Interaction networks and Collective intelligence Team

The RI2C team was built around the study of complex systems, focusing on the notion of interactions and on the emergence of collective intelligence within these systems.

• Temporal & dynamic graphs
• Collective intelligence
• Complex systems
• Optimization & operations research
• Logistics & port systems
• Drone swarms
• Blockchain & traceability
• Crisis & risk management

The general objective is to model the complex systems encountered in various application fields through interaction networks, and to study them.

We seek to understand, explain and model their behaviours and organisations, and to design new algorithmic approaches, with a strong applicative anchoring on the logistics and port corridor of the Seine Valley.

We consider several often complementary types of models: multi-agent, bio-inspired, graphs, and mathematical models from dynamical systems or optimization. The notion of interaction network is always present in our models.

Many problems on real complex systems are expressed as optimization problems, for instance scheduling or vehicle routing. We solve them using operations research tools: mathematical programming, metaheuristics and classical graph algorithms, revisited to meet the requirements arising from the dynamic and sometimes distributed nature of the systems.

We seek to understand the genesis of these networks and their structures (morphogenesis), and to simulate it using models based on dynamic graphs. We also characterise the emergence of global properties on these networks.

We design algorithms to steer these systems while guaranteeing certain properties related to connectivity, security, energy saving and the maintenance of geometric structures.

• Modelling and optimization for maritime and port logistics, and multimodal transport.
• Operations research for crisis management and reverse logistics (post-disaster dismantling and recovery).
• Coordination of drone swarms for victim search and surveillance in hazardous areas.
• Blockchain and traceability to secure exchanges in port information systems.
• Agent-based simulations: logistics flows, maritime and multimodal networks, crowd dynamics, information diffusion.
• Network morphogenesis and dynamic graph generation.

International collaborations

• Tunisia -- operations research, blockchain, bio-inspired methods (University of Sfax),
• Norway -- logistics, optimization, drones (Molde University College, NIBIO),
• Brazil -- operations research and optimization (Federal University of Fortaleza, U. São João del-Rei),
• Poland -- port logistics, dynamic graphs, sensor networks (Poznań),
• Thailand -- complex systems and collective intelligence (NECTEC),
• Algeria -- network analysis and complex systems,
• China -- complex systems and nonlinear dynamical systems,
• Spain and Portugal -- bio-inspired methods.

National institutional collaborations

• GIS ILI-VS (Institute for Smart Logistics in the Seine Valley)
• LOMC (UMR 6294) and LMAH -- Université Le Havre Normandie
• UMR Sebio, Ineris, ULHN, U. Reims
• GREAH EA 3220
• Le Havre Seine Métropole

National industry collaborations

• HAROPA PORT Le Havre
• SOGET (Smart LogiLab joint laboratory)
• 2SN and Carrefour
• CEGELEC Défense
• SQUADRONE System
• Bolloré Logistics
• SYNERZIP-LH
• ORMES (major-hazards office for the Seine estuary)

• NormaSTIC research federation - FR CNRS 3638
• GDR IM (computer science and mathematics)
  • Graphs working group
• GDR RO (operations research)
  • GT2L working group (transport-logistics)
• GDR OMER (ocean and seas)
  • PoMar working group (maritime ports)
• CSS-France (Complex Systems Society -- France)
• UNESCO UniTwin Chair Complex System Digital Campus
• GIS ILI-VS (smart logistics in the Seine Valley)

• PERMANENT STAFF: 19
• PHD STUDENTS: 12
• POSTDOCS: 2
• ENGINEERS: 1
• ASSOCIATE MEMBERS: 6