Reinforcement learning based optimal decision making towards product lifecycle sustainability-Reference-Cited by-同舟云学术

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Reinforcement learning based optimal decision making towards product lifecycle sustainability

Published:2022-01-31 Issue:10-11 Volume:35 Page:1269-1296
ISSN:0951-192X
Container-title:International Journal of Computer Integrated Manufacturing
language:en
Short-container-title:International Journal of Computer Integrated Manufacturing

Author:

Liu Yang¹²^ORCID,Yang Miying³^ORCID,Guo Zhengang⁴^ORCID

Affiliation:

1. Department of Management and Engineering, Linköping University, Linköping, Sweden

2. Department of Production, University of Vaasa, Vaasa, Finland

3. Group of Sustainability, School of Management, Cranfield University, Cranfield, UK

4. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

Funder

Vinnova

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2022.2025623

Reference68 articles.

1. A multiple lifecycle-based approach to sustainable product configuration design

2. Knowledge-based assessment of manufacturing process performance: integration of product lifecycle management and value-chain simulation approaches

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1. AGI-Enabled Robotics for Healthcare Industry;Advanced Technologies and Societal Change;2024-08-31

2. Integrating MBD with BOM for consistent data transformation during lifecycle synergetic decision-making of complex products;Advanced Engineering Informatics;2024-08

3. Product Concept Development and Evaluation Using Multiagent Reinforcement Learning;IEEE Transactions on Engineering Management;2024

4. Analysis of artificial intelligence-based technologies and approaches on sustainable entrepreneurship;Technological Forecasting and Social Change;2023-01

5. Exploring self-organization and self-adaption for smart manufacturing complex networks;Frontiers of Engineering Management;2022-11-17

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