Research graph
References from Agent-based, immune system-inspired supply chain automation for disruption management. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
2022 · External reference
Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments
10.1016/j.omega.2023.102841 · 2023 · External reference
Enhancing supply chain visibility with knowledge graphs and large language models
10.1080/00207543.2025.2575841 · 2026 · External reference
A hybrid deep learning-based approach for disruption detection and recovery planning in a prototype cognitive digital supply chain twin
2026 · External reference
Heterogeneous risk management using a multi-agent framework for supply chain disruption response
10.1109/lra.2024.3388838 · 2024 · External reference
An empirically derived agenda of critical research issues for managing supply-chain disruptions
10.1080/00207540500151549 · 2005 · External reference
Human immune system variation
10.1038/nri.2016.125 · 2017 · External reference
Resilience and immunity
10.1016/j.bbi.2018.08.010 · 2018 · External reference
Measuring and avoiding the bullwhip effect: A control theoretic approach
10.1016/s0377-2217(02)00369-7 · 2003 · External reference
A Network-of-networks adaptation for cross-industry manufacturing repurposing
10.1080/24725854.2023.2253881 · 2024 · External reference
Dynamic digital capabilities and supply chain resilience: The role of government effectiveness
10.1016/j.ijpe.2023.108790 · 2023 · External reference
Benchmarking operations and supply chain management practices using Generative AI: Towards a theoretical framework
10.1016/j.tre.2024.103689 · 2024 · External reference
10.1007/bfb0013570
10.1007/bfb0013570 · External reference
Review of quantitative methods for supply chain resilience analysis
10.1016/j.tre.2019.03.001 · 2019 · External reference
DIMA – a research methodology for comprehensive multi-disciplinary modelling of production and logistics networks
10.1080/00207540701557205 · 2009 · External reference
Supply chain resilience: Conceptual and formal models drawing from immune system analogy
10.1016/j.omega.2024.103081 · 2024 · External reference
Unresolved reference
2025 · External reference
Conceptual and formal models for design, adaptation, and control of digital twins in supply chain ecosystems
10.1016/j.omega.2025.103356 · 2025 · External reference
When is the supply chain resilient? Customer and operational perspectives
10.1080/00207543.2025.2454331 · 2025 · External reference
Unresolved reference
2026 · External reference
Agentic digital twins: bridging model-based and ai-driven decision-making support for a new era of supply chain and operations management
10.1080/00207543.2026.2630277 · 2026 · External reference
Analytical and agent-based extensions of supply chain viability modeling in intertwined supply networks
10.1007/s10479-026-07266-y · 2026 · External reference
Toward Industry 6.0: The Ecosystem Age, superintelligence, viability, and OR-AI symbiosis
10.1016/j.cor.2026.107563 · 2026 · External reference
Themes and methods in supply chain viability research
10.1080/00207543.2026.2707318 · 2026 · External reference
Supply chain viability: Foundations, perspectives, and future research agenda
10.1080/24725854.2026.2703086 · 2026 · External reference
Supply chain digital twin design and implementation at scale: The case study at the Ford Motor Company and generalizations
10.1016/j.omega.2025.103447 · 2026 · External reference
Coordination of production and ordering policies under capacity disruption and product write-off risk: An analytical study with real-data based simulations of a fast moving consumer goods company
10.1007/s10479-017-2643-8 · 2020 · External reference
Literature review on disruption recovery in the supply chain
10.1080/00207543.2017.1330572 · 2017 · External reference
Unresolved reference
2025 · External reference
Generative artificial intelligence in supply chain and operations management: A capability-based framework for analysis and implementation
10.1080/00207543.2024.2309309 · 2024 · External reference
From natural language to simulations: Applying AI to automate simulation modelling of logistics systems
10.1080/00207543.2023.2276811 · 2024 · External reference
Supply chain mapping through retrieval-augmented generation: Applications to the electronics industry
10.1080/01605682.2025.2608868 · 2026 · External reference
Agentic LLMs in the supply chain: Towards autonomous multi-agent consensus-seeking
10.1080/00207543.2025.2604311 · 2025 · External reference
Coordination techniques for distributed artificial intelligence
1996 · External reference
A comprehensive survey on multi-agent cooperative decision-making: Scenarios, approaches, challenges and perspectives
2025 · External reference
Towards trustworthy AI for link prediction in supply chain knowledge graph: A neurosymbolic reasoning approach
10.1080/00207543.2024.2399713 · 2025 · External reference
Cooperative product agents to improve manufacturing system flexibility: A model-based decision framework
10.1109/tase.2022.3156384 · 2023 · External reference
A large language model-enabled control architecture for dynamic resource capability exploration in multi-agent manufacturing systems
2025 · External reference
Robust actions for improving supply chain resilience and viability
2023 · External reference
State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains
10.1080/00207543.2021.1877842 · 2022 · External reference
How generative AI improves supply chain management
2025 · External reference
Time-To-Adapt (TTA)
10.1016/j.ijpe.2024.109432 · 2024 · External reference
Supply network topology and robustness against disruptions – an investigation using multi-agent model
10.1080/00207543.2010.518744 · 2010 · External reference
Rebooting simulation
10.1080/24725854.2023.2261028 · 2024 · External reference
Understanding systemic disruption from the Covid-19-induced semiconductor shortage for the auto industry
10.1016/j.omega.2022.102720 · 2022 · External reference
BDI agents: From theory to practice
1995 · External reference
Adapting supply chain operations in anticipation of and during the COVID-19 pandemic
10.1016/j.omega.2022.102635 · 2022 · External reference
Disruption mitigation and recovery in supply chains using portfolio approach
10.1016/j.omega.2018.05.006 · 2019 · External reference
A stochastic optimization approach to maintain supply chain viability under the ripple effect
10.1080/00207543.2023.2172964 · 2023 · External reference
Agent-based distributed manufacturing process planning and scheduling: A state-of-the-art survey
10.1109/tsmcc.2006.874022 · 2006 · External reference
Identifying risks and mitigating disruptions in the automotive supply chain
10.1287/inte.2015.0804 · 2015 · External reference
Modeling supply chain dynamics: A multiagent approach
10.1111/j.1540-5915.1998.tb01356.x · 1998 · External reference
The digital twin synchronization problem: Framework, formulations, and analysis
10.1080/24725854.2023.2253869 · 2023 · External reference
IoT-driven dynamic replenishment of fresh produce in the presence of seasonal variations: A deep reinforcement learning approach using reward shaping
10.1016/j.omega.2025.103299 · 2025 · External reference
Unresolved reference
2009 · External reference
Will bots take over the supply chain? Revisiting agent-based supply chain automation
10.1016/j.ijpe.2021.108279 · 2021 · External reference
On implementing autonomous supply chains: A multi-agent system approach
10.1016/j.compind.2024.104120 · 2024 · External reference
Modelling supply chain adaptation for disruptions: An empirically grounded complex adaptive systems approach
10.1002/joom.1009 · 2019 · External reference
Modelling supply chain adaptation for disruptions: An empirically grounded complex adaptive systems approach
10.1002/joom.1009 · ExternalCitation · doi-reference
10.1007/bfb0013570
10.1007/bfb0013570 · ExternalCitation · doi-reference
Coordination of production and ordering policies under capacity disruption and product write-off risk: An analytical study with real-data based simulations of a fast moving consumer goods company
10.1007/s10479-017-2643-8 · ExternalCitation · doi-reference
Analytical and agent-based extensions of supply chain viability modeling in intertwined supply networks
10.1007/s10479-026-07266-y · ExternalCitation · doi-reference
Resilience and immunity
10.1016/j.bbi.2018.08.010 · ExternalCitation · doi-reference
On implementing autonomous supply chains: A multi-agent system approach
10.1016/j.compind.2024.104120 · ExternalCitation · doi-reference
Toward Industry 6.0: The Ecosystem Age, superintelligence, viability, and OR-AI symbiosis
10.1016/j.cor.2026.107563 · ExternalCitation · doi-reference
Will bots take over the supply chain? Revisiting agent-based supply chain automation
10.1016/j.ijpe.2021.108279 · ExternalCitation · doi-reference
Dynamic digital capabilities and supply chain resilience: The role of government effectiveness
10.1016/j.ijpe.2023.108790 · ExternalCitation · doi-reference
Time-To-Adapt (TTA)
10.1016/j.ijpe.2024.109432 · ExternalCitation · doi-reference
Disruption mitigation and recovery in supply chains using portfolio approach
10.1016/j.omega.2018.05.006 · ExternalCitation · doi-reference
Adapting supply chain operations in anticipation of and during the COVID-19 pandemic
10.1016/j.omega.2022.102635 · ExternalCitation · doi-reference
Understanding systemic disruption from the Covid-19-induced semiconductor shortage for the auto industry
10.1016/j.omega.2022.102720 · ExternalCitation · doi-reference
Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments
10.1016/j.omega.2023.102841 · ExternalCitation · doi-reference
Supply chain resilience: Conceptual and formal models drawing from immune system analogy
10.1016/j.omega.2024.103081 · ExternalCitation · doi-reference
IoT-driven dynamic replenishment of fresh produce in the presence of seasonal variations: A deep reinforcement learning approach using reward shaping
10.1016/j.omega.2025.103299 · ExternalCitation · doi-reference
Conceptual and formal models for design, adaptation, and control of digital twins in supply chain ecosystems
10.1016/j.omega.2025.103356 · ExternalCitation · doi-reference
Supply chain digital twin design and implementation at scale: The case study at the Ford Motor Company and generalizations
10.1016/j.omega.2025.103447 · ExternalCitation · doi-reference
Review of quantitative methods for supply chain resilience analysis
10.1016/j.tre.2019.03.001 · ExternalCitation · doi-reference
Benchmarking operations and supply chain management practices using Generative AI: Towards a theoretical framework
10.1016/j.tre.2024.103689 · ExternalCitation · doi-reference
Measuring and avoiding the bullwhip effect: A control theoretic approach
10.1016/s0377-2217(02)00369-7 · ExternalCitation · doi-reference
Human immune system variation
10.1038/nri.2016.125 · ExternalCitation · doi-reference
An empirically derived agenda of critical research issues for managing supply-chain disruptions
10.1080/00207540500151549 · ExternalCitation · doi-reference
DIMA – a research methodology for comprehensive multi-disciplinary modelling of production and logistics networks
10.1080/00207540701557205 · ExternalCitation · doi-reference
Supply network topology and robustness against disruptions – an investigation using multi-agent model
10.1080/00207543.2010.518744 · ExternalCitation · doi-reference
Literature review on disruption recovery in the supply chain
10.1080/00207543.2017.1330572 · ExternalCitation · doi-reference
State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains
10.1080/00207543.2021.1877842 · ExternalCitation · doi-reference
A stochastic optimization approach to maintain supply chain viability under the ripple effect
10.1080/00207543.2023.2172964 · ExternalCitation · doi-reference
From natural language to simulations: Applying AI to automate simulation modelling of logistics systems
10.1080/00207543.2023.2276811 · ExternalCitation · doi-reference
Generative artificial intelligence in supply chain and operations management: A capability-based framework for analysis and implementation
10.1080/00207543.2024.2309309 · ExternalCitation · doi-reference
Towards trustworthy AI for link prediction in supply chain knowledge graph: A neurosymbolic reasoning approach
10.1080/00207543.2024.2399713 · ExternalCitation · doi-reference
When is the supply chain resilient? Customer and operational perspectives
10.1080/00207543.2025.2454331 · ExternalCitation · doi-reference
Enhancing supply chain visibility with knowledge graphs and large language models
10.1080/00207543.2025.2575841 · ExternalCitation · doi-reference
Agentic LLMs in the supply chain: Towards autonomous multi-agent consensus-seeking
10.1080/00207543.2025.2604311 · ExternalCitation · doi-reference
Agentic digital twins: bridging model-based and ai-driven decision-making support for a new era of supply chain and operations management
10.1080/00207543.2026.2630277 · ExternalCitation · doi-reference
Themes and methods in supply chain viability research
10.1080/00207543.2026.2707318 · ExternalCitation · doi-reference
Supply chain mapping through retrieval-augmented generation: Applications to the electronics industry
10.1080/01605682.2025.2608868 · ExternalCitation · doi-reference
The digital twin synchronization problem: Framework, formulations, and analysis
10.1080/24725854.2023.2253869 · ExternalCitation · doi-reference
A Network-of-networks adaptation for cross-industry manufacturing repurposing
10.1080/24725854.2023.2253881 · ExternalCitation · doi-reference
Rebooting simulation
10.1080/24725854.2023.2261028 · ExternalCitation · doi-reference
Supply chain viability: Foundations, perspectives, and future research agenda
10.1080/24725854.2026.2703086 · ExternalCitation · doi-reference
Heterogeneous risk management using a multi-agent framework for supply chain disruption response
10.1109/lra.2024.3388838 · ExternalCitation · doi-reference
Cooperative product agents to improve manufacturing system flexibility: A model-based decision framework
10.1109/tase.2022.3156384 · ExternalCitation · doi-reference
Agent-based distributed manufacturing process planning and scheduling: A state-of-the-art survey
10.1109/tsmcc.2006.874022 · ExternalCitation · doi-reference
Modeling supply chain dynamics: A multiagent approach
10.1111/j.1540-5915.1998.tb01356.x · ExternalCitation · doi-reference
Identifying risks and mitigating disruptions in the automotive supply chain
10.1287/inte.2015.0804 · ExternalCitation · doi-reference
