An empirical framework using weighted feed forward neural network for supply chain resilience (SCR) strategy selection

DOI10.1007/S43069-024-00313-ZzbMATH Open1541.90074MaRDI QIDQ6559493

Ramkumar Sivasakthivel, Manikandan Rajagopal

Publication date: 21 June 2024

Published in: SN Operations Research Forum (Search for Journal in Brave)

zbMATH Keywords

supply chain management (SCM)artificial intelligence (AI)supply chain resilience (SCR)fuzzy programming and multi-level decision support (MLDS) framework

Mathematics Subject Classification ID

Transportation, logistics and supply chain management (90B06) Fuzzy and other nonstochastic uncertainty mathematical programming (90C70) Inventory, storage, reservoirs (90B05) General topics in artificial intelligence (68T01)

Cites Work

• Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19
• Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

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