The field of supply chain, manufacturing, warehouse, and building evacuation optimization has undergone transformative changes with the integration of artificial intelligence (AI) and simulation technologies. These advancements have revolutionized logistical operations and emergency management by significantly enhancing efficiency, safety, and responsiveness. A current issue faced within this domain pertains to the optimal allocation of resources, reduction of operational costs, and assurance of human safety, especially during evacuation scenarios. While recent studies underscore AI's potential in automating tasks, refining layout designs, and optimizing inventory placements, challenges remain in understanding the comprehensive synergy between AI-driven solutions and real-world applications. The scalability of AI models and their adaptability to dynamically shifting environments are ongoing focal points of debate, necessitating further exploration into innovative solutions that can elevate AI and simulation capabilities within the field.

This Research Topic aims to delve deeply into the optimization of supply chains, manufacturing processes, warehouse management, and building evacuations through the lens of AI and simulation. It seeks to identify critical areas where AI can make substantial impacts on efficiency and safety while investigating AI-driven optimization models' hypotheses and real-world integration. By addressing these focal points, the research aims to furnish valuable insights beneficial for academics, industry stakeholders, and practitioners.

To gather further insights within the domain of optimizing logistical operations and emergency management using AI and simulation, we welcome articles addressing, but not limited to, the following themes:

AI-driven resource allocation and cost reduction strategies in supply chains

Simulation techniques for enhancing warehouse layout and inventory management

Development of AI models for efficient building evacuation planning

Case studies on AI implementation in manufacturing processes

Challenges and solutions in scaling AI applications for dynamic environments

Comparative analyses of traditional vs. AI-based optimization methods

We encourage submissions that explore diverse perspectives and methodologies, aiming to broaden current understanding and catalyze further research in this vital area of study.

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Harnessing AI and simulation for enhanced supply chain and emergency management optimization