Universiteit Leiden Universiteit Leiden

Research

Research in natural computing is at the core of our activities, covering theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods. Some of our current projects, in particular, focus on the following areas:

  • Robust optimization using evolutionary algorithms
  • Multiple criteria decision support
  • Mixed-integer evolutionary strategies (MIES)
  • Cellular automata for simulation applications
  • Particle swarm algorithms
  • Multiparameter physics applications (e.g., quantum control)
  • Medical image analysis applications
  • Drug design by interactive and automatic evolution
  • Protein folding and docking applications
  • Supply chain applications

Beyond this, we are also executing projects in direct cooperation with industry (see collaborations for more information).

The driving force behind our research is the mission to increase our understanding of natural systems as models of computation, with a focus on the development of new algorithms and applications to challenging problems.

Our current publicly funded research projects are:

  • DAMIOSO: Data Mining on High Volume Simulation Output
  • CIMPLO: Cross-Industry Predictive Maintenance Optimization Platform
  • PROMIMOOC: Process mining for multi-objective online control (NWO)
  • EvoMPP: An Evolutionary Approach to Many-Parameter Physics (FOM)
  • DELIVER: Distributed Coordination for Continuous Planning (EUREKA)
  • SAVAGE: Self-Adaptation of Vision Agents through Genetic Evolution (NWO)
  • RODEO: Robust Design Optimization (NWO)
  • BETNET: The evolution of stochastic heterogeneous networks as bet-hedging adaptations to fluctuating environments (NWO)