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