Next-Generation Decision Making International Lab (NEDMIL)

The Next-Generation Decision Making International Lab (NEDMIL) is a premier global research consortium dedicated to advancing both fundamental and applied research in decision sciences and AI-powered analytics.
Our laboratory functions as an internationally collaborative platform where leading scholars and practitioners from multiple disciplines and continents converge to investigate the theoretical foundations and emerging paradigms of next-generation decision making for sustainable and intelligent systems.

Through rigorous methodologies spanning prescriptive analytics, simulation–optimization, advanced operations research, and applied artificial intelligence, NEDMIL explores the complex dynamics of decision processes across diverse application domains.
These include logistics and supply chain management, transportation and multimodal mobility, industrial and marine engineering, sustainable infrastructure, corrosion monitoring and predictive maintenance, business strategy, and public policy design.

Our research framework integrates cutting-edge computational technologies—including AI and machine learning, digital twins, stochastic and robust optimization, reinforcement learning, distributed sensing networks, and quantum-inspired decision models—to conduct comprehensive investigations into complex adaptive systems and real-world decision environments.

NEDMIL-ThemeMap

NEDMIL’s international research initiatives encompass:

  • AI-powered decision support systems for logistics, supply chains, and sustainable production planning

  • Simulation–optimization frameworks for resilient, adaptive, and environmentally responsible systems

  • Prescriptive analytics for strategic, tactical, and operational decision-making under uncertainty

  • Applied AI in smart infrastructure, marine systems, corrosion intelligence, health systems, and sustainable resource management

  • Cross-disciplinary integration of computational intelligence, behavioral decision theory, materials science, and organizational research

NEDMIL positions itself at the core of Industry 4.0 and the global sustainability transition, addressing emerging challenges in data-driven, AI-powered, and environmentally intelligent decision environments.
By integrating IoT-enabled sensing networks, big data analytics, and cyber-physical systems, the lab investigates how next-generation technologies reshape logistics, manufacturing, marine operations, and complex socio-technical systems in the context of climate resilience and circular economy goals.

Our international team of principal investigators, postdoctoral researchers, and doctoral candidates collaborates on projects that bridge theory and practice, tackling pressing global challenges such as intelligent logistics networks, sustainable mobility, corrosion prediction and maintenance optimization, resilient maritime infrastructures, and trustworthy AI for decision-making.

Through sustained global collaboration, rigorous peer review, and cross-cultural knowledge exchange, NEDMIL contributes to the advancement of decision science, sustainability, and applied artificial intelligence, shaping the future of how organizations, industries, and societies make complex, high-impact decisions in a rapidly evolving world.

Research Areas

AI-Powered Prescriptive Analytics & Decision Intelligence

Smart Systems for Complex Decisions
Building AI- and optimization-driven frameworks to support real-time strategic, tactical, and operational choices.

Focus Areas:

  • Hybrid AI-OR prescriptive models

  • Reinforcement learning for planning under uncertainty

  • Multi-objective trade-off optimization

  • AI dashboards for Industry 4.0

 

Digital Twins & Industry 4.0 Optimization

IoT-Enabled Smart Operations
Using IoT data, digital twins, and simulation-optimization to enhance resilience and efficiency in Industry 4.0 ecosystems.

Focus Areas:

  • Digital twin optimization for logistics and production

  • IoT-driven predictive analytics for operations

  • Cyber-physical systems optimization and control

  • Real-time resilience in smart factories and supply chains

Applied AI for Sustainability & Societal Systems

Decision Making for Sustainable Futures
Applying AI and decision analytics to design resilient systems in energy, healthcare, agriculture, and infrastructure.

Focus Areas:

  • AI-driven energy and resource optimization

  • Sustainable logistics and circular economy design

  • Healthcare decision support with predictive AI

  • Climate risk management and adaptation