Special Session on AI–driven methods for Multimodal Networks and Processes Modeling (AIMPM)

Scope

The special session AI-driven methods for Multimodal Networks and Processes Modeling (AIMPM 2026) aims to provide an interdisciplinary forum for researchers and practitioners to present and discuss recent advances in artificial intelligence–based modeling, analysis, optimization, and control of multimodal networks and processes. The session focuses on complex, interconnected systems arising in domains such as manufacturing, transportation, logistics, telecommunication networks, and cyber-physical production systems, where multiple heterogeneous flows, resources, and decision layers coexist and interact.

SCOPE

Building on the established scope of previous AIMPM editions, the session emphasizes integrated and synchronized modeling of multimodal processes, including the coordination of transportation, production, information, and financial flows, as well as the interaction between physical infrastructures and digital services. AI-based approaches enable the representation and management of system complexity, uncertainty, and dynamics, supporting both strategic and operational decision-making.

In response to recent technological developments, AIMPM 2026 explicitly extends its scope to include digital twins of multimodal networks and processes. Digital twins are considered as data-driven and model-based virtual representations of real systems that support real-time monitoring, simulation, prediction, optimization, and adaptive control. Particular attention is given to the integration of digital twins with AI techniques—such as machine learning, evolutionary computation, constraint-based methods, hybrid AI/OR approaches, and simulation—to enable proactive, resilient, and autonomous decision support in complex multimodal environments.

Topics

The session therefore welcomes contributions addressing, among others:

AI-enhanced digital twins for manufacturing, logistics, transportation, and supply chains,
Modeling, simulation, and synchronization of multimodal production and distribution processes,
Planning, scheduling, and resource allocation under uncertainty and dynamic conditions,
Proactive and reactive control strategies supported by predictive and prescriptive analytics,
Integration of heterogeneous data sources, IoT, and cyber-physical systems into multimodal models,
Intelligent transport systems, vehicle routing, and network flow optimization,
Knowledge representation and reasoning for complex networked systems,
Security, robustness, and resilience of multimodal and digitally twinned systems.

Both theoretical foundations and practical applications, including industrial case studies, experimental results, and real-world implementations, are strongly encouraged. The AIMPM 2026 special session seeks to foster cross-domain exchange and to stimulate novel research directions at the intersection of artificial intelligence, multimodal systems modeling, and digital twin technologies.