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Introduction
This SI aims to support logistics resilience by leveraging novel ideas for supply chain operations. Bridging isolated maintenance and holistic operational needs using data-driven analytics, model-based simulations, and improved cognitive and knowledge graphs. The mission is to move from a reactive mode to a closed loop, achieving resource optimization and reducing downtime with a supply chain continuously operating in an uncertain environment. This method creates a self-healing resilient logistics system that can be wire-framed to recover, thereby increasing the efficiency of logistics systems as well. Based on predictive models and adaptive control, the problem changes the perspective of optimizing logistics resilience and going beyond conventional methods for recovering end-to-end continuity. The SI addresses a critical gap concerning resilient supply chain strategies, bridging theoretical perspectives and methods underpinning best practices in recent years for more sustainable, effective logistics management.
The SI launches a novel supply chain resilience framework using AI-driven cognitive architectures , which provide framework and models that incorporate AI with human and cognitive process of thinking, learning and creation. . It powerfully binds the dislocated phases (prevention, response, and recovery) of traditional lifecycles into an integrated system, bringing innovations such as predictive maintenance or real-time scheduling as indispensable parts of a complete architecture for resilience operations. Modular design and the co-creation of shared expertise enable autonomous innovation advancements to feed and be informed by adjacent fields of applications, creating a living ecosystem. It also introduces a unique taxonomy that shows how AI techniques like deep reinforcement learning, large language models, or knowledge graphs can support resilience objectives. Rather than being full-phase integrated as in prior work, [this issue] is pioneering in supporting targeted innovation at each stage that works together towards that ultimate end goal of resilience. They keep system phenomena and multiscale development of the supply chain, with academic depth in specialty with interdisciplinary interactions of the entire design for systems.
This SI tackles key societal challenges by enhancing supply chain resilience and efficiency. By improving resource management and reducing waste, it supports the UN Sustainable Development Goals (SDGs) such as SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production). These advancements contribute to sustainable practices and innovation, helping communities access essential goods and services more reliably. Additionally, fostering resilience aids in achieving SDG 2 (Zero Hunger) and SDG 11 (Sustainable Cities and Communities), ensuring that resources are distributed equitably and sustainably. This approach promotes environmental stewardship and supports global efforts towards a more sustainable future.
List of Topic Areas
- Emerging AI-Driven Innovations and Next-Generation Data-Intelligent Architectures for Real-Time Decision-Making in Supply Chain Ecosystems
- AI-Driven Synergies and Digital Architectures for Dynamic Supply Chain Resilience
- Seamless Multimodal Interaction and Natural Interfaces for Enhanced Human-AI Collaboration in Supply Chains
- Agent-Based Systems and Embodied Intelligence for Decentralized Supply Chain Optimization
- Agentic AI with Embodied Intelligence for Proactive and Autonomous Decision-Making in Supply Chain
- Ambient and Invisible Intelligence in Supply Chain Architectures
- LLM-Powered Edge AI and IoT Integration for Real-Time Supply Chain Analytics
- Failure Knowledge Management in AI-Driven Supply Chains
- Hybrid Human-AI Collaboration for Strategic Supply Chain Decision-Making
- Prognostics and Health Management in Production/Supply Chain
- Predictive, Re-active, and Proactive maintenance in AI-Driven Supply Chain Management
Submission Information
Submissions are made using ScholarOne Manuscripts. Registration and access are available here:
Author guidelines must be strictly followed. Please see:
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key Dates
Opening date for manuscript submissions: 24 November 2025
Closing date for manuscript submissions: 15 September 2026
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