Simulation and Digital Twins in Humanitarian Supply Chain Management

Dear Colleagues,

The increasing frequency and intensity of disasters, coupled with the complexity of global disruptions such as pandemics and conflicts, have underscored the urgent need for intelligent, adaptive, and sustainable humanitarian logistics systems. This Special Issue seeks to advance the state of knowledge in simulation-driven and digital twin-enabled humanitarian supply chain management (HLSCM). It will serve as a platform for exploring how emerging technologies, ranging from AI-enabled modeling and multi-objective optimization to digital twins and data analytics, can strengthen resilience, enhance coordination, and improve resource efficiency across all phases of disaster preparedness, response, and recovery. We invite original research, reviews, and case studies that bridge the gap between theory and practice, focusing on computational, systemic, and data-driven approaches that transform real-time information into actionable intelligence to support life-saving decisions in humanitarian contexts.

Topics of Interest

This Special Issue welcomes papers that address themes including, but not limited to, the following:

1. Simulation-Based and Data-Driven Modeling:

• Agent-based, discrete-event, and system dynamics models for humanitarian logistics;
• Monte Carlo and scenario-based simulation for uncertainty analysis;
• Digital twins for real-time decision support and crisis visualization;
• Multi-fidelity and hybrid simulation frameworks for complex disaster systems;
• AI- and ML-enhanced simulation for forecasting and adaptive logistics planning.

2. Digital Twins in Humanitarian Operations:

• Conceptualization and architecture of digital twins for humanitarian and emergency networks;
• Human–AI decision-making and cognitive digital twins in logistics and crisis management;
• Integration of IoT, blockchain, and cloud-based infrastructures in digital humanitarian supply chains;
• Model calibration, synchronization, and data validation in digital twin ecosystems;
• Digital twins as enablers of operational resilience, visibility, and sustainability.

3. Optimization and Decision Support:

• Multi-objective and stochastic optimization in disaster response and recovery logistics;
• Facility location, resource allocation, and vehicle routing under uncertainty;
• Scheduling and coordination in multi-agency humanitarian operations;
• Risk and vulnerability modeling integrated with simulation and digital twins;
• Trade-off analysis among cost, time, equity, and environmental performance.

4. Governance, Ethics, and Sustainability:

• Sustainability and circularity principles in humanitarian supply chains;
• Ethical and governance frameworks for AI and digital twin applications;
• Public–private partnerships and policy modeling for resilient HLSCM;
• Socio-technical system design for equitable and inclusive humanitarian response;
• Evaluation metrics for sustainable and resilient digital supply chains.

Relevance and Contribution

This Special Issue aims to

• Bridge simulation modeling and digital twin technologies within the context of humanitarian operations;
• Promote cross-disciplinary research combining engineering systems, data science, and operations research;
• Offer novel insights into resilience engineering, real-time situational awareness, and adaptive logistics;
• Contribute to the global agenda of sustainable disaster management and climate adaptation.

Dr. Seyed Mojtaba Sajadi
Prof. Dr. Said M. Easa
Dr. Armin Mahmoodi
Guest Editors

Manuscript Submission Information

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