  Complex scheduling problems require a large amount computation power and
innovative solution methods. The objective of this paper is the conception and
implementation of a multi-agent system that is applicable in various problem
domains. Independent specialized agents handle small tasks, to reach a
superordinate target. Effective coordination is therefore required to achieve
productive cooperation. Role models and distributed artificial intelligence are
employed to tackle the resulting challenges. We simulate a NP-hard scheduling
problem to demonstrate the validity of our approach. In addition to the general
agent based framework we propose new simulation-based optimization heuristics
to given scheduling problems. Two of the described optimization algorithms are
implemented using agents. This paper highlights the advantages of the
agent-based approach, like the reduction in layout complexity, improved control
of complicated systems, and extendability.
