Operational Resilience Under Carbon Constraints: A Socio-Technical Multi-Agentic Approach to Global Supply Chains

The crisis

• Carbon regulations are reshaping global supply chains faster than optimization models can adapt
• Energy transition creates new failure modes: carbon cost spikes, grid instability, and sourcing constraint cascades that conventional resilience models don't capture
• Humanitarian supply chains disaster response, medical logistics operate under the same carbon pressures as commercial chains, with less margin for failure
• Most supply chain optimization treats carbon as a constraint, not a dynamic variable leading to brittle configurations that fail under regulatory change
• Organizations need operational resilience metrics that account for carbon exposure, not just cost and time

About this research

Supply chain resilience under carbon constraints is fundamentally different from conventional resilience. Carbon regulations introduce new failure modes: not just disruption and cost shock, but regulatory exposure, sourcing constraint cascades, and energy transition risk. This paper introduces CASP a weighted harmonic mean metric that evaluates operational resilience by combining carbon exposure, adaptive capacity, supply continuity, and performance under carbon stress. The multi-agentic framework models supply chain behavior across energy transition scenarios, capturing the socio-technical dependencies (regulatory, behavioral, infrastructure) that static optimization models ignore. This work directly extends the CCI carbon cost framework (Energies 2026) to the supply chain optimization domain.

Research question

Can a multi-agentic approach with a composite resilience metric (CASP) capture carbon-regulatory supply chain failure modes that static optimization models miss, and enable adaptive reconfiguration under energy transition scenarios?

Methodology

CASP metric design as weighted harmonic mean across four resilience dimensions; multi-agent simulation across supply chain configuration space under carbon constraint scenarios; socio-technical dependency modeling (regulatory, infrastructure, behavioral); scenario analysis across energy transition timelines; comparison against static optimization baseline; ablation study isolating CASP component contributions.

Key findings

• Open access in MDPI Systems (2026): supply chain resilience under carbon constraints with socio-technical failure modes
• CASP (composite metric) combines carbon exposure, adaptive capacity, supply continuity, and performance under carbon stress
• Multi-agentic modeling links regulatory and infrastructure dynamics to configuration-level outcomes

References

• Kaur, R., Kundu, T., Park, K.M., & Pinsky, E. (2026) Carbon Cost of Intelligence, Energies, DOI: 10.3390/en19030642
• WEF Global Risks Report 2025 Carbon regulatory risk in global supply chains
• Park, K. "Humanitarian Logistics Innovation" (In Progress)
• Journal of Cleaner Production (2024) Carbon cost variability in logistics optimization

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