In practice many applications demand efficient algorithms for the optimization of problems which are subject to dynamic changes of operating and environmental conditions. This project examines the benefits of dynamically reconfigurable architecture as a platform for the implementation of optimization algorithms for dynamically changing optimization problems. The focus is put on Ant Colony Optimization (ant algorithms) as optimization algorithm.

The main aspects considered are:

  • Design, implementation and experimental studies of different types of ant algorithms based on dynamically reconfigurable hardware.
  • Development, application and validation of models and languages supporting the design and analysis of efficient hardware algorithms on reconfigurable architectures.
  • Analysis of the benefits of dynamic reconfiguration, self-reconfiguration/-adaptiveness and hardware/software repartitioning for dynamically changing optimization algorithms implemented in reconfigurable hardware