Study of Collocation Indexing

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCD industry;International Journal of Production Research;2024-08-27

2. Machine learning in smart production logistics: a review of technological capabilities;International Journal of Production Research;2024-07-22

3. Artificial Intelligence for Enhancing Resilience;SSRN Electronic Journal;2024

4. Artificial intelligence and machine learning for resilient and sustainable logistics and supply chain management;SSRN Electronic Journal;2024

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