A machine learning approach to optimise the usage of recycled material in a remanufacturing environment

DOI10.1080/00207540802452157zbMath1197.90167OpenAlexW1995330930MaRDI QIDQ3163724

Purvin Shah, Abhijit Gosavi, Rakesh Nagi

Publication date: 26 October 2010

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540802452157

zbMATH Keywords

process planningprocessesprocess industryprocess economicsreconfigurable manufacturing

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Production models (90B30)

Related Items (1)

Optimal acquisition and inventory control for a remanufacturing system

Cites Work

• Optimal policy and holding cost stability regions in a periodic review inventory system with manufacturing and remanufacturing options
• Simulation-based optimization: Parametric optimization techniques and reinforcement learning
• Simple heuristics for push and pull remanufacturing policies
• Closed-Loop Supply Chain Models with Product Remanufacturing
• The Economics of Remanufacturing Under Limited Component Durability and Finite Product Life Cycles
• Optimization analysis for recycle-oriented manufacturing systems

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